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  • Sebastopol, CA : O'Reilly Media  (45)
  • Cmabridge, MA : O'Reilly
  • Database management  (45)
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  • 1
    Online Resource
    Online Resource
    Financial governance for data processing in the cloud : managing costs while democratizing data at scale (2019)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Cloud computing ; Electronic data processing ; Information technology ; Management ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Cloud platforms are changing big data processing for the better, but there's one significant challenge: the problem of managing costs. Organizations used to on-premises solutions are often surprised by expense overruns for various tasks in the cloud, due to the ever-increasing amounts of structured, semi-structured, and unstructured data they collect and use. With this comprehensive guide, IT leaders, data architects, data engineers, and data analysts will examine several factors that affect cloud-based data processing costs. You'll also come away with a collection of financial governance best practices. Through the course of this ebook, you'll explore three areas essential to any successful governance plan: cost controls, traceability, and predictability. Authors Amit Duvedi, Balaji Mohanam, Andy Still, and Andrew Ash cover the processes, tools, and systems that will enable you to perform effective financial governance of your data processing platform. Learn how cloud-based financial governance differs from on-premises solutions Examine the way your company currently uses a cloud data platform Explore available cloud provider tools, third-party cloud management tools, and the new breed of analytic data platforms Dive into the stages of the financial governance lifecycle-to understand, control, and then optimize activity in your cloud platform Control your cloud costs while still meeting rising business demand and SLAs
    Note: Description based on online resource; title from title page (Safari, viewed June 17, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492049760/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Data science from scratch : first principles with Python (2019)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Database management ; Data structures (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: To really learn data science, you should not only master the tools-data science libraries, frameworks, modules, and toolkits-but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today's messy glut of data. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability-and how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest neighbors, Naïve Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
    Note: Previous edition published: 2015. - Includes bibliographical references and index. - Description based on online resource; title from title page (Safari, viewed April 24, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492041122/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Data engineers vs. data scientists : how misconceptions of data roles can hurt teams and compromise productivity (2019)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Database design ; Database management ; Teams in the workplace ; Job descriptions ; Electronic books ; Electronic books ; local
    Abstract: Data engineers and data scientists are not interchangeable-and misperceptions of their roles can hurt teams and compromise productivity. This article clears up the differences of each role and how to best optimize these roles.
    Note: "Report.". - Description based on online resource; title from cover (viewed June 3, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492082491/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
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  • 4
    Online Resource
    Online Resource
    Fifty years of data management and beyond (2019)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume)
    Keywords: Database management ; Electronic data processing ; Management ; Information technology ; Management ; Electronic books ; Electronic books ; local
    Abstract: Every decade since the 1960s, researchers at companies like IBM, Amazon, and many others have introduced major new frameworks and techniques to handle rising data management problems. This concise ebook explains how these new systems helped data science evolve quickly-from hierarchical and relational databases to big data and cloud computing to streaming and graph data. Computer scientist Paco Nathan shows members of your data science team how major companies created each of these data management systems not just to deal with new data types but also to take full advantage of the opportunities the data presented. Their efforts over the years have propelled an entire industry. This report covers the historical progression of data management topics including: Hierarchical databases -1960s mainframe batch systems are still used in finance, healthcare, manufacturing, energy, and other industries. Relational databases -these enabled faster transactions, mathematical optimization, and budgeting guarantees for many businesses. Big data -this includes relatively cheap horizontal scale-out systems for collecting huge amounts of customer data. Cloud computing -large companies began managing reliable, scalable, cost-effective data centers; Amazon turned the concept into a business. Cluster schedulers -managing horizontal clusters was difficult before schedulers such as Apache Mesos appeared. Streaming data -data continuously generated by different sources requires responses in "real time"-generally milliseconds.
    Note: Description based on online resource; title from title page (Safari, viewed May 31, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492057512/?ar
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    Online Resource
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  • 5
    Online Resource
    Online Resource
    Foundations for architecting data solutions : managing successful data projects (2018)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Big data ; Database management ; Electronic books ; Electronic books ; local
    Abstract: While many companies ponder implementation details such as distributed processing engines and algorithms for data analysis, this practical book takes a much wider view of big data development, starting with initial planning and moving diligently toward execution. Authors Ted Malaska and Jonathan Seidman guide you through the major components necessary to start, architect, and develop successful big data projects. Everyone from CIOs and COOs to lead architects and developers will explore a variety of big data architectures and applications, from massive data pipelines to web-scale applications. Each chapter addresses a piece of the software development life cycle and identifies patterns to maximize long-term success throughout the life of your project. Start the planning process by considering the key data project types Use guidelines to evaluate and select data management solutions Reduce risk related to technology, your team, and vague requirements Explore system interface design using APIs, REST, and pub/sub systems Choose the right distributed storage system for your big data system Plan and implement metadata collections for your data architecture Use data pipelines to ensure data integrity from source to final storage Evaluate the attributes of various engines for processing the data you collect
    Note: Includes index. - Description based on online resource; title from title page (Safari, viewed March 11, 2019)
    URL: lizenzpflichtig
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    Online Resource
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  • 6
    Online Resource
    Online Resource
    Architecting data lakes : data management architectures for advanced business use cases (2018)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Big data ; Database management ; Business enterprises ; Data processing ; Information technology ; Management ; Electronic books ; Electronic books ; local
    Abstract: Many organizations today are succeeding with data lakes, not just as storage repositories but as places to organize, prepare, analyze, and secure a wide variety of data. Management and governance is critical for making your data lake work, yet hard to do without a roadmap. With this ebook, you'll learn an approach that merges the flexibility of a data lake with the management and governance of a traditional data warehouse. Author Ben Sharma explains the steps necessary to deploy data lakes with robust, metadata-driven data management platforms. You'll learn best practices for building, maintaining, and deriving value from a data lake in your production environment. Included is a detailed checklist to help you construct a data lake in a controlled yet flexible way. Managing and governing data in your lake cannot be an afterthought. This ebook explores how integrated data lake management solutions, such as the Zaloni Data Platform (ZDP), deliver necessary controls without making data lakes slow and inflexible. You'll examine: A reference architecture for a production-ready data lake An overview of the data lake technology stack and deployment options Key data lake attributes, including ingestion, storage, processing, and access Why implementing management and governance is crucial for the success of your data lake How to curate data lakes through data governance, acquisition, organization, preparation, and provisioning Methods for providing secure self-service access for users across the enterprise How to build a future-proof data lake tech stack that includes storage, processing, data management, and reference architecture Emerging trends that will shape the future of data lakes
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed January 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492033004/?ar
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  • 7
    Online Resource
    Online Resource
    Gaining data agility with multi-model databases (2018)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Database management ; Information technology ; Management ; Agile software development ; Electronic books ; Electronic books ; local
    Abstract: Most organizations realize that their future depends on the ability to quickly adapt to constant changes brought on by variable and complex environments. It's become increasingly clear that the core source behind these innovative solutions is data. Polyglot persistence refers to systems that provide many different types of data storage technologies to deal with this vast variability of data. Applications that need to access data from more than one store have to navigate an array of databases in a complex-and ultimately unsustainable-maze. One solution to this problem is readily available. In this ebook, consultant Joel Ruisi explains how a multi-model database enables you to take advantage of many different types of data models (and multiple schemas) in a single backend. With a multi-model database, companies can easily centralize, manage, and search all the data the IT system collects. The result is data agility : the ability to adapt to changing environments and serve users what they need when they need it. Through several detailed use cases, this ebook explains how multi-model databases enable you to: Store and manage multiple heterogeneous data sources Consolidate your data by bringing everything in "as is" Invisibly extend model features from one model to another Take a hybrid approach to analytical and operational data Enhance user search experience, including big data search Conduct queries across data models Offer SQL without relational constraints
    Note: Description based on online resource; title from title page (Safari, viewed January 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492032946/?ar
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    Online Resource
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  • 8
    Online Resource
    Online Resource
    Cleaning up the data lake with an operational data hub (2018)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Database management ; Information storage and retrieval systems ; Electronic data processing ; Big data ; Electronic books ; Electronic books ; local
    Abstract: The data lake was once heralded as the answer to the flood of big data that arrived in a variety of structured and unstructured formats. But, due to the ease of integration and the lack of governance, data lakes in many companies have devolved into unusable data swamps. This short ebook shows you how to solve this problem using an Operational Data Hub (ODH) to collect, store, index, cleanse, harmonize, and master data of all shapes and formats. Gerhard Ungerer-CTO and co-founder of Random Bit LLC-explains how the ODH supports transactional integrity so that the hub can serve as integration point for enterprise applications. You'll also learn how the ODH helps you leverage the investment in your data lake (or swamp), so that the data trapped there can finally be ingested, processed, and provisioned. With this ebook, you'll learn how an ODH: Allows you to focus on categorizing data for easy and fast retrieval Provides flexible storage models, indexing support, query capabilities, security, and a governance framework Delivers flexible storage models; support for indexing, scripting, and automation; query capabilities; transactional integrity; and security Includes a governance model to help you access, ingest, harmonize, materialize, provision, and consume data
    Note: Description based on online resource; title from title page (viewed January 10, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492027386/?ar
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  • 9
    Online Resource
    Online Resource
    Getting started with Kudu : perform fast analytics on fast data (2018)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Apache Hadoop ; Electronic data processing ; Distributed processing ; Big data ; Real-time data processing ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Fast data ingestion, serving, and analytics in the Hadoop ecosystem have forced developers and architects to choose solutions using the least common denominator-either fast analytics at the cost of slow data ingestion or fast data ingestion at the cost of slow analytics. There is an answer to this problem. With the Apache Kudu column-oriented data store, you can easily perform fast analytics on fast data. This practical guide shows you how. Begun as an internal project at Cloudera, Kudu is an open source solution compatible with many data processing frameworks in the Hadoop environment. In this book, current and former solutions professionals from Cloudera provide use cases, examples, best practices, and sample code to help you get up to speed with Kudu. Explore Kudu's high-level design, including how it spreads data across servers Fully administer a Kudu cluster, enable security, and add or remove nodes Learn Kudu's client-side APIs, including how to integrate Apache Impala, Spark, and other frameworks for data manipulation Examine Kudu's schema design, including basic concepts and primitives necessary to make your project successful Explore case studies for using Kudu for real-time IoT analytics, predictive modeling, and in combination with another storage engine
    Note: Includes index. - Description based on online resource; title from title page (Safari, viewed April 10, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491980248/?ar
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  • 10
    Online Resource
    Online Resource
    Understanding data governance : practices and frameworks for regulatory compliance and security (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Database management ; Management information systems ; Information resources management ; Information technology ; Management ; Electronic books ; Electronic books ; local
    Abstract: From the moment your organization starts collecting data, it's crucial to make key decisions about governance. What data should you gather? How do you ensure it's accurate and current? Where do you store it, and for how long? Today, many policies for gathering and sharing data are determined in business suites, rather than by the nature of the data itself. In order to meet strategic business requirements, you must understand and define the rules that manage your organization's data assets. In this report, you'll examine the many aspects of data-driven governance, particularly how this approach makes automation, enforcement, and security tasks easier. Author Federico Castanedo of Vodafone Group describes the practices and frameworks for regulatory compliance, including technology that can marry your policies to data you collect and provide fine-grained access controls. Many businesses collect large volumes of structured, unstructured, geospatial, and other data types that often require NoSQL databases alongside relational platforms. This detailed report explores how multi-model databases support a wide range of data models against a single integrated backend, enabling your organization to easily define data-driven governance policies at scale-and ultimately to help you reduce compliance costs. Discover a new approach that establishes governance at the data level versus the system level in order to reduce risk, facilitate operational decisions, and improve integrity.
    Note: Description based on online resource; title from title page (viewed January 9, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491990797/?ar
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  • 11
    Online Resource
    Online Resource
    Designing data-intensive applications : the big ideas behind reliable, scalable, and maintainable systems (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Web site development ; Application software ; Development ; Database management ; Electronic books ; local ; Electronic books
    Abstract: Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
    Note: Includes index. - Description based on online resource; title from title page (Safari, viewed March 24, 2017)
    URL: lizenzpflichtig
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  • 12
    Online Resource
    Online Resource
    Data warehousing with Greenplum : open source massively parallel data analytics (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Data warehousing ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Relational databases haven't gone away, but they are evolving to integrate messy, disjointed unstructured data into a cleansed repository for analytics. With the execution of massively parallel processing (MPP), the latest generation of analytic data warehouses is helping organizations move beyond business intelligence to processing a variety of advanced analytic workloads. These MPP databases expose their power with the familiarity of SQL. This report introduces the Greenplum Database, recently released as an open source project by Pivotal Software. Lead author Marshall Presser of Pivotal Data Engineering takes you through the Greenplum approach to data analytics and data-driven decisions, beginning with Greenplum's shared-nothing architecture. You'll explore data organization and storage, data loading, running queries, as well as performing analytics in the database. You'll learn: How each networked node in Greenplum's architecture features an independent operating system, memory, and storage Four deployment options to help you balance security, cost, and time to usability Ways to organize data, including distribution, storage, partitioning, and loading How to use Apache MADlib for in-database analytics, and GPText to process and analyze free-form text Tools for monitoring, managing, securing, and optimizing query responses available in the Pivotal Greenplum commercial database
    Note: Includes bibliographical references. - Description based on online resource; title from title page (viewed February 4, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491983539/?ar
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  • 13
    Online Resource
    Online Resource
    Implementing a smart data platform : how enterprises survive in the era of smart data (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Information resources management ; Database management ; Computing platforms ; Design ; Electronic books ; Data mining ; Electronic books ; local
    Abstract: With the big data boom, the rise of the Internet of Things (IoT), and the development of artificial intelligence (AI) applications, we've entered a new era of smart data. Unfortunately, not many enterprises are ready for it. Some companies are deficient in data management, while others lack standard data engineering systems. Some simply lag behind in data science. The bottom line is that many enterprises have no advanced technical platform for building IoT-driven AI applications. But there is a practical solution. This report examines how the Smart Data Platform, or SmartDP, enables enterprises to enhance their capacities in data management, data engineering, and data science. Authors Yifei Lin and Xiao Wenfeng of TalkingData describe a complete SmartDP solution that involves data, platform products, data applications, and consulting services-components that together can supplement and strengthen your current data platforms. Explore SmartDP from concept to practice and discover how implementing this solution will allow your organization to achieve new business value.
    Note: Description based on online resource; title from title page (viewed January 9, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491983492/?ar
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  • 14
    Online Resource
    Online Resource
    Defining data-driven software development : developing on a multi-model database management system (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Database design ; Computer software ; Development ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Every year, developers learn new frameworks and languages not only to enhance productivity, but also to stay relevant in an ever-changing industry. And yet there's always a chance that tools you learn today won't be around next year. So you end up wasting your time, and worse, you waste the opportunity to learn something more relevant. This report examines the benefits of developing on a multi-model database that supports document, graph, relational, key-value, and other data models. Author Eric Laquer of MarkLogic describes tools and techniques for working directly with data as it arrives from the source, enabling your team to explore, on the fly, what a potential solution for a customer will look like. By leveraging what you already know about modeling and indexing data, a multi-model database will help you apply data management to the DevOps model and move past the limitations of rows and tables altogether. This report explores: How multi-model database management systems support a data-driven approach to software development Why applications that support data integration and analytic use cases can break a relational data model Case studies of two Fortune 50 companies that successfully adopted multi-model databases Why a data-driven approach requires collaboration among DBAs, sysadmins, analysts, and compliance and risk managers
    Note: Description based on online resource; title from title page (viewed January 10, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492049272/?ar
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  • 15
    Online Resource
    Online Resource
    Application delivery with DC/OS : building and running modern data-driven apps (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Apache Mesos (Electronic resource) ; Application software ; Development ; Cloud computing ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Developers and ops engineers have their hands full today delivering scalable, interconnected, always-on applications that can be consumed on a wide range of platforms-all while dealing with a container-driven distributed architecture. This practical report explores a new technology that can greatly aid the process: DC/OS from Mesosphere, a distributed operating system for managing multiple datacenter machines as if they were a single computer. Author Andrew Jefferson, VP Engineering at Tractable, demonstrates how the integrated set of software tools in DC/OS (Data Center Operating System) allows you to easily manage and run containerized apps and data services in production. You'll learn how to automate resource management, facilitate inter-process communication, and simplify the installation and management of distributed services. This report helps you: Learn exactly what DC/OS is and how it helps you configure and automate interdependent applications across on machine clusters Manage DC/OS clusters, and install and configure packages from Mesosphere's Universe registry Design and write applications to run on DC/OS, manage persistent state, and use service discovery Learn how to run DC/OS in production-from scaling, deployment, and security to monitoring and intrusion detection Discover the enterprise application architecture requirements that DC/OS addresses
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed December 6, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781491983454/?ar
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  • 16
    Online Resource
    Online Resource
    Database reliability engineering : designing and operating resilient database systems (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Database management ; Information technology ; Management ; Electronic books ; Electronic books ; local
    Abstract: The infrastructure-as-code revolution in IT is also affecting database administration. With this practical book, developers, system administrators, and junior to mid-level DBAs will learn how the modern practice of site reliability engineering applies to the craft of database architecture and operations. Authors Laine Campbell and Charity Majors provide a framework for professionals looking to join the ranks of today's database reliability engineers (DBRE). You'll begin by exploring core operational concepts that DBREs need to master. Then you'll examine a wide range of database persistence options, including how to implement key technologies to provide resilient, scalable, and performant data storage and retrieval. With a firm foundation in database reliability engineering, you'll be ready to dive into the architecture and operations of any modern database. This book covers: Service-level requirements and risk management Building and evolving an architecture for operational visibility Infrastructure engineering and infrastructure management How to facilitate the release management process Data storage, indexing, and replication Identifying datastore characteristics and best use cases Datastore architectural components and data-driven architectures
    Note: Includes index. . - Description based on online resource; title from title page (Safari, viewed November 2, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781491925935/?ar
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  • 17
    Online Resource
    Online Resource
    Building on multi-model databases : how to manage multiple schemas using a single platform (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Database management ; Application program interfaces (Computer software) ; Non-relational databases ; Electronic data processing ; Distributed processing ; Management ; Electronic books ; Electronic books ; local
    Abstract: In many organizations today, businesspeople are busy requesting unified views of data stored across multiple sources within their organizations. But integrating multiple data types from multiple data stores is a complex, error-prone, and time-consuming process of cobbling everything together manually. This concise book examines how multi-model databases can help you integrate data storage and access across your organization in a seamless and elegant way. Author Pete Aven and Diane Burley from MarkLogic explain how this latest evolution in data management naturally accepts heterogeneous data, enabling you to eventually phase out technical data silos. Through several case studies, you'll discover how organizations use multi-model databases to reduce complexity, save money, take advantage of opportunities, lessen risk, and shorten time to value. Get unified views across disparate data models and formats within a single database Learn how multi-model databases leverage the inherent structure of the data being stored Load and use unstructured and semi-structured data (such as documents and text) as is Provide agility in data access and delivery through APIs, interfaces, and indexes Learn how to scale a multi-model database, and provide ACID capabilities and security Examine how a multi-model database would fit into your existing architecture
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed January 3, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492049234/?ar
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  • 18
    Online Resource
    Online Resource
    Agile data mastering (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Big data ; Business enterprises ; Data processing ; Information technology ; Management ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Organizations across all industries are attempting to capitalize on the promise of Big Data by using their information assets as a source of competitive advantage. In doing so, they are investing heavily in areas such as analytic tools and new storage capabilities. However, they often neglect the data management layer of the equation: it's not simply about finding an optimal way to store or analyze the data, but it's also vital that you prepare and manage the data for consumption. After all, if the data is inaccurate or incomplete, no consumer will trust or use it. Typically, organizations expend a lot of time on manual data cleaning and vetting to create "master records"-a single, trusted view of an organizational entity such as a customer or supplier-and this is often the area where most help is needed. This report explains just how powerful machine learning can be when applied directly to the creation of master data records. Known as agile data mastering, this method leverages ML's speed and flexibility to quickly create accurate master records that can scale across datasets and domains. You'll learn agile data mastering processes based on the operation of Tamr, an enterprise-scale data unification company that applies human-guided machine learning to this task. This report explores the: Overall importance and many uses of master data records Challenge of creating these records in distributed, complex data environments Differences between traditional master data management (MDM) and agile data mastering Advantages of agile data mastering Technology of Tamr, a data unification company that provides agile data mastering solutions
    Note: Description based on online resource; title from title page (Safari, viewed January 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492028468/?ar
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    PostgreSQL : up and running : a practical guide to the advanced open source database (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: PostgreSQL ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Thinking of migrating to PostgreSQL? This clear, fast-paced introduction helps you understand and use this open source database system. Not only will you learn about the enterprise class features in versions 9.5 to 10, you'll also discover that PostgeSQL is more than a database system-it's an impressive application platform as well. With examples throughout, this book shows you how to achieve tasks that are difficult or impossible in other databases. This third edition covers new features, such as ANSI-SQL constructs found only in proprietary databases until now: foreign data wrapper (FDW) enhancements; new full text functions and operator syntax introduced in version 9.6; XML constructs new in version 10; query parallelization features introduced in 9.6 and enhanced in 10; built-in logical replication introduced in Version 10.e. If you're a current PostgreSQL user, you'll pick up gems you may have missed before. Learn basic administration tasks such as role management, database creation, backup, and restore Apply the psql command-line utility and the pgAdmin graphical administration tool Explore PostgreSQL tables, constraints, and indexes Learn powerful SQL constructs not generally found in other databases Use several different languages to write database functions Tune your queries to run as fast as your hardware will allow Query external and variegated data sources with foreign data wrappers Learn how to use built-in replication to replicate data
    Note: Includes index. - Description based on online resource; title from title page (viewed October 16, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781491963401/?ar
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    Architecting data lakes : data management architectures for advanced business use cases (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Big data ; Database management ; Business enterprises ; Data processing ; Information technology ; Management ; Electronic books ; Electronic books ; local
    Abstract: Many organizations use Hadoop-driven data lakes as an adjunct staging area for their enterprise data warehouses (EDW). But for those companies ready to take the plunge, a data lake is far more useful as a one-stop-shop for extracting insights from their vast collection of data. With this eBook, you'll learn best practices for building, maintaining, and deriving value from a Hadoop data lake in production environments. Authors Alice LaPlante and Ben Sharma explain how a data lake will enable your organization to manage an increasing volume of datasets-from blog postings and product reviews to streaming data-and to discover important relationships between them. Whether you want to control administrative costs in healthcare or reduce risk in financial services, this ebook addresses the architectural considerations and required capabilities you need to build your own data lake. With this report, you'll learn: The key attributes of a data lake, including its ability to store information in native formats for later processing Why implementing data management and governance in your data lake is crucial How to address various challenges for building and managing a data lake Self-service options that enable different users to access the data lake without help from IT Emerging trends that will shape the future of data lakes
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 11, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492042518/?ar
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  • 21
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    Real user measurements : why the last mile is the relevant mile (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Data mining ; Web databases ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Real User Measurements (RUM) is gaining recognition as an effective way to monitor user interaction with your website or application, but there are quite a few misconceptions about what RUM is and how it works. In this O'Reilly report, you'll dive into the essence of this decades-old technology to learn why anything that can be measured can be measured with RUM. Author Pete Mastin from Cedexis also demonstrates how RUM can track facets that affect the quality of your web service, including page load times and latency. Mastin specifically focuses on the last mile: the ISP or network that connects end users to the Internet. That last mile is often the best place to improve performance, and RUM can help you determine how. Learn the pros and cons of implementing RUM-and how it compares to synthetic measurements Use RUM for both active and passive monitoring, as well as top-down and bottom-up monitoring Crowd-source results by aggregating RUM measurements from several web-driven companies Implement RUM on your site or app at the webserver, switch, or browser Examine several use cases where the last mile is important, and understand the complexities involved Compare Internet RUM with other forms of Real User Measurements to provide context and deeper understanding Pete Mastin, Director of Market Strategy and Product Evangelism at Cedexis, has years of experience in technology and business strategy. He has deep knowledge of IP Video, content delivery networks (CDN), and Internet and Cloud technologies.
    Note: Description based on online resource; title from title page (Safari, viewed November 29, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781492029656/?ar
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  • 22
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    Cassandra : the definitive guide (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Distributed databases ; Database management ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This expanded second edition-updated for Cassandra 3.0-provides the technical details and practical examples you need to put this database to work in a production environment.
    Note: Description based on online resource; title from title page (viewed July 11, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781491933657/?ar
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  • 23
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    Architecting HBase applications : a guidebook for successful development and design (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Non-relational databases ; Big data ; Real-time data processing ; Distributed databases ; Electronic data processing ; Distributed processing ; Database management ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Lots of HBase books, online HBase guides, and HBase mailing lists/forums are available if you need to know how HBase works. But if you want to take a deep dive into use cases, features, and troubleshooting, Architecting HBase Applications is the right source for you. With this book, you'll learn a controlled set of APIs that coincide with use-case examples and easily deployed use-case models, as well as sizing/best practices to help jump start your enterprise application development and deployment.
    Note: Includes bibliographical references and index. - Description based on online resource; title from title page (viewed July 22, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781491915806/?ar
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  • 24
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    Type inheritance and relational theory : subtypes, supertypes, and substitutability : inheritance in The third manifesto (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Database management ; Relational databases ; Electronic data processing ; Electronic books ; Electronic books ; local
    Abstract: Type inheritance is that phenomenon according to which we can say, for example, that every square is also a rectangle, and so properties that apply to rectangles in general apply to squares in particular. In other words, squares are a subtype of rectangles, and rectangles are a supertype of squares. Recognizing and acting upon such subtype / supertype relationships provides numerous benefits: Certainly it can help in data modeling, and it can also provide for code reuse in applications. For these reasons, many languages, including the standard database language SQL, have long supported such relationships. However, there doesn't seem to be any consensus in the community at large on a formal, rigorous, and abstract model of inheritance. This book proposes such a model, one that enjoys several advantages over other approaches, not the least of which it is that it's fully compatible with the well known relational model of data.
    Note: Includes bibliographical references and index. - Description based on online resource; title from title page (viewed October 4, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781491959985/?ar
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  • 25
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    Modern PHP : new features and good practices (2015)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: PHP (Computer program language) ; Web site development ; Web sites ; Design ; Database management ; Database design ; Electronic books ; Electronic books ; local
    Abstract: PHP is experiencing a renaissance, though it may be difficult to tell with all of the outdated PHP tutorials online. With this practical guide, you'll learn how PHP has become a full-featured, mature language with object-orientation, namespaces, and a growing collection of reusable component libraries. You'll learn best practices for application architecture and planning, databases, security, testing, debugging, and deployment.
    Note: Includes index. - Description based on online resource; title from title page (Safari, viewed March 5, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781491905173/?ar
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  • 26
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    PostgreSQL : up and running (2015)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: 2nd edition
    Keywords: PostgreSQL ; Database management ; Database design ; Electronic books ; Electronic books ; local
    Abstract: Thinking of migrating to PostgreSQL? This clear, fast-paced introduction helps you understand and use this open source database system. Not only will you learn about the enterprise class features in versions 9.2, 9.3, and 9.4, you'll also discover that PostgeSQL is more than a database system-it's also an impressive application platform.
    Note: Subtitle on cover : practical guide to the advanced open source database. - Includes index. - Description based on online resource; title from title page (Safari, viewed December 11, 2014)
    URL: https://learning.oreilly.com/library/view/-/9781449373184/?ar
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  • 27
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    Oracle PL/SQL language : pocket reference (2015)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume)
    Edition: Fifth edition.
    Keywords: Oracle (Computer file) ; PL/SQL (Computer program language) ; Relational databases ; Electronic books ; Electronic books ; local
    Abstract: Be more productive with the Oracle PL/SQL language. The fifth edition of this popular pocket reference puts the syntax of specific PL/SQL language elements right at your fingertips, including features added in Oracle Database 12 c . Whether you're a developer or database administrator, when you need answers quickly, the Oracle PL/SQL Language Pocket Reference will save you hours of frustration.
    Note: Includes index. - Description based on online resource; title from title page (Safari, viewed September 23, 2015)
    URL: lizenzpflichtig
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    Getting started with Impala (2015)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Keywords: Apache Hadoop ; Parallel processing (Electronic computers) ; Data mining ; Database management ; SQL (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn how to write, tune, and port SQL queries and other statements for a Big Data environment, using Impala-the massively parallel processing SQL query engine for Apache Hadoop. The best practices in this practical guide help you design database schemas that not only interoperate with other Hadoop components, and are convenient for administers to manage and monitor, but also accommodate future expansion in data size and evolution of software capabilities. Ideal for database developers and business analysts, the latest revision covers analytics functions, complex types, incremental statistics, subqueries, and submission to the Apache incubator.
    Note: Description based on online resource; title from title page (Safari, viewed Oct. 10, 2014)
    URL: https://learning.oreilly.com/library/view/-/9781491905760/?ar
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  • 29
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    Managing the data lake : moving to big data analysis (2015)
    Sebastopol, CA : O'Reilly Media
    Details
    ISBN: 9781491941683 , 1491941685
    Language: English
    Pages: 1 online resource (1 volume)
    Edition: First edition.
    Keywords: Big data ; Quantitative research ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Organizations across many industries have recently created fast-growing repositories to deal with an influx of new data from many sources and often in multiple formats. To manage these data lakes, companies have begun to leave the familiar confines of relational databases and data warehouses for Hadoop and various big data solutions. But adopting new technology alone won't solve the problem. Based on interviews with several experts in data management, author Andy Oram provides an in-depth look at common issues you're likely to encounter as you consider how to manage business data. You'll explore five key topic areas, including: Acquisition and ingestion: how to solve these problems with a degree of automation. Metadata: how to keep track of when data came in and how it was formatted, and how to make it available at later stages of processing. Data preparation and cleaning: what you need to know before you prepare and clean your data, and what needs to be cleaned up and how. Organizing workflows: what you should do to combine your tasks-ingestion, cataloging, and data preparation-into an end-to-end workflow. Access control: how to address security and access controls at all stages of data handling. Andy Oram, an editor at O'Reilly Media since 1992, currently specializes in programming. His work for O'Reilly includes the first books on Linux ever published commercially in the United States.
    Note: Description based on online resource; title from title page (viewed January 4, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492049876/?ar
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    I [heart symbol] logs : event data, stream processing, and data integration (2015)
    Sebastopol, CA : O'Reilly Media
    Details
    ISBN: 9781491909386 , 1491909382
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Edition: 1st ed.
    Keywords: Data logging ; Data integration (Computer science) ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Why a book about logs? That's easy: the humble log is an abstraction that lies at the heart of many systems, from NoSQL databases to cryptocurrencies. Even though most engineers don't think much about them, this short book shows you why logs are worthy of your attention. Based on his popular blog posts, LinkedIn principal engineer Jay Kreps shows you how logs work in distributed systems, and then delivers practical applications of these concepts in a variety of common uses-data integration, enterprise architecture, real-time stream processing, data system design, and abstract computing models.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed Oct. 24, 2014)
    URL: lizenzpflichtig
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    Data science from scratch (2015)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Python (Computer program language) ; Database management ; Data structures (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the discipline without actually understanding data science. In this book, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch . If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today's messy glut of data holds answers to questions no one's even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability-and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
    Note: Includes index. - Description based on online resource; title from title page (Safari, viewed May 6, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781491901410/?ar
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    Data : emerging trends and technologies : how sensors, fast networks, AI, and distributed computing are affecting the data landscape (2014)
    Sebastopol, CA : O'Reilly Media
    Details
    ISBN: 9781491920732 , 1491920734
    Language: English
    Pages: 1 online resource (1 volume)
    Edition: First edition.
    Keywords: Electronic data processing ; Management ; Database management ; Electronic books ; Electronic books ; local
    Abstract: What are the emerging trends and technologies that will transform the data landscape in coming months? In this report from Strata + Hadoop World co-chair Alistair Croll, you'll learn how the ubiquity of cheap sensors, fast networks, and distributed computing have given rise to several developments that will soon have a profound effect on individuals and society as a whole. Machine learning, for example, has quickly moved from lab tool to hosted, pay-as-you-go services in the cloud. Those services, in turn, are leading to predictive apps that will provide individuals with the right functionality and content at the right time by continuously learning about them and predicting what they'll need. Computational power can produce cognitive augmentation. Report topics include: The swing between centralized and distributed computing Machine learning as a service Personal digital assistants and cognitive augmentation Graph databases and analytics Regulating complex algorithms The pace of real-time data and automation Solving dire problems with big data Implications of having sensors everywhere This report contains many more examples of how big data is starting to reshape business and change behavior, and it's just a small sample of the in-depth information Strata + Hadoop World provides. Pick up this report and make plans to attend one of several Strata + Hadoop World conferences in the San Francisco Bay Area, London, and New York.
    Note: Description based on online resource; title from title page (viewed January 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492048169/?ar
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    Apache Sqoop cookbook (2013)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.)
    Parallel Title: Erscheint auch als
    Keywords: Apache (Computer file : Apache Group) ; Relational databases ; Data warehousing ; Database design ; Database management ; Web site development ; Electronic books ; Electronic books ; local
    Abstract: Integrating data from multiple sources is essential in the age of big data, but it can be a challenging and time-consuming task. This handy cookbook provides dozens of ready-to-use recipes for using Apache Sqoop, the command-line interface application that optimizes data transfers between relational databases and Hadoop. Sqoop is both powerful and bewildering, but with this cookbook's problem-solution-discussion format, you'll quickly learn how to deploy and then apply Sqoop in your environment. The authors provide MySQL, Oracle, and PostgreSQL database examples on GitHub that you can easily adapt for SQL Server, Netezza, Teradata, or other relational systems. Transfer data from a single database table into your Hadoop ecosystem Keep table data and Hadoop in sync by importing data incrementally Import data from more than one database table Customize transferred data by calling various database functions Export generated, processed, or backed-up data from Hadoop to your database Run Sqoop within Oozie, Hadoop's specialized workflow scheduler Load data into Hadoop's data warehouse (Hive) or database (HBase) Handle installation, connection, and syntax issues common to specific database vendors
    Note: Description based on print version record
    URL: https://learning.oreilly.com/library/view/-/9781449364618/?ar
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    Access 2013 : the missing manual (2013)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Series Statement: The missing manual
    Parallel Title: Erscheint auch als
    Keywords: Microsoft Access ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Unlock the secrets of Access 2013 and discover how to use your data in creative ways. With this book's easy step-by-step instructions, you'll learn how to build and maintain a full-featured database and even turn it into a web app. You also get tips and practices from the pros for good database design-ideal whether you're using Access for business, school, or at home. The important stuff you need to know Build a database with ease. Organize and update lists, documents, catalogs, and other types of information. Create your own web app. Let your whole team work on a database in the cloud. Share your database on a network. Link your Access database to SQL Server or SharePoint. Customize the interface. Make data entry a breeze by building your own templates Find what you need fast. Search, sort, and summarize huge amounts of data in minutes. Put your info to use. Turn raw info into well-formatted printed reports. Dive into Access programming. Automate complex tasks and solve common challenges.
    Note: Includes index. - Description based on print version record
    URL: lizenzpflichtig
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    Business models for the data economy (2013)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.)
    Keywords: Database management ; Electronic data processing ; Data editing ; Databases ; Quality control ; Electronic books ; Electronic books ; local
    Abstract: You're sitting on a pile of interesting data. How do you transform that into money? It's easy to focus on the contents of the data itself, and to succumb to the (rather unimaginative) idea of simply collecting and reselling it in raw form. While that's certainly profitable right now, you'd do well to explore other opportunities if you expect to be in the data business long-term. In this paper, we'll share a framework we developed around monetizing data. We'll show you how to think beyond pure collection and storage, to move up the value chain and consider longer-term opportunities.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed Jan. 17, 2014)
    URL: https://learning.oreilly.com/library/view/-/9781491947036/?ar
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    Getting started with Storm (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Parallel Title: Erscheint auch als
    Keywords: Storm (Computer file) ; Database management ; Computer programming ; Electronic books ; Electronic books ; local
    Abstract: Even as big data is turning the world upside down, the next phase of the revolution is already taking shape: real-time data analysis. This hands-on guide introduces you to Storm, a distributed, JVM-based system for processing streaming data. Through simple tutorials, sample Java code, and a complete real-world scenario, you'll learn how to build fast, fault-tolerant solutions that process results as soon as the data arrives.
    Note: Description based on print version record
    URL: https://learning.oreilly.com/library/view/-/9781449324025/?ar
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    View updating and relational theory (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Keywords: Relational databases ; Design and construction ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Views are virtual tables. That means they should be updatable, just as "real" or base tables are. In fact, view updatability isn't just desirable, it's crucial , for practical reasons as well as theoretical ones. But view updating has always been a controversial topic. Ever since the relational model first appeared, there has been widespread skepticism as to whether (in general) view updating is even possible. In stark contrast to this conventional wisdom, this book shows how views, just like base tables, can always be updated (so long as the updates don't violate any integrity constraints). More generally, it shows how updating always ought to work, regardless of whether the target is a base table or a view. The proposed scheme is 100% consistent with the relational model, but rather different from the way updating works in SQL products today. This book can: Help database products improve in the future Help with a "roll your own" implementation, absent such product improvements Make you aware of the crucial role of predicates and constraints Show you how relational products are really supposed to behave Anyone with a professional interest in the relational model, relational technology, or database systems in general can benefit from this book.
    Note: Includes bibliographical references and index. - Description based on online resource; title from PDF title page (Safari, viewed Jan. 24, 2013)
    URL: https://learning.oreilly.com/library/view/-/9781449357832/?ar
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    High performance MySQL (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (xxviii, 793 p.) , ill.
    Edition: 3rd ed.
    Parallel Title: Erscheint auch als
    Keywords: MySQL (Electronic resource) ; SQL (Computer program language) ; Relational databases ; Database management ; Electronic books ; Electronic books ; local
    Abstract: How can you bring out MySQL's full power? With High Performance MySQL , you'll learn advanced techniques for everything from designing schemas, indexes, and queries to tuning your MySQL server, operating system, and hardware to their fullest potential. This guide also teaches you safe and practical ways to scale applications through replication, load balancing, high availability, and failover. Updated to reflect recent advances in MySQL and InnoDB performance, features, and tools, this third edition not only offers specific examples of how MySQL works, it also teaches you why this system works as it does, with illustrative stories and case studies that demonstrate MySQL's principles in action. With this book, you'll learn how to think in MySQL. Learn the effects of new features in MySQL 5.5, including stored procedures, partitioned databases, triggers, and views Implement improvements in replication, high availability, and clustering Achieve high performance when running MySQL in the cloud Optimize advanced querying features, such as full-text searches Take advantage of modern multi-core CPUs and solid-state disks Explore backup and recovery strategies-including new tools for hot online backups
    Note: First ed. by Jeremy D. Zawodny and . 2004. - Includes index. - Description based on print version record
    URL: https://learning.oreilly.com/library/view/-/9781449332471/?ar
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    MPI Ethno. Forsch.
  • 39
    Online Resource
    Online Resource
    PostgreSQL : up and running (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Keywords: PostgreSQL ; Database management ; Electronic books ; Electronic books ; local
    Abstract: If you're thinking about migrating to the PostgreSQL open source database system, this guide provides a concise overview to help you quickly understand and use PostgreSQL's unique features. Not only will you learn about the enterprise class features in the 9.2 release, you'll also discover that PostgeSQL is more than just a database system-it's also an impressive application platform. With numerous examples throughout this book, you'll learn how to achieve tasks that are difficult or impossible in other databases.
    Note: Description based on online resource; title from PDF title page (Safari, viewed Oct. 10, 2012)
    URL: https://learning.oreilly.com/library/view/-/9781449326326/?ar
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  • 40
    Online Resource
    Online Resource
    Programming Hive (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Edition: 1st ed.
    Parallel Title: Erscheint auch als
    Keywords: Apache Hive (Data warehouse system) ; Apache Hadoop (Computer file) ; Hive QL (Computer program language) ; Data warehousing ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Need to move a relational database application to Hadoop? This comprehensive guide introduces you to Apache Hive, Hadoop's data warehouse infrastructure. You'll quickly learn how to use Hive's SQL dialect-HiveQL-to summarize, query, and analyze large datasets stored in Hadoop's distributed filesystem. This example-driven guide shows you how to set up and configure Hive in your environment, provides a detailed overview of Hadoop and MapReduce, and demonstrates how Hive works within the Hadoop ecosystem. You'll also find real-world case studies that describe how companies have used Hive to solve unique problems involving petabytes of data. Use Hive to create, alter, and drop databases, tables, views, functions, and indexes Customize data formats and storage options, from files to external databases Load and extract data from tables-and use queries, grouping, filtering, joining, and other conventional query methods Gain best practices for creating user defined functions (UDFs) Learn Hive patterns you should use and anti-patterns you should avoid Integrate Hive with other data processing programs Use storage handlers for NoSQL databases and other datastores Learn the pros and cons of running Hive on Amazon's Elastic MapReduce
    Note: Includes bibliographical references and index. - Description based on print version record
    URL: https://learning.oreilly.com/library/view/-/9781449326944/?ar
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  • 41
    Online Resource
    Online Resource
    Getting started with Couchbase Server (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Keywords: Client/server computing ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Starting with the core architecture and structure of Couchbase Server, this title will tell you everything you need to know to install and setup your first Couchbase cluster. You'll be given guidance on sizing your cluster so that you maximise your performance. After installation, you'll be shown how to use the admin web console to administer your server, and then learn the techniques behind the specific tasks behind cluster management. This includes adding and removing nodes, rebalancing, and backing up and restoring your cluster.
    Note: Description based on online resource; title from PDF title page (Safari, viewed Sept. 21, 2012)
    URL: https://learning.oreilly.com/library/view/-/9781449331054/?ar
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  • 42
    Online Resource
    Online Resource
    Monitoring with Ganglia (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Parallel Title: Erscheint auch als
    Keywords: Web usage mining ; Internet users ; Statistics ; Data processing ; Database management ; Web site development ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Written by Ganglia designers and maintainers, this book shows you how to collect and visualize metrics from clusters, grids, and cloud infrastructures at any scale. Want to track CPU utilization from 50,000 hosts every ten seconds? Ganglia is just the tool you need, once you know how its main components work together. This hands-on book helps experienced system administrators take advantage of Ganglia 3.x. Learn how to extend the base set of metrics you collect, fetch current values, see aggregate views of metrics, and observe time-series trends in your data. You'll also examine real-world case studies of Ganglia installs that feature challenging monitoring requirements. Determine whether Ganglia is a good fit for your environment Learn how Ganglia's gmond and gmetad daemons build a metric collection overlay Plan for scalability early in your Ganglia deployment, with valuable tips and advice Take data visualization to a new level with gweb, Ganglia's web frontend Write plugins to extend gmond's metric-collection capability Troubleshoot issues you may encounter with a Ganglia installation Integrate Ganglia with the sFlow and Nagios monitoring systems Contributors include: Robert Alexander, Jeff Buchbinder, Frederiko Costa, Alex Dean, Dave Josephsen, Peter Phaal, and Daniel Pocock. Case study writers include: John Allspaw, Ramon Bastiaans, Adam Compton, Andrew Dibble, and Jonah Horowitz.
    Note: "Taking dynamic host and application metrics at scale"--Cover. - Includes index. - Description based on print version record
    URL: https://learning.oreilly.com/library/view/-/9781449330637/?ar
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  • 43
    Online Resource
    Online Resource
    MySQL troubleshooting (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (xvi, 243 p.) , ill.
    Edition: 1st ed.
    Parallel Title: Erscheint auch als
    Keywords: MySQL (Electronic resource) ; SQL (Computer program language) ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Stuck with bugs, performance problems, crashes, data corruption, and puzzling output? If you're a database programmer or DBA, they're part of your life. The trick is knowing how to quickly recover from them. This unique, example-packed book shows you how to handle an array of vexing problems when working with MySQL. Written by a principal technical support engineer at Oracle, MySQL Troubleshooting provides the background, tools, and expert steps for solving problems from simple to complex-whether data you thought you inserted doesn't turn up in a query, or the entire database is corrupt because of a server failure. With this book in hand, you'll work with more confidence. Understand the source of a problem, even when the solution is simple Handle problems that occur when applications run in multiple threads Debug and fix problems caused by configuration options Discover how operating system tuning can affect your server Use troubleshooting techniques specific to replication issues Get a reference to additional troubleshooting techniques and tools, including third-party solutions Learn best practices for safe and effective troubleshooting-and for preventing problems
    Note: Includes index. - Description based on print version record
    URL: https://learning.oreilly.com/library/view/-/9781449317836/?ar
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  • 44
    Online Resource
    Online Resource
    Microsoft SQL Server 2012 analysis services : the BISM Tabular Model (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (xxv, 625 p.) , ill.
    Parallel Title: Erscheint auch als
    Keywords: SQL server ; Client/server computing ; Relational databases ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Build agile and responsive Business Intelligence solutions Analyze tabular data using the BI Semantic Model (BISM) in Microsoft SQL Server 2012 Analysis Services-and discover a simpler method for creating corporate-level BI solutions. Led by three BI experts, you'll learn how to build, deploy, and query a BISM tabular model with step-by-step guides, examples, and best practices. This hands-on book shows you how the tabular model's in-memory database enables you to perform rapid analytics-whether you're a professional BI developer new to Analysis Services or familiar with its multidimensional model. Discover how to: Determine when a tabular or multidimensional model is right for your project Build a tabular model using SQL Server Data Tools in Microsoft Visual Studio 2010 Integrate data from multiple sources into a single, coherent view of company information Use the Data Analysis eXpressions (DAX) language to create calculated columns, measures, and queries Choose a data modeling technique that meets your organization's performance and usability requirements Optimize your data model for better performance with xVelocity storage engine Manage complex data relationships, such as multicolumn, banding, and many-to-many Implement security by establishing administrative and data user roles
    Note: Includes index. - Description based on print version record
    URL: https://learning.oreilly.com/library/view/-/9780735670099/?ar
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  • 45
    Online Resource
    Online Resource
    Microsoft SQL Server 2012 high-performance T-SQL using window functions (2012)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (xvii, 221 p.) , ill.
    Parallel Title: Erscheint auch als
    Keywords: SQL server ; Client/server computing ; Relational databases ; Database management ; Electronic books ; Electronic books ; local
    Abstract: Apply powerful window functions in T-SQL-and increase the performance and speed of your queries Optimize your queries-and obtain simple and elegant solutions to a variety of problems-using window functions in Transact-SQL. Led by T-SQL expert Itzik Ben-Gan, you'll learn how to apply calculations against sets of rows in a flexible, clear, and efficient manner. Ideal whether you're a database administrator or developer, this practical guide demonstrates ways to use more than a dozen T-SQL querying solutions to address common business tasks. Discover how to: Go beyond traditional query approaches to express set calculations more efficiently Delve into ordered set functions such as rank, distribution, and offset Implement hypothetical set and inverse distribution functions in standard SQL Use strategies for improving sequencing, paging, filtering, and pivoting Increase query speed using partitioning, ordering, and coverage indexing Apply new optimization iterators such as Window Spool Handle common issues such as running totals, intervals, medians, and gaps
    Note: "Microsoft.". - Includes index. - Description based on print version record
    URL: https://learning.oreilly.com/library/view/-/9780735671591/?ar
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  • 46
    Online Resource
    Online Resource
    Programming the Perl DBI (2000)
    Cmabridge, MA : O'Reilly | Boston, MA :Safari,
    Details
    Language: English
    Pages: p. cm
    DDC: 005.74
    Keywords: Database management ; Perl (Computer program language) ; Electronic books ; local
    Abstract: One of the greatest strengths of the Perl programming language is its ability to manipulate large amounts of data. Database programming is therefore a natural fit for Perl, not only for business applications but also for CGI-based web and intranet applications.The primary interface for database programming in Perl is DBI. DBI is a database-independent package that provides a consistent set of routines regardless of what database product you use--Oracle, Sybase, Ingres, Informix, you name it. The design of DBI is to separate the actual database drivers (DBDs) from the programmer's API, so any DBI program can work with any database, or even with multiple databases by different vendors simultaneously. Programming the Perl DBI is coauthored by Alligator Descartes, one of the most active members of the DBI community, and by Tim Bunce, the inventor of DBI. For the uninitiated, the book explains the architecture of DBI and shows you how to write DBI-based programs. For the experienced DBI dabbler, this book reveals DBI's nuances and the peculiarities of each individual DBD.The book includes: An introduction to DBI and its design How to construct queries and bind parameters Working with database, driver, and statement handles Debugging techniques Coverage of each existing DBD A complete reference to DBI This is the definitive book for database programming in Perl.
    URL: https://learning.oreilly.com/library/view/-/1565926994/?ar
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