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  • Online Resource  (11)
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  • Oram, Andrew  (11)
  • Sebastopol, CA : O'Reilly Media  (11)
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  • Online Resource  (11)
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  • 1
    Online Resource
    Online Resource
    Data lake maturity model : charting a course for data success (2019)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Electronic data processing ; Distributed processing ; Management ; Big data ; Information storage and retrieval systems ; Electronic books ; Electronic books ; local
    Abstract: Data is changing everything. Many industries today are being fundamentally transformed through the accumulation and analysis of large quantities of data, stored in diversified but flexible repositories known as data lakes. Whether your company has just begun to think about big data or has already initiated a strategy for handling it, this practical ebook shows you how to plan a successful data lake migration. You'll learn the value of data lakes, their structure, and the problems they attempt to solve. Using Zaloni's data lake maturity model, you'll then explore your organization's readiness for putting a data lake into action. Do you have the tools and data architectures to support big data analysis? Are your people and processes prepared? The data lake maturity model will help you rate your organization's readiness. This report includes: The structure and purpose of a data lake Descriptive, predictive, and prescriptive analytics Data lake curation, self-service, and the use of data lake zones How to rate your organization using the data lake maturity model A complete checklist to help you determine your strategic path forward
    Note: Description based on online resource; title from title page (viewed June 4, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491996560/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    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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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Delivering embedded analytics in modern applications : a product manager's guide to integrating contextual analytics (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Application software ; Development ; Information technology ; Management ; Information visualization ; Decision making ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Organizations are rapidly consuming more data than ever before, and to drive their competitive advantage, they're demanding interactive visualizations and interactive analyses of that data be embedded in their applications and business processes. This will enable them to make faster and more effective decisions based on data, not guesses. This practical book examines the considerations that software developers, product managers, and vendors need to take into account when making visualization and analytics a seamlessly integrated part of the applications they deliver, as well as the impact of migrating their applications to modern data platforms. Authors Federico Castanedo (Vodafone Group) and Andy Oram (O'Reilly Media) explore the basic requirements for embedding domain expertise with fast, powerful, and interactive visual analytics that will delight and inform customers more than spreadsheets and custom-generated charts. Particular focus is placed on the characteristics of effective visual analytics for big and fast data. Learn the impact of trends driving embedded analytics Review examples of big data applications and their analytics requirements in retail, direct service, cybersecurity, the Internet of Things, and logistics Explore requirements for embedding visual analytics in modern data environments, including collection, storage, retrieval, data models, speed, microservices, parallelism, and interactivity Take a deep dive into the characteristics of effective visual analytics and criteria for evaluating modern embedded analytics tools Use a self-assessment rating chart to determine the value of your organization's BI in the modern data setting
    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/-/9781491984451/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    2016-2017 web salary survey : tools, trends, what pays (and what doesn't) for web professionals (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations, map
    Edition: First edition.
    Keywords: Web site development industry ; Employees ; Salaries, etc ; Computer industry ; Employees ; Salaries, etc ; Electronic data processing personnel ; Salaries, etc ; Electronic books ; Electronic books ; local
    Abstract: The speed of change in web development, in terms of favored tooling, techniques, and standards, allows for much innovation in a vibrant ecosystem of developers. It also presents challenges for those trying to keep up. What can you earn as a web developer today? How does the type of job, the language you use, or your geographic location affect your salary? Based on a survey of more than 2,000 developers, O'Reilly's inaugural web salary survey provides valuable insight from respondents in 51 countries and all 50 US states. This survey, conducted in the spring of 2016, examines the current world of software development-and the careers that propel it-in great detail. In this report, you'll learn: Salaries by country and by regions in the US, as well as by age, education, gender, and bargaining skills The best and worst industries to work for in this field, and how company size determines salary amount How web developer salaries are affected by job title, number of hours worked per week, and on-the-job activities Respondents' choices of different languages, platforms, and tools, including clusters of related tools
    Note: Description based on online resource; title from title page (viewed February 11, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491990674/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    Hadoop and Spark performance for the Enterprise : ensuring quality of service in multi-tenant environments (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Apache Hadoop ; Spark (Electronic resource : Apache Software Foundation) ; Electronic data processing ; Distributed processing ; Information technology ; Management ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Virtually every enterprise depends on big data analysis, but distributed computing environments such as Hadoop and Spark are complicated, to say the least. Multiple users, business units, and workload types often compete for valuable computing resources. Monitoring tools are not well equipped to handle this level of complexity, and typically provide only very high-level and historical information. The lack of fine-grained visibility for making real-time adjustments to running workloads means that high-priority jobs can easily be pushed aside by lower-priority jobs. It's time to bring Quality of Service (QoS) to distributed processing in multi-tenant Hadoop environments. This O'Reilly report explains how QoS allows operators to assign priorities to jobs, ensuring that higher-priority tasks get the resources needed to meet critical deadlines. Author Andy Oram examines the critical role of performance in the evolution of operating systems, data warehouses, and distributed processing. He also discusses Quasar (part of Mesos) and Pepperdata, two tools that can help improve performance in distributed computing environments. You'll discover how tools that help ensure QoS can help distributed environments evolve to accommodate: Multiple users contending for resources, such as those on operating systems Jobs that grow or shrink in hardware usage, so they don't strain at resource limits or let resources go to waste Jobs of different priorities, including soft real-time requirements that allow them to override lower-priority or adhoc jobs Performance guarantees, similar to service-level agreements (SLAs)
    Note: Description based on online resource; title from title page (Safari, viewed December 12, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781492048985/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Scaling data science for the Industrial Internet of Things : advanced analytics in real time (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Big data ; Electronic data processing ; Distributed processing ; Management ; Information technology ; Management ; Information visualization ; Internet of things ; Electronic books ; Electronic books ; local
    Abstract: One estimate holds that, by 2020, businesses involved with the Internet of Things will spend roughly 26% of their entire IoT cost on technologies and services that store, integrate, visualize, and analyze data from various IoT devices-or nearly twice what IoT companies spend today. Conventional techniques for extracting and evaluating IoT data need to get a lot smarter if companies are to keep pace with the phenomena they're tracking. In this report, author Andy Oram discusses the state of IoT analytics by examining ThingWorx and its partners Glassbeam and National Instruments-companies that provide development tools and capabilities for building and running IoT applications. By learning how to use modern techniques to automate and speed up analytics on IoT projects, you can gain an edge in security, customer satisfaction, and operational efficiencies. Understand the demands of IoT analytics by exploring examples of farm, factory, vehicle maintenance, and healthcare automation Explore the characteristics of predictive analytics, a realm where you don't know in advance which factors are relevant Examine the tools for IoT analytics used by companies at various levels of data analytics Get revealing case studies of IoT analytics from ThingWorx, Glassbeam, and National Instruments
    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/-/9781492049265/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 7
    Online Resource
    Online Resource
    Pitching your IoT project : how to get executive buy-in (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume)
    Edition: First edition.
    Keywords: Internet of things ; New products ; Information technology ; Organizational change ; Electronic books ; Electronic books ; local
    Abstract: If you're a developer trying to get corporate buy-in for an IoT project, you need to understand that this pitch is much different than one for a typical new product or technology buy. Without fully realizing it, you may be asking for many things in one pitch: new approaches to interdepartmental communication, new ways to make management decisions based on the data your project will generate, new forms of customer interaction, and/or even major changes in staffing. This report from veteran O'Reilly editor Andy Oram delivers practical advice for preparing a compelling IoT pitch to CxO-level execs. Not only will you need to demonstrate how your project will improve the product, the customer experience, or the manufacturing or delivery processes, you also should be aware of how these changes will affect your relationships with suppliers, customers, and even competitors. This report explores the challenges and provides strategies for a successful pitch.
    Note: Description based on online resource; title from title page (Safari, viewed June 11, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781492042433/?ar
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    Online Resource
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  • 8
    Online Resource
    Online Resource
    Trends shaping the London tech scene (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: High technology ; England ; London ; London (England) ; Economic conditions ; Electronic books ; Electronic books ; local
    Abstract: London has been a world leader in finance, journalism, trade, the arts, and government for ages, but you don't hear much about computer technology. With this report, you'll learn that-while London is no Silicon Valley-the city's tech scene over the past decade has not only pervaded all of its world-leading activities, it's also created a vibrant, independent business environment of its own. Author Andy Oram, Senior Editor at O'Reilly, provides a comprehensive view of the London tech scene-where it stands, what feeds its strengths, and who is participating. This report explores: London's computer technologists: where in the world they come from, and how they got their skills The strong tech community and rich meetup culture, particularly in the Python, Java, and PHP spaces How London startups are breaking new ground on several recent innovations The active role played by the Government Digital Service (GDS) in pursuing new projects Why London tech companies stay small for a longer period than comparable US firms Current speculations about how the Brexit will influence the tech community
    Note: Description based on online resource; title from title page (viewed February 4, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492051732/?ar
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    Online Resource
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  • 9
    Online Resource
    Online Resource
    2016 software development salary survey : tools, trends, titles : what pays (and what doesn't) for programming professionals in Europe (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Computer programmers ; Salaries, etc ; Europe ; Computer software ; Development ; Computer industry ; Employees ; Salaries, etc ; Europe ; Electronic data processing personnel ; Salaries, etc ; Europe ; Electronic books ; Electronic books ; local
    Abstract: Of the more than 5,000 participants in O'Reilly Media's 2016 Software Development Salary Survey, 1,353 software engineers, developers, and other programming professionals live and work in Europe. This report includes complete survey results from those respondents, including participants in organizations both large and small, and from a wide variety of industries. You'll learn about the current state of software development-and the careers that propel it-across Europe today. This report presents European survey results, including: The top programming languages that respondents currently use professionally Where, by country, European programmers make the highest salaries Salary ranges by industry and by specific programming language The difference in earnings between programmers who work on very small teams vs. those who work on larger teams The most common programming languages that European respondents no longer use in their work The most common languages that respondents intend to learn within the next couple of years Find out where you stand in the European programming world. We encourage you to plug your own data points into our survey model to see how you compare to other programming professionals in your industry.
    Note: Description based on online resource; title from title page (viewed February 12, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492049104/?ar
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    Online Resource
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  • 10
    Online Resource
    Online Resource
    Search-driven business analytics : designing a new search engine for data (2015)
    Sebastopol, CA : O'Reilly Media
    Details
    ISBN: 9781491938133 , 1491938137
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: First edition.
    Keywords: Data mining ; Computer programs ; Quantitative research ; Computer programs ; Electronic information resource searching ; Search engines ; Electronic books ; Electronic books ; local
    Abstract: Compared to the speed and convenience of major web search engines, most business intelligence (BI) products are slow, stiff, and unresponsive. Business leaders today often wait days or weeks to get BI reports on inquiries about customers, products, or markets. But the latest BI products show that a significant change is taking place-a change led by search. This O'Reilly report examines three recent products with intelligent search capabilities: the ThoughtSpot Analytical Search Appliance, Microsoft's Power BI service, and an offering from Adatao. You'll learn how these products can provide you with answers and visualizations as quickly as questions come to mind. You'll investigate: The convergence of BI and search What a search-driven user experience looks like The intelligence required for analytical search Data sources and their associated data modeling requirements Turning on-the-fly calculations into visualizations Applying enterprise scale and security to search
    Note: Description based on online resource; title from title page (viewed January 4, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492049890/?ar
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  • 11
    Online Resource
    Online Resource
    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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