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  • MPI Ethno. Forsch.  (5)
  • Regensburg UB
  • HeBIS
  • GRASSI Mus. Leipzig
  • Castanedo, Federico  (5)
  • Sebastopol, CA : O'Reilly Media  (5)
  • Albany : State University of New York Press
  • Electronic books  (5)
  • Python (Computer program language)
Datenlieferant
  • MPI Ethno. Forsch.  (5)
  • Regensburg UB
  • HeBIS
  • GRASSI Mus. Leipzig
Materialart
Sprache
Erscheinungszeitraum
Verfasser
Verlag/Herausgeber
  • Sebastopol, CA : O'Reilly Media  (5)
  • Albany : State University of New York Press
Schlagwörter
  • 1
    Online-Ressource
    Online-Ressource
    Understanding data governance : practices and frameworks for regulatory compliance and security (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Sprache: Englisch
    Seiten: 1 online resource (1 volume) , illustrations
    Schlagwort(e): Database management ; Management information systems ; Information resources management ; Information technology ; Management ; Electronic books ; Electronic books ; local
    Kurzfassung: 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.
    Anmerkung: Description based on online resource; title from title page (viewed January 9, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491990797/?ar
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
  • 2
    Online-Ressource
    Online-Ressource
    Delivering embedded analytics in modern applications : a product manager's guide to integrating contextual analytics (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Sprache: Englisch
    Seiten: 1 online resource (1 volume) , illustrations
    Ausgabe: First edition.
    Schlagwort(e): Application software ; Development ; Information technology ; Management ; Information visualization ; Decision making ; Data processing ; Electronic books ; Electronic books ; local
    Kurzfassung: 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
    Anmerkung: 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
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
  • 3
    Online-Ressource
    Online-Ressource
    Understanding metadata : create the foundation for a scalable data architecture (2017)
    Sebastopol, CA : O'Reilly Media
    Details
    Sprache: Englisch
    Seiten: 1 online resource (1 volume) , illustrations
    Ausgabe: First edition.
    Schlagwort(e): Metadata ; Electronic books ; Electronic books ; local
    Kurzfassung: One viable option for organizations looking to harness massive amounts of data is the data lake, a single repository for storing all the raw data, both structured and unstructured, that floods into the company. But that isn't the end of the story. The key to making a data lake work is data governance, using metadata to provide valuable context through tagging and cataloging. This practical report examines why metadata is essential for managing, migrating, accessing, and deploying any big data solution. Authors Federico Castanedo and Scott Gidley dive into the specifics of analyzing metadata for keeping track of your data-where it comes from, where it's located, and how it's being used-so you can provide safeguards and reduce risk. In the process, you'll learn about methods for automating metadata capture. This report also explains the main features of a data lake architecture, and discusses the pros and cons of several data lake management solutions that support metadata. These solutions include: Traditional data integration/management vendors such as the IBM Research Accelerated Discovery Lab Tooling from open source projects, including Teradata Kylo and Informatica Startups such as Trifacta and Zaloni that provide best of breed technology
    Anmerkung: Description based on online resource; title from title page (Safari, viewed April 10, 2017)
    URL: lizenzpflichtig
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
  • 4
    Online-Ressource
    Online-Ressource
    Advancing procurement analytics : capturing the long tail with simplified data preparation (2016)
    Sebastopol, CA : O'Reilly Media
    Details
    Sprache: Englisch
    Seiten: 1 online resource (1 volume) , illustrations
    Ausgabe: First edition.
    Schlagwort(e): Business logistics ; Data processing ; Purchasing ; Management ; Industrial procurement ; Management ; Electronic books ; Electronic books ; local
    Kurzfassung: One area where data analytics can have profound effect is your company's procurement process. Some organizations spend more than two thirds of their revenue buying goods and services, making procurement-out of all business activities-a key element in achieving cost reduction. This report examines how your company can significantly improve procurement analytics to solve business questions quickly and effectively. Author Federico Castanedo, Chief Data Scientist at WiseAthena.com, explains how a probabilistic, bottom-up approach can significantly increase the quality, speed, and scalability of your data preparation operations-whether you're integrating datasets or cleaning and classifying them. You'll learn how new solutions leverage automation and machine learning, including the Tamr platform, and help you take advantage of several data-driven actions for procurement-including compliance, price arbitrage, and spend recovery.
    Anmerkung: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed June 13, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781492042662/?ar
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
  • 5
    Online-Ressource
    Online-Ressource
    Data preparation in the big data era : best practices for data integration (2015)
    Sebastopol, CA : O'Reilly Media
    Details
    Sprache: Englisch
    Seiten: 1 online resource (1 volume)
    Ausgabe: First edition.
    Schlagwort(e): Business enterprises ; Data processing ; Information technology ; Management ; Information visualization ; Decision making ; Data processing ; Electronic books ; Electronic books ; local
    Kurzfassung: Preparing and cleaning data is notoriously expensive, prone to error, and time consuming: the process accounts for roughly 80% of the total time spent on analysis. As this O'Reilly report points out, enterprises have already invested billions of dollars in big data analytics, so there's great incentive to modernize methods for cleaning, combining, and transforming data. Author Federico Castanedo, Chief Data Scientist at WiseAthena.com, details best practices for reducing the time it takes to convert raw data into actionable insights. With these tools and techniques in mind, your organization will be well positioned to translate big data into big decisions. Explore the problems organizations face today with traditional prep and integration Define the business questions you want to address before selecting, prepping, and analyzing data Learn new methods for preparing raw data, including date-time and string data Understand how some cleaning actions (like replacing missing values) affect your analysis Examine data curation products: modern approaches that scale Consider your business audience when choosing ways to deliver your analysis
    Anmerkung: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed January 7, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492048329/?ar
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    MPI Ethno. Forsch.
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