This chapter contains instructions for cataloging practices and special materials that present unique problems to catalogers. The provider-neutral cataloging model results in a single bibliographic record to describe all instances of the same manifestation of an online resource, a photocopy, or a print-on-demand reproduction regardless of which content publisher, aggregator, or provider has made the manifestation available. Provider-neutral cataloging is a practical solution to cataloging the growing number of online resources, photocopies, and print-on-demand reproductions for identical resources. Provider-neutral cataloging guidelines often conflict with other established cataloging instructions with which they are used. Provider-neutral cataloging guidelines were first developed for cataloging online resources and later expanded to include photocopies and print-on-demand reproductions. Provider-neutral cataloging of online serials began in and was expanded to include online textual monographs in and all other online resources in
Data Catalog—Enterprise Data Assets | Microsoft Azure
The editors at Solutions Review have compiled this list of of analytics data catalog tools to consider during vendor evaluation. The editors at Solutions Review have developed this resource to assist buyers in search of the best analytics data catalog tools to fit then needs of their organization. Choosing the right vendor and solution can be a complicated process — one that requires in-depth research and often comes down to more than just the solution and its technical capabilities. The product centralizes business terms and definitions, metrics, and information assets for discoverability and collaboration. Connect lets users discover the types of information their data contains, where the information comes from, who is using it, and how it is used. The tool features powerful search to find and reuse information in analytic apps, workflows, macros, visualizations, dashboards, and data science models as well.
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What is Azure Data Lake Analytics?
Run SQL and complex, analytic queries against structured and unstructured data in your data warehouse and data lake, without the need for unnecessary data movement. Quickly and easily process vast amounts of data in your data lake or on-premises for data engineering, data science development, and collaboration. Collect, process, and analyze streaming data, and load data streams directly into your data lakes, data stores, and analytics services so you can respond in real time.
Azure Data Lake Analytics is an on-demand analytics job service that simplifies big data. Instead of deploying, configuring, and tuning hardware, you write queries to transform your data and extract valuable insights. The analytics service can handle jobs of any scale instantly by setting the dial for how much power you need. You only pay for your job when it is running, making it cost-effective. Azure Data Lake analytics service is updated on an aperiodic basis for certain purpose.