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Enterprise data architecture best practices News
September 30, 2019
The list of vendors offering managed cloud database services is growing rapidly, which gives IT teams more opportunities to offload management of database systems.
August 29, 2019
Data management consultant Donna Burbank outlines how effective data governance hinges on the deployment of a comprehensive enterprise data architecture.
August 20, 2019
Self-service data preparation can duplicate work and slow down analytics. One possible fix: an internal marketplace where users can 'shop' for data assets.
May 31, 2019
It's right there in a MapR letter to California's labor department: A leader in the Hadoop market is desperately seeking funding after poor sales of its promising data platform.
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Big data, the cloud and analytics profoundly shape data warehouse purpose and design. Learn how companies derive value from a repository that at times needs definition. Continue Reading
Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization, as explained in this in-depth look at the process. Continue Reading
Hadoop is an open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems. Continue Reading
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There's still a place for data warehouses in data architectures. But first, ask whether your organization needs one and what type of technology platform is the best fit. Continue Reading
The various types of database software come with advantages, limitations and optimal uses that prospective buyers should be aware of before choosing a DBMS. Continue Reading
For companies considering third-party database tools, this handbook provides expert advice on evaluating and deploying on-premises and cloud options from third parties. Continue Reading
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As the concept of storing data and the technologies needed to do it evolve, companies with set goals in mind are building their data warehouses to maximize analytics outcomes. Continue Reading
This handbook provides advice on creating data catalogs to help data analysts and other users find information in corporate systems, plus insight on data catalog trends. Continue Reading
Data catalogs for analytics applications demand detailed assessment of user needs, cross-functional teams, ready access, continuous improvement and a self-sustaining system. Continue Reading
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Flooding a Hadoop cluster with data that isn't well organized and managed can stymie analytics efforts. Take these steps to help make your data lake accessible and usable. Continue Reading
Forrester's Mike Gualtieri details how to develop a unified plan to manage customer data that gives business users what they need to manage CRM programs. Continue Reading
What's the difference between DDL and DML? Get the answer and see examples of data manipulation language and data definition language commands for SQL databases. Continue Reading