Enterprise data architecture best practices
New & Notable
Databases vs. Data Warehouses vs. Data Lakes vs. Data Marts
This cheat sheet will help you better understand how each repository differs based on the type, purpose and quality of data. Plus, you’ll get an introduction to the features of data catalog software, a user-friendly metadata management system.
Enterprise data architecture best practices News
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September 30, 2019
30
Sep'19
Cloud database services multiply to ease admin work by users
The list of vendors offering managed cloud database services is growing rapidly, which gives IT teams more opportunities to offload management of database systems.
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August 29, 2019
29
Aug'19
Align enterprise data architecture, governance for 'quick wins'
Data management consultant Donna Burbank outlines how effective data governance hinges on the deployment of a comprehensive enterprise data architecture.
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August 20, 2019
20
Aug'19
Enterprise data marketplace aims to ease self-service chaos
Self-service data preparation can duplicate work and slow down analytics. One possible fix: an internal marketplace where users can 'shop' for data assets.
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May 31, 2019
31
May'19
MapR's future in jeopardy, layoffs loom
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.
Enterprise data architecture best practices Get Started
Bring yourself up to speed with our introductory content
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Data warehousing design and value change with the times
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
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What Is Data Management and Why Is It Important?
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
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Hadoop
Hadoop is an open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems. Continue Reading
Evaluate Enterprise data architecture best practices Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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Evaluating data warehouse platform options and your need for one
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
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Evaluating the different types of DBMS products
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
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Third-party database tools boast attractive alternatives
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
Manage Enterprise data architecture best practices
Learn to apply best practices and optimize your operations.
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Analytics demands add loftier goals to data warehouse strategies
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
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Data catalog best practices rely on teamwork, governance, tools
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
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Data catalog management for analytics fraught with unique demands
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
Problem Solve Enterprise data architecture best practices Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
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7 steps to a successful data lake implementation
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
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Four first steps for customer data management
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
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What's the difference between DDL and DML?
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