Enterprise data architecture best practices

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8 Worst Practices in MDM and How You Can Avoid Them

Master data management (MDM) depends on the alignment and partnership between business and IT because both groups are responsible for improving data quality, accuracy, and streamlining data sharing across the enterprise. To help your organization along the journey to a successful MDM program, here are 8 worst practices in MDM and how you can avoid them.

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Enterprise data architecture best practices News

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.
August 29, 2019 29 Aug'19
Align enterprise data architecture, governance for 'quick wins'

Data management consultant Donna Burbank outlines how binding business and IT governance together effectively hinges on a comprehensive enterprise data architecture.
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.
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.

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Enterprise data architecture best practices Get Started

Bring yourself up to speed with our introductory content

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
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
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

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Evaluate Enterprise data architecture best practices Vendors & Products

Weigh the pros and cons of technologies, products and projects you are considering.

Database management tools from third parties make natives restless

Third-party database performance tools offer attractive alternatives to management software from DBMS vendors, provided their capabilities include orchestration, governance and integration. Continue Reading
Data warehouse vs. data lake vs. data mart: Beyond the RDBMS

There are many ways to store big data, but the choice of data warehouse vs. data lake vs. data mart comes down to who uses the data and how. Use this cheat sheet to compare. Continue Reading
10 Apache Kafka best practices for data management pros

How can data management teams most effectively deploy and use Apache Kafka in data pipelines and streaming applications? Here are some key guidelines to follow. Continue Reading

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Manage Enterprise data architecture best practices

Learn to apply best practices and optimize your operations.

GDPR, AI intensify privacy and data protection compliance demands

This guide covers the challenges data management teams face on data protection and privacy, particularly with the rise of GDPR and similar laws and the growing use of AI tools. Continue Reading
Data modeling techniques to overcome common business challenges

In this interview, author and data modeling instructor Steve Hoberman discusses techniques for dealing with challenges that may arise in the data modeling process. Continue Reading
Building leaner, meaner BI data sources

As business intelligence analysis and reporting platforms become increasingly important in the enterprise, so does the data that feeds them. Are your BI data sources up to par? Continue Reading

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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.

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
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
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

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