Enterprise data architecture best practices
New & Notable
Machine Learning Meets Data Quality
Read an exclusive interview with Andrew Burt, chief privacy offer and legal engineer at Immuta Inc., on data governance and machine learning integration. Plus, uncover steps IT managers are taking to improve data quality in their big data environments in order to ensure analytics accuracy.
Enterprise data architecture best practices News
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April 04, 2019
04
Apr'19
Tools manage performance for big data cloud applications
Tools such as Unravel and Pepperdata offer a way to measure performance of big data cloud applications, which may aid companies with on-premises configuration issues.
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March 21, 2019
21
Mar'19
Machine learning approaches gain critical mass for data pros
Machine learning will bring change to analytics and data management, said data luminary Michael Stonebraker. Others agree managing such change will take special effort.
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March 15, 2019
15
Mar'19
Big data management practices gain attention amid risks
Many data professionals have yet to solidify traditional data management practices, but they have a new set of challenges to overcome to ensure data privacy and avoid misuse.
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March 12, 2019
12
Mar'19
Aerospike database garners Spark, Kafka connectors
Apache Kafka and Apache Spark connectors ease use of the Aerospike NoSQL data store in high-speed applications such as analytics that are becoming more broadly supported.
Enterprise data architecture best practices Get Started
Bring yourself up to speed with our introductory content
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data analytics (DA)
Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. Continue Reading
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data mart (datamart)
A data mart is a repository of data that is designed to serve a particular community of knowledge workers. Continue Reading
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Good data quality for machine learning is an analytics must
As companies add machine learning applications, they need to really understand -- and be able to improve -- their data. That's where data quality initiatives come in. 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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4 factors to consider in a Hadoop distributions comparison
Examine the key characteristics necessary to evaluate in a Hadoop distribution comparison, focusing on enterprise features, subscription options and deployment models. Continue Reading
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Augmented data management draws more enterprise interest
With AI and machine learning, organizations are starting to augment their data management. This is changing the way enterprise users capture, govern and integrate data. Continue Reading
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Explore Hadoop distributions to manage big data
Discover the uses of Hadoop distributions and the first steps in evaluating these products, as well as how the merger of rivals Cloudera and Hortonworks affects the market. Continue Reading
Manage Enterprise data architecture best practices
Learn to apply best practices and optimize your operations.
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Data management trends for 2019: Governance, DataOps, cloud
Better data governance, increased cloud use and wider DataOps adoption head the list of trends for data management teams to plan for in 2019, IT analysts say. Continue Reading
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How to build a master data index: Static vs. dynamic indexing
Expert David Loshin explores the differences between static and dynamic indexing in master data management systems, and which queries each approach can support. Continue Reading
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Big data platform broadens place in analytics architecture
Big data platforms stumbled a bit getting out of the prototyping stage. But a view from the Strata Data Conference in New York sees broader use in the offing. 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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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
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Data integration techniques to help keep BI data consistent
Data integration processes that aren't managed properly can create inconsistent data in BI and analytics applications. Here are some steps to avoid that problem. Continue Reading