Enterprise data architecture best practices

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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.

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Enterprise data architecture best practices News

January 22, 2019 22 Jan'19
New Teradata CEO pursues cloud-based architecture

Cloud architecture, analytics and AI data processing are top innovation priorities for new Teradata CEO Oliver Ratzesberger. He talks about his goals in this Q&A.
December 28, 2018 28 Dec'18
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.
December 18, 2018 18 Dec'18
Datawatch Swarm on path to combine data prep, analytics

Datawatch plans to add analytics and data visualization tools to its Swarm data preparation platform, starting with integration capabilities in a Swarm 2.2 release.
November 30, 2018 30 Nov'18
Amazon Timestream, QLDB aim to grab more DBMS users for AWS

Built-for-purpose databases target general ones, especially in the cloud. At re:Invent 2018, AWS added time-series and transaction ledger databases to expand its line.

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Enterprise data architecture best practices Get Started

Bring yourself up to speed with our introductory content

data analytics (DA)

Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. Continue Reading
data mart (datamart)

A data mart is a repository of data that is designed to serve a particular community of knowledge workers. Continue Reading
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

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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.

5 data management infrastructure technologies to evaluate

It's the start of a new year -- is your organization ready to face the data management challenges ahead? Here are five technologies to consider adopting. Continue Reading
Graph database use cases reveal relationships in data sets

Graph databases specialize in mapping relationships in data sets, particularly complex ones. We explore how they work and the applications they're suited for. Continue Reading
Advantages of graph databases: Easier data modeling, analytics

Graph databases are finding a place in analytics applications at organizations that need to be able to map and understand the connections in large and varied data sets. Continue Reading

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Manage Enterprise data architecture best practices

Learn to apply best practices and optimize your operations.

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
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
Mining equipment maker uses BI on Hadoop to dig for data

BI on Hadoop is still new, but moving BI to data is trending. A data scientist working with IoT data at Komatsu sees the importance of getting big data to the right people. 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.

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
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

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