Enterprise data architecture best practices

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Enterprise data architecture best practices News

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.
May 01, 2019 01 May'19
Snowflake CEO Bob Muglia replaced by former ServiceNow CEO

Frank Slootman, who led ServiceNow and Data Domain through successful IPOs, is the new chairman and CEO of cloud data warehouse vendor Snowflake, replacing former CEO Bob Muglia.
April 30, 2019 30 Apr'19
Snowflake CEO Bob Muglia talks cloud data warehouse evolution

In this Q&A, now-former Snowflake CEO Bob Muglia discusses the vendor's decision to embrace cloud data warehousing and how the industry is changing as more data moves to the cloud.

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Enterprise data architecture best practices Get Started

Bring yourself up to speed with our introductory content

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
Big data containers gain wider appeal in system deployments

This handbook examines the use of Docker containers in Kubernetes clusters to run big data systems and offers insight on container deployment and management issues. Continue Reading
Data virtualization tools promote anywhere, anytime data access

This online handbook examines data virtualization software and how organizations are deploying and using the technology as part of their data integration processes. 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.

Data management roles: Data architect vs. data engineer, others

Veteran data professional Michael Bowers differentiates between key data management positions, including their salaries and which ones can add the most business value. Continue Reading
Container technologies promise more agility for big data apps

Along with the ability to provide greater agility and flexibility for big data applications, containers can play a role in IT strategy that drives real-time decision-making. Continue Reading
Data virtualization benefits seen in unified views, IT agility

Through in-place integration, data virtualization platforms can provide wider access to data and simplify security and governance. But they come with some limitations. Continue Reading

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Manage Enterprise data architecture best practices

Learn to apply best practices and optimize your operations.

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
Data virtualization layer feeds logical data warehouse, Agile BI

Indiana University is using data virtualization to combine data from various source systems for analysis, as part of an initiative to improve strategic decision-making. 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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