Enterprise data architecture best practices news, help and research

Enterprise data architecture best practices News

October 08, 2020 08 Oct'20
Denodo Platform 8.0 expands data virtualization features

The updated platform from Denodo looks to help organizations via enhanced features that connect and query disparate sources of data across different environments.
July 08, 2020 08 Jul'20
SODA Foundation launches to unify open source data management

A new Linux Foundation-sponsored group will support open source data management and promote interoperability between applications and data sources, on premises or cloud-based.
February 24, 2020 24 Feb'20
Lessons learned from Credit Karma GraphQL architecture

Credit Karma's vice president of engineering explains why and how the personal finance service is using the GraphQL data query technology to support its growing business.
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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big data as a service (BDaaS)

Big data as a service (BDaaS) is the delivery of data platforms and tools by a cloud provider to help organizations process, manage and analyze large data sets so they can generate insights in order to improve business operations and gain a ... Continue Reading
big data management

Big data management is the organization, administration and governance of large volumes of both structured and unstructured data. Continue Reading
15 big data tools and technologies to know about in 2021

Lots of tools are available to use in big data applications. Here's a look at the key features of 15 open source options to see if they fit your needs. Continue Reading

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

The ultimate guide to big data for businesses

Big data is the fuel for today's analytics applications. This in-depth big data guide explains how businesses can benefit from it and what they need to do to use it effectively. Continue Reading
How to build an all-purpose big data pipeline architecture

Like a superhighway system and its many on- and off-ramps, an enterprise's big data pipeline transports infinite amounts of collected data from its sources to its destinations. Continue Reading
Hadoop vs. Spark: Comparing the two big data frameworks

Hadoop and Spark are widely used big data frameworks. Here's a look at their features and capabilities and the key differences between the two technologies. Continue Reading

Learn to apply best practices and optimize your operations.

Data warehouse environment modernization tools and tips

A data warehouse environment is made up of many tools and systems. Read on to learn the history of the modern data warehouse and how they're currently evolving. Continue Reading
Investment in talent key for data quality in healthcare

Investing in training employees on proper data gathering and management practices is crucial for healthcare organizations seeking to ensuring data quality and patient care. Continue Reading
Building a strong data analytics platform architecture

A strong analytics platform is key to meeting demands in a data-driven business. Read on for the key components your platform architecture should include. Continue Reading

We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.

Data quality for big data: Why it's a must and how to improve it

As volumes of collected data increase exponentially, methods to improve and ensure big data quality are critical in making accurate, effective and trusted business decisions. Continue Reading
What data lake governance challenges do organizations face?

Consultant Anne Marie Smith details five challenges that an organization may face in applying data governance policies to data lakes and offers advice on how to overcome them. Continue Reading
5 data integration challenges and how to overcome them

Automation can solve a lot of data integration problems, but not all of them. Learn about the top five data integration challenges and what else to do to overcome them. Continue Reading