Enterprise data warehouse management

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Databases vs. Data Warehouses vs. Data Lakes vs. Data Marts

This cheat sheet will help you better understand how each repository differs based on the type, purpose and quality of data. Plus, you’ll get an introduction to the features of data catalog software, a user-friendly metadata management system.

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Enterprise data warehouse management News

March 04, 2020 04 Mar'20
Microsoft boosts Azure big data strategy with Hadoop distro

Microsoft Azure's HDInsight has a new, company-backed distribution of Hadoop, which should reassure customers interested in hybrid big data deployments.
February 25, 2020 25 Feb'20
Databricks Data Ingestion Network brings data to lakehouse

Databricks Ingest entered a public preview in a move by Databricks to enable a lakehouse that combines the best features of the data lake and data warehouse models.
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.
February 11, 2020 11 Feb'20
Snowflake raises $479 million to boost cloud data warehouse

Snowflake is looking to grow its data warehouse platform with new funding and a partnership with Salesforce that could differentiate its platform from rivals.

Enterprise data warehouse management Get Started

Bring yourself up to speed with our introductory content

How to handle data management in the cloud

Managing data in the cloud can result in cost and management complexities. But you can also use the technology to get a deeper understanding of your data. Continue Reading
What steps are key to building a data catalog?

An enterprise data catalog can help data stewards and other users in an organization manage metadata and explore data assets. Here are 10 key steps for creating a data catalog. Continue Reading
Extract, Load, Transform (ELT)

Extract, Load, Transform (ELT) is a data integration process for transferring raw data from a source server to a data system (such as a data warehouse or data lake) on a target server and then preparing the information for downstream uses. Continue Reading

Evaluate Enterprise data warehouse management Vendors & Products

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

Data hub vs. data lake: Deciphering the differences

Data lakes and data hubs are approaches to data management that are typically opposed. Here are the main differences between these two storage options. Continue Reading
3 of the top use cases for graph databases

Graph databases establish many unique relationships between data points. These unusual relationships are beneficial in many use cases, but here are the top three. Continue Reading
Ethical data collection in the spotlight over new regulations

New regulations have put data privacy top of mind for many consumers. Here's a look at how businesses can incorporate ethical data collection -- and even benefit from it. Continue Reading

Manage Enterprise data warehouse management

Learn to apply best practices and optimize your operations.

How to build an effective streaming data architecture

Data architecture can be tricky when it comes to real-time analytics. Clear objectives and scalability are important factors when determining the streaming data architecture you need. Continue Reading
3 cloud-based data management challenges

Your organization has data in the cloud, but there are still concerns as to how you and your data protection vendor manage that data to maintain performance and costs. Continue Reading
6 best practices on data governance for big data environments

Efforts to govern big data must corral a mix of structured and unstructured data. That's a challenge for most organizations. These six action items will help. Continue Reading

Problem Solve Enterprise data warehouse management Issues

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

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
Breaking down data silos with strong data governance

Not having a single source of truth can be a huge issue for data professionals. But strong data governance policies can prevent data silos and lead to better-quality data. Continue Reading
Proactive practices for data quality improvement

Instead of waiting for data quality to become an issue, consider a proactive approach. Here are ways to improve data quality in your organization before it's a problem. Continue Reading