Data warehouse software news, help and research

Data warehouse software News

February 16, 2021 16 Feb'21
Matillion raises $100M for ETL to enable data middleware

The co-founder and CEO of Matillion, talks about his company’'s latest round of Series D funding and how data will be the key to success for many organizations in 2021.
February 01, 2021 01 Feb'21
Databricks fueling data lakehouse goals with $1B funding round

Databricks gets a major vote of confidence from big name investors, including Franklin Templeton, as it raises new funding to help it advance its cloud data management technology efforts.
December 09, 2020 09 Dec'20
Snowflake's Slootman predicts future of cloud analytics

Cloud data platforms that effectively eliminate data silos and reduce the need for multiple tools will emerge over the next few years, according to Snowflake's CEO.
November 20, 2020 20 Nov'20
Yellowbrick data warehouse update boosts workload management

Hybrid cloud data warehouse vendor updates platform with self-healing cluster capabilities and a "penalty box" feature to improve workload management.

Bring yourself up to speed with our introductory content

big data analytics

Big data analytics is the often complex process of examining big data to uncover information -- such as hidden patterns, correlations, market trends and customer preferences -- that can help organizations make informed business decisions. 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
What is data management and why is it important?

Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization, as explained in this in-depth look at the process. Continue Reading

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

Data warehouse vs. data lake: Key differences

Data warehouses and data lakes are both data repositories common in the enterprise, but what are the main differences between the two and which is best for your data? Continue Reading
Evaluating data warehouse platform options and your need for one

There's still a place for data warehouses in data architectures. But first, ask whether your organization needs one and what type of technology platform is the best fit. Continue Reading
Data warehouse technologies evolve as vendors look skyward

The need for high-speed analytics and low latency are pushing data warehousing vendors to create and reinvent their platforms and, in some cases, reinvent themselves. Continue Reading

Learn to apply best practices and optimize your operations.

Should you host your data lake in the cloud?

On premises or in the cloud: What's the better place for your data lake? Here are some things to consider before deciding where to deploy a big data environment. Continue Reading
How data staging helped Walgreens transform its supply chain

Walgreens built a centralized data warehouse to give supply chain partners a better view into its data -- but analytics were slow. That's where a data staging tier came in. Continue Reading
How graph data modeling can help evaluate database tools

Mapping data to a graph model can be challenging, but these steps can help you create prototype applications -- which then can aid in evaluating graph databases. Continue Reading

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

Why data silos matter: Settling ownership of data issues

Data management is often still seen as an IT task, but that can lead to data silos. Find out why the business should be in charge of its data as part of a governance process. Continue Reading
Dimension tables vs. fact tables: What's the difference?

Fact tables and dimension tables are used together in star schemas to support data analytics applications. But they play different roles and hold different types of data. Continue Reading
Operational data store vs. data warehouse: How do they differ?

Operational data stores and data warehouses both store operational data, but the similarities between them end there -- and they both have a role to play in analytics architectures. Continue Reading