Data quality management software news, help and research

Data quality management software News

June 10, 2021 10 Jun'21
Quest updates Erwin Data Modeling and Data Intelligence

Quest is looking to build out what it calls a data empowerment platform with the help of data modeling and other technology from its recently acquired Erwin business unit.
June 10, 2021 10 Jun'21
Prefect raises $32M for dataflow automation technology

Data startup Prefect is looking to grow its open source project and commercial business to help organizations manage automated data pipeline requirements.
June 03, 2021 03 Jun'21
Cribl aims to ease data observability with LogStream update

LogStream 3.0 brings new configuration capabilities to Cribl's pipeline technology that can help organizations optimize log and metrics data.
May 21, 2021 21 May'21
Superconductive raises $21M for open source data quality

The open source Great Expectations project is becoming increasingly popular, as the commercial vendor seeks to build out a cloud service to expand the project's reach.

Bring yourself up to speed with our introductory content

What is data governance and why does it matter?

Data governance (DG) is the process of managing the availability, usability, integrity and security of the data in enterprise systems, based on internal data standards and policies that also control data usage. Continue Reading
data stewardship

Data stewardship is the management and oversight of an organization's data assets to help provide business users with high-quality data that is easily accessible in a consistent manner. Continue Reading
How data lineage tools boost data governance policies

Organizations can bolster data governance efforts by tracking the lineage of data in their systems. Get advice on how to do so and key features in data lineage tools. Continue Reading

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

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
Why consider an open source data catalog

Enterprise data catalogs offer organizations plenty of benefits with metadata management and data organization. Find out why some enterprises choose open source data catalogs. Continue Reading
3 growing applications of AI in data management

There are plenty of ways AI can augment data professionals throughout the data pipeline, from sifting through large data sets for duplicates to easing the preparation process. Continue Reading

Learn to apply best practices and optimize your operations.

Big data security management embraces governance, privacy

Cyberattacks, GDPR and CCPA compliance, and COVID-19 present serious security and privacy challenges for managers tasked with protecting their data stores. Continue Reading
GDPR, CCPA, cloud drive security management tool makeovers

As data protection and privacy laws like GDPR and CCPA take hold, data managers refine governance practices, while vendors enhance traditional big data security tools. 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

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

5 steps to an improved data quality assurance plan

Consultant David Loshin offers tips on developing a data quality strategy that can help identify data errors before they cause big business problems. Continue Reading
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
Using data profiling techniques -- and estimating the effort required

Data profiling is a key part of data quality efforts. Here's a simple formula for calculating the amount of time needed to profile a data set. Continue Reading