What's the difference between data modeling and data analysis? Which is the right approach for your next project? This guide helps answer those questions.

These best practices are designed to help your data preparation initiatives in machine learning.

Here's how to create bulk rules that let you streamline and automate data quality processes in your organization.

Data quality assessments help you avoid introducing errors into your database. Learn how they work and why you need them.

Lenovo’s innovation in the metaverse, a study of how hybrid work affects women and tips for migrating to a new iPhone lead TechRepublic’s news this last week.

Syniti has announced Syniti Match, a rapid, precise and comprehensive solution for data matching. Learn more here.

This article gives a detailed introduction to data quality and the current status it has in healthcare.

Data models are used to represent real-world entities, but they often have limitations. Avoid these common data modeling mistakes to keep data integrity.

Consumer data compliance and privacy are growing in importance. Learn how to automate compliance efforts here.

There are a few different types of predictive modeling. Find out what makes each unique and how you can use them in your data projects.

Ingesting large volumes of disparate data can yield a rich source of information — but it's also a recipe for data chaos. Use these tips to improve data quality as your data lake grows.

Compare the data quality solutions of SAS and Talend to find the best fit for your organization now.

Data mining tools can collect and analyze data in much the same way a human can, but much faster. Learn what data mining is, how it works and how to use it effectively.

Discover the top trends for data integration in 2022, including data accessibility, integration tools and process improvement.

Explore the requirements of the data quality manager role, and examine the skills necessary to succeed as one.