Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping a toe: Integrating a legacy data warehouse into a data lake leverages the structured systems that have been ...

Data warehouse systems have been at the center of many big data initiatives going as far back as the 1980s. Today companies from leading cloud hyperscalers such as Amazon Web Services (Redshift) and ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A data warehouse is defined as a central repository that allows ...

I work at a startup and our data is very messy at the moment, as you might imagine. We have a few product level transactional databases, but no central database to store it all in a useful way for ...

Data engineering is the process that makes it usable. It involves moving, cleaning, and organizing. This creates the foundation for BI and analytics. The goal is to replace guesswork with facts. That ...

The true measure of an effective data warehouse is how much key business stakeholders trust the data that is stored within. To achieve certain levels of data trustworthiness, data quality strategies ...

How to use Excel’s Data Model to turn related data into meaningful information Your email has been sent Excel's Data Model feature allows you to build relationships between data sets for easier ...

Alexandra Twin has 15+ years of experience as an editor and writer, covering financial news for public and private companies. Natalya Yashina is a CPA, DASM with over 12 years of experience in ...

In today’s business environment, survival depends on competing against data-driven digital natives whose every move is made based on a barrage of insights gained from intelligent analysis of customer ...

Data warehouses have been at the center of data analytics systems as far back as the 1980s. Today cloud-based data warehouse services offered by the likes of AWS, Snowflake and Google Cloud have ...