Data hygiene in ETL and reverse ETL
Good data hygiene means data is correct and easily used to draw insight. This definition then begs the question: How do you achieve it?
Good data hygiene means data is correct and easily used to draw insight. This definition then begs the question: How do you achieve it?
Retrieving data from a source, ensuring it suits business requirements, and moving that data into a target data source is critical to any data strategy. Low-code tools can help create robust and flexible ETL processes that automate your data loading.
Building a data-driven pricing platform for speed, scale and automation with BigQuery, Looker and more.
Backcountry, the specialty retailer of premium outdoor gear and apparel, shares key lessons on using a modern data stack to overcome data silos, complexities with legacy systems and improve its customer experience.
Data plays a profound role in finance. In fact, some might argue that finance professionals are some of the most data-driven individuals in an organization. That’s because finance data, and the insights you draw from it, can literally make or break a company. This is especially true in times of economic uncertainty, when businesses are trying to make data-driven decisions about where to invest and cut resource allocation.