The warehouse served as a single (on-premises) storage location for data from disparate sources, where BI teams could find cleaned and organized data. The data warehouse first appeared in the 1980s when relational databases using SQL replaced outmoded methods of storage, making databases more valuable. In this guide, we explore how data warehouses and BI have evolved in the cloud, the benefits of using modern cloud BI and analytics, and additional resources for continuing the journey toward gaining actionable insights from your data more quickly. Companies that aren’t taking advantage of what’s possible are falling behind those that are. Now, with powerful managed cloud storage solutions like Google BigQuery, Amazon Redshift, and Snowflake, data doesn’t even need to be fully summarized to work with it effectively. And modern analytics tools have turbocharged organizations’ ability to quickly make use of their data. The cloud brought these sky-castles down to earth, completely transforming what’s possible with the data warehouse. People might have wished for faster access to insights based on their data, but a more efficient data warehouse looked like a castle in the sky, and everyone faced the same challenges. Everyone was dealing with limited on-premises servers and had to rely on IT to run reports in slow-moving batches overnight and on weekends. In the past, a plodding approach to data processing and analysis worked just fine.
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