2 years ago

Category: Business, Database, Data

https://www.linkedin.com/in/josh-treichel-a29b943/ The cloud has drastically changed the data analytics space, as organizations have decoupled storage from compute in order to power new analytics, ranging from traditional business intelligence (BI) to machine learning (ML). Gartner projects that https://solutionsreview.com/data-management/key-takeaways-2020-gartner-magic-quadrant-for-cloud-database-management-systems/ will be deployed or migrated to a cloud platform by 2022. As organizations migrate their data from existing on-premises data analytics platforms (Teradata, Cloudera, etc)., they are increasingly moving to cloud-based data warehouses (Snowflake, Databricks, BigQuery, Redshift, Synapse).

The data storage problem began with your traditional on-premises data warehouse designed to store and process structured business data, but too expensive to do it in large volumes.

https://cdn.thenewstack.io/media/2021/11/91968df1-image2.png To take advantage of these benefits, organizations are increasingly migrating from their traditional on-premises data stores to cloud data warehouses.