Proper data warehousing is the key to unlocking advanced insights in large amounts of data. With so many tools and platforms available, finding the right one to fit your unique needs and problems can be a challenge.
In this edition of Tech We Like, we’re looking at some of our favorite tools for getting the most out of data warehousing.
Azure Synapse Analytics
Microsoft’s Azure Synapse Analytics brings together enterprise data warehousing and large-scale analytics.
Whether you want to use Python, Spark, or SQL, you can interact with your data via a single UI and scale everything in concert as needed. Analytics results can be delivered extremely fast, and security measures include such features as column- and row-level security and dynamic data masking.
Databricks
Databricks is all about flexibility. Whether you’re running streaming, machine learning, or data integration workloads, you have a single platform to run robust analytics without the cost and expense of managing a Spark cluster.
With Databricks, your data scientists can quickly fire up a cluster, work on it, and destroy it with ease.
Profisee
Profisee’s Master Data Management platform leans heavily into speed, scalability, and affordability. Highlights of the platform include advanced verification to fill incomplete or missing data, identification of incorrect data, and easy unification of your data in a single master view.
Cloudera
Cloudera’s hybrid and multi-cloud data warehouse services provides you with multi-function analytics on a unified platform. Security and governance remains consistent throughout, and the platform supports public, multi-cloud, and on-premises deployments.
Download our free whitepaper Navigating the Flood: Building Value by Reducing Data Complexity and Properly Managing Your Data.
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Navigating the Flood: Building Value by Reducing Data Complexity and Properly Managing Your Data
