Inside Analysis

Modernizing the Legacy Data Warehouse With Confidence

Recent developments in data management, big data, data lakes, NoSQL, Hadoop and the cloud, enable businesses to gain more insights faster. This new age of data warehousing has a high emphasis on self-service and global access to data, raising new challenges. How can we optimize workloads originated from self-service applications? How can we maintain data warehouse health as it is leveraged by more diverse analytics? How can we ensure scalability without having to increase IT resources? To enable self service and modernize with confidence, modern tools will be needed to increase visibility into workloads, automate health checks and workload tuning, and introduce self-service troubleshooting to the user community.

You will learn:
-The big challenges of modernizing legacy data warehousing
-How to maintain control with more granular visibility into workloads from any application, job or query – at the application level
-How continuous and deep health checks can analyze symptoms to find root cause – fix the cause not band-aid the symptoms
-How easy to use, self-service guided troubleshooting moves troubleshooting to the user where it is more efficiently managed, without increasing burden to IT resources
-Tips for getting started with data warehouse modernization

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