Moving Your Data Warehouse to the Cloud

In a recent TDWI survey, a surprising number of enterprise respondents (almost 50%!) reported they were planning to replace on-prem data warehouses with cloud data warehouses (CDWs). Our advice, and we cannot stress this enough, is, to learn from experts who have already done it many times.

CDW migrations are much, much easier said than done. In our hard-won experience, successful Data warehouse-to-cloud migrations are a juggling act of managing change within hybrid environments while also supporting the ongoing needs of multiple business units.

How it works:

At the end of the day, CDWs must solve four modern enterprise class challenges:

• Data sources will eventually span across on-prem and multiple cloud environments. Getting the data to one place is only the first step in the journey. From there, it must be governed and curated to ensure data quality and usability.
• Users will include business analytics, data scientists, and DevOps pros, whose access methods, data requirements, and IT IQs are widely divergent.
• Data must be secure and auditable. At the same time, high-performance and self-service is a prerequisite.
• Data quality governance is Job #1.

The bottom line:

Wavicle believes these challenges are best answered by 1) moving the heavy lifting challenges out of the database; and 2) engaging the cost-performance capabilities of Spark. This approach enables enterprise data solutions that are more robust, scalable, and manageable. Spark’s in-memory architecture shifts processing to cores that are designed for these workloads and can be scaled massively to deliver optimal query performance while minimizing spend.

One last thing:

It is crucial that data pipelines are both reliable and manageable, so Wavicle developed pre-built toolkits and frameworks to accelerate delivery of the above Spark-based data pipelines. We work closely with partners such as Talend and Databricks to ensure that your enterprise data solutions are robust and future- proof. Easy!