Moving to the Cloud for Better Data Analytics and Business Insights  

The benefits of cloud analytics are powerful, and decision-makers are taking note. IDC and Statista forecast significant big data and business analytics growth through 2022, projecting these markets to reach approximately $275 billion around the globe.

There are tremendous benefits in moving data analytics to the cloud, namely, better return on investment. Engineers have designed these platforms to process and analyze massive quantities of data at accelerating speeds. In turn, cloud analytics help businesses extract value from their data for better decision-making, improved operations, and faster growth.

Those benefits disappear, however, if businesses don’t have the necessary expertise to manage the cloud’s complexities.

Mistakes can cost you, particularly if you don’t closely monitor your data consumption usage or plan appropriately. For example, Gartner, Inc. predicts that 60% of infrastructure and operations leaders will encounter public cloud cost overruns through 2024.

See also: Deliver Analytics Like Amazon Delivers Packages

To avoid challenges and maximize ROI, we recommend managers consider these best practices.

Review Your Cloud Analytics Strategy and Plan

First, look at your cloud technology infrastructure. Is it viable over the long term? Database software is evolving, so you’ll want to consider your needs today and in the future. As serverless computing evolves, are your solutions taking advantage of the cost and flexibility of a pay-per-transaction model that eliminates the need for historically expensive instances?

Both data governance and cybersecurity should guide your plan. Review your policies, determine what’s necessary to comply with industry regulations, and ensure you aren’t moving personally identifiable information to the cloud.

Clean Up Your Data

If you’re consolidating data from various sources, consider how your master data management strategy ensures consistency across your data ecosystem. Customers with different names, such as “Acme LLC” in one database and “Acme Foods LLC” in another, can lead to downstream inefficiencies that can be costly to remediate.

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