Transitioning Big Data Onto the Cloud

Be it IoT, social media, or even UTM tracking, business data has become a fundamental part of an enterprise looking to improve their decision making process. Crucial to this are the data lakes, which are gigantic repositories of unstructured data that are easy for business analysts to dig through to find key learnings and help intone business decisions.

This has led to a critical juncture for enterprises: Is it better to house a data lake on the cloud as opposed to building an on-premise infrastructure?

Any enterprise would be prudent to initially assess the level of risk they are willing to take with their data lake investment. Investing in an on-premise infrastructure means not just an investment in on-site hardware but also in onboarding and maintenance. Teams need to be trained, servers need to be purchased and installed, and an outlay of resources have to be purchased up front before even being used. The cloud, especially in the hands of an expert managed service provider, can alleviate the initial investment costs while providing access to expert help that can help avoid the missteps in initial setup and maintenance. As an added benefit, major cloud providers now offer hundreds of services that maximize the analytical potential of cloud-based data lakes. The AWS marketplace now has nearly 400 business intelligence services available, many of which cater to building data lakes and making lives easier for business analysts in every enterprise. With less risk and far more rewards, leveraging the cloud to build a data lake makes perfect sense for enterprises that are ready to dive into their big data.

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