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THE INS AND OUTS OF TCO FOR DATA ANALYTICS

By 23 November 2021 No Comments

Gartner defines TCO (Total Cost of Ownership) as « the total acquisition, usage, management and asset withdrawal cost over its entire life cycle ». 78% of financial executives focus on growth levers with a fast ROI.

Among these levers is the use of Big Data since it allows to best profit from the company’s data heritage. Entreprises’ use cases are improved from Big Data usage.

The TCO of these use cases needs in turn to be optimized to guarantee the best possible results.

What are the key elements to take into account in order to ensure digital transformation and optimization of analytic use cases tied to Big Data for a company to succeed in its TCO calculation? What are the best practices to optimize its results?

Going into the Cloud world

How to store data is an essential question for companies. Generally, the choice is between an environment deployed on-premise and one deployed in the Cloud. With Big Data, the Cloud is seen more and more as the future solution. Why? Because the Cloud is a more scalable, faster, cheaper option that allows the use of NoOps.

Becoming aware of the true value of BI

In the world of analytics, Business Intelligence tools are essentials. They allow users to have access to data and to visualize it easily, in order to have a clear vision of the company’s current performances. Going forward, it is impossible to improve without understanding the present situation.

Knowing how to calculate and optimize your TCO means ensuring your future

Ensuring the best possible TCO is critical to a company’s sustainability. The TCO of analytics is even more so, as it reflects the ability of companies to exploit their data assets correctly, quickly and efficiently.

 

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