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Why Should Companies Consider Hyperscale Approach To Data Analytics?

Key Highlights

  • The amount of data generated by the growing digitized world continues to increase at an unprecedented rate.
  • According to Matt Aslett, VP and research director at Ventana Research, By 2024, six in 10 organizations will re-examine their current operational database suppliers to support more agile and intelligent operational applications and improve fault tolerance.

With an increasing number of sensors and smart devices generating data, several organizations must not only scale the amount of data they ingest and analyze but also adapt to harness more complex data sets generated from a rapidly growing number of sources.

This explosion in machine-generated data creates opportunities to unlock more insights. It creates structural, operational, and organizational challenges simultaneously as companies must quickly adapt and innovate to unlock smarter business decisions and stay ahead.

Because of this, it is the right time for enterprises to consider moving beyond big data and adopting strategies and tools to harness data and leverage operational intelligence at a hyperscale.

How Is Hyperscale Data Analytics Changing the Game?

Currently, terabytes to petabytes of data are common in a hyperscale data center, but that data usually remains challenging to analyze in a meaningful way. Google reported that its data centers were handling about 1 million requests per second (RPS) in 2022 and processing more than 20 petabytes of data per day, just from search queries.

In such times, knowing where to start analyzing all of that valuable information can be challenging, and how to do it quickly. When it comes to hyperscale data analytics, only some organizations have the resources of a tech giant such as Google to scale and manage robust computational solutions to work with their data continuously.

Hence, architecting high-performance solutions at effective costs takes a lot of work, especially when the data sets start to reach the petabyte scale. Still, most organizations recognize practical data analysis is essential to their business.

Organizations should consider adopting new strategies and tools to harness the massive data created by an increasingly digital world.

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