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How to control the operational data value chain?

By 20 November 2020 No Comments

Between 2018 and 2019, the volume of data managed by companies grew by 39% according to the Global Source Data Protection Index. Indeed, this mass is becoming more and more consequent and always more diversified.

For good reason, data is the core of the business. But mastering the operational value chain of this data remains a frequent challenge for all IT teams.

Systems administrators, DBAs, architects and other operational teams must ensure a resilient and efficient data structure of the digital enterprise.

To guarantee this architecture, this requires responding to several challenges: managing the migration of data to the cloud, integrating data and systems at the scale of the company or even developing a certain governance model that guarantees security. of the SI. Responding to these challenges will ensure the resilience capacity of IT teams but also of the entire company.

As a result, the impact between anticipation and reaction can be considerably reduced. This will prevent deadly losses. Every year, $ 26 billion in losses go up in smoke as a result of a system failure. (1)

In such complex data environments, analytics may be the answer to the equation. It will be necessary to integrate it into IT processes by combining it with the use of Machine Learning for example, capable of artificially extending the field of intervention of specialists. Automation will allow more agile use of the technological tools put in place.

IT teams: How to Accelerate Data Architecture?

 

Download the white paper “Ending the operational constraints of digital” here

  • What are the challenges of digitization projects in complex IS environments?
  • What are the use cases and expected benefits of implementing analytics in IT processes?
  • What technologies to use and best practices to retain?

(1) Forbes

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