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LMI – You can’t be a data-driven company without involving the IT team in analytics

By 19 November 2020 No Comments

“You cannot be a” data-driven “company without involving the IT team in the analytics”

“We want to become a data-driven company”. If you work in an IT team, it is very likely that this directive has accompanied you more than once in recent years, reflecting the desire of organizations to put data at the center of their organizational and economic model.

“We want to become a data-driven company”. If you work in an IT team, it is very likely that this directive has accompanied you more than once in recent years, reflecting the desire of organizations to put data at the center of their organizational and economic model. But if the advantages linked to this approach are still proving to be just as rich – data not being considered as the new “black gold” for nothing – the implementation of the operational value chain is still a major challenge for the technical teams , whether they are systems administrators, data administrators (DBA), architects or other operational teams.

With many technological constraints, shrinking budgets, an acceleration of digital transformation and more pressing analytical needs to face the post-Covid period, IT functions are under pressure to allow the businesses to exploit the data. What if analytics did not become a constraint on IT management but a real opportunity? The key is extensive monitoring, greater knowledge of hidden data, access to data science and a final step in finally becoming a data-centric company.

Provide business analytics while managing the many technological constraints

If data analysts are used to collecting, ingesting, manipulating and analyzing data, it is the IT teams who make it possible to implement the right solutions and manage the rules of data in an enterprise. With an increasing volume of data and many technological solutions in such wide and varied fields, it is sometimes difficult for the IT team to navigate. The Covid crisis brings its share of challenges with the acceleration of reporting needs and therefore of rapid and efficient analytical tools.

The technical challenges are numerous: while 81% of companies have more than 2 public cloud providers according to a study by Gartner, the management of cloud solutions and all their associated tools has made the visibility of systems more complex. of information. Increasingly heterogeneous environments not only complicate the mapping of systems, but also the migration of data to the cloud. While most of the BI and reporting tools are installed on the site, data management can become a real headache.

While connecting the on-premises infrastructure to an IaaS can be an obstacle course, it is the integration and orchestration of data that is the most difficult step. The massive influx of data and the increase in the number of applications create new difficulties related to the size of the environment to be managed, not to mention the management of security.

With all these technological challenges, it is not surprising to see the pressure undergone by IT teams to allow businesses to access powerful tools and analyze the data so precious to the organization today.

What if we change the vision and role of the IT team when it comes to data? Data analysts and business teams no longer have a monopoly on data, architects and systems administrators also have their business in the data-driven strategy of their company.

What if the IT team could also benefit from analytics?

Analytics shouldn’t just be a business tool when this approach can benefit all levels of the business. Today’s technical collaborators are equally entitled to reap the benefits of analytics.

IT teams must be able to visualize what is happening in platforms, in data centers or even in clusters, but most of them only have access to analytics from dedicated monitoring tools on specific use case. While current solutions are aimed at spotting and understanding failures, identifying abnormal uses or spotting server saturation, the field of action is still very limited today.

By allowing IT teams to benefit from more general and therefore more complete BI solutions, the entire company is reaping the benefits. Some organizations have already seen the benefits, such as Mappy, where IT teams have been able, after putting analytics into practice by monitoring server performance and analyzing logs, to detect a lot of data that has not been used until now. This “dark data”, which corresponds to 48% on average of the volumes of data stored in companies according to the Vanson Bourne firm, could then be used by business functions to develop their knowledge and uses.

Yellow Pages also implemented the IT team’s log analysis alongside marketing data to monitor metrics in two different ways and verify results. This methodology ensured that Yellow Pages data and calculations were relevant.

The Machine Learning present in business analytical tools can only benefit technical teams, allowing them to extend their scope of intervention, to foresee possible requests and failures and to dedicate a more suitable number of resources. By analyzing traffic, log levels and changing response times, IT management can gain predictability and speed of analysis.

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Source : Le Monde Informatique – Florent Voignier

Language : French

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