Data Intelligence Project: How To Approach?

Data Intelligence Project: How To Approach?

Vast amounts of data are generated every minute that puts the internal architecture of all companies and Cloud services to the test. Also, there have been changes in both the generation and consumption of data at a global level in the current context.

Data Intelligence

Vast amounts of data are generated every minute that puts the internal architecture of all companies and Cloud services to the test. Also, there have been changes in both the generation and consumption of data at a global level in the current context.

In 2020, each person produced 1.7 MB of data every second and this figure is estimated to double each year, according to data from Domo’s ‘Data never Sleeps’ report. The reality is that so much information is produced that, used well, it can be the differential value of companies. Therefore, the ability to make decisions based on data is crucial to obtain the maximum potential of Big Data.

Data is the most strategic asset of companies since it contains the strength and great value of companies. A Gartner study affirms that 90% of corporate strategies will consider data their most critical asset in 2022. Both internal data generated by the company itself and external ones, the so-called Open Data provided by public bodies or governments, and our competitor’s data, is precious and requires careful study.

The volume of data we are faced with today is infinite. It is estimated that from the year 2025, around 175 Zettabytes will be generated annually. 1 ZB equals one billion Terabytes, according to IDC data. Faced with this overwhelming scenario, those organizations that take advantage of their data and scale their businesses towards advanced analytics will have a competitive advantage and will ensure the survival of their companies in the long term.

Also Read: Cisco Meraki Cloud-managed Networking Benefits

From Descriptive Analytics To Intelligent Prescriptive Analytics

Today it is necessary to evolve towards smart prescriptive analytics, which guides the steps to follow or adopt strategies. The transformation of companies towards a data-driven model implies a new vision, a new mentality to adapt processes and collaborative models to build and add value to end-users.

Thanks to Artificial Intelligence and Machine Learning models, advanced analytics will allow making predictions, recommendation models, and automation that will help process efficiency. All of this should lead to establishing a Data-Driven Company, an organization focused on turning its data into valuable information, which will allow more strategic decisions to be taken to generate new business models.

When it comes to becoming a data-driven company, some roadblocks can come your way:

  • Lack of knowledge and talent for data analysis
  • Data can be sealed or unreliable.
  • Legacy systems may be incompatible with centralizing information. 

From Planning To Progress

To grant the power of transformation to data, it must be critical for the business. The information must be accessible, interpretable and actionable so that the technology used can drive Data projects. For this, four fundamental pillars are recommended:

  • Match data to business priorities
  • Create a data-driven culture
  • Make the most of the information.
  • Implement the technology and infrastructure necessary to undertake this series of initiatives.

Success depends on matching technological innovation with each company’s strategic priorities and specific needs to establish its objectives. Data-driven organizations are not those that have a large amount of data and cutting-edge analytical capabilities but have evolved to take advantage of their data, monitor it, generate insights and make a significant difference among their customers.

Data Ops From Laboratory To Production In An Agile Way

Most companies are still not able to define the appropriate strategy in managing their data since the lack of a centralized data export system can be immobilized to some extent. Therefore, a realistic plan and the establishment of specific technologies will facilitate the search for new opportunities based on data to face this transformation of Data Intelligence projects. 

It is essential to centralize the information in a single system to evolve towards analytical maturity developing far-reaching projects. Thanks to the cloud, we will have computing capabilities to analyze all the information, monitor data in real-time, alert notifications or collaborative analytical systems. An innovative vision of data processing will set the pace for the new era of Big Data and Business Intelligence, a vast ecosystem to explore full of opportunities for organizations.

Also Read: Most Of The SMEs Rely On Artificial Intelligence To Gain Visibility


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