What are the trends in data analysis?

According to the Gartner company, in the next five years the way in which data analysis is managed, produced and delivered will change. But what are the most important innovations, and what technological services and data analysis tools will be crucial in the future?

Know the trends in data analysis 

Next, we will review what those trends in data analysis are that your company should know about.

A data-driven business culture

Today's directors and some technology specialists perceive information as a critical asset for their companies. However, there are still businesses that do not measure the value of data as part of their business culture and do not take advantage of the benefits associated with using data analysis tools.

Machine Learning and Big Data Analytics

By 2022, the 40% of Machine Learning and Scoring models will be realized in products that do not incorporate machine learning as part of its main objective. This is because more and more companies will be able to enjoy technological services with information processing through a Big Data ecosystem.

In other words, the ability to generate data in real time and with greater speed for better decision-making is created.

According to in the study "How Info-Savvy Are You", made by the Gartner company, data analysis has led many organizations to seek a way for their goods and services to generate more positive and measurable economic value. This in order to monetize, obtain a license or right and commercialize them in the near future.

Evolution of IT resources 

Most technology architectures evolve according to the IT resources that a company may have. What yesterday were physical servers is now through a serverless culture; that is, the possibility of having a management and infrastructure thanks to cloud computing and the execution of various applications. Some of its benefits are:

  • Simplify processes and the development of architectures based on microservices.
  • Reduce the financial investment of companies in technological infrastructure.
  • Optimize budget because the cost is generated only when the technological services are running.
  • Better processing is achieved through the development of data extraction, transformation and loading flows, among others.

Data analysis tools 

Along with the continued growth that has been maintained in Big Data analytics, it is expected that the use of augmented analytics will grow in 2020 and become one of the main strategies of companies. This means a conversion of large amounts of data as part of a tool that allows the implementation of Machine Learning and Artificial Intelligence systems.

Today, this and other tools are classified according to their processing categories such as analysis, data migration, predictive analytics and machine learning services. Most have emerged as a response to improving the technological infrastructure used by companies and allowing them to obtain greater efficiency in the use of their resources.

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