Artificial intelligence has led to an exponential growth in the data collected by companies. A situation that poses a real challenge for companies, as the amount of information often exceeds their analytical capacity. With this in mind, the best solution for businesses is to resort to data analysis platforms that make it easy to study the information collected and extract the relevant data for each business.

Out of to shapea Spanish platform specialized in data science, explain that “over the last decade, the rise of big data and the need for high scalability have led to the emergence of many data science projects and companies that help companies to quickly extract information from qualitative to obtain quality information, facilitate decision-making and improve business value”.

Many of these platforms, such as shapelets, are designed to process, analyze and easily compare data in real time, favoring knowledge of the company and the environment in which it is located at all times. However, not all analytics platforms on the market meet these requirements and therefore the company has compiled the seven elements companies need to consider when choosing a data analytics platform.

Different analysis methods of files

It is essential that the platform we choose uses various analysis systems such as machine learning, time series analysis, DSL or SQL. This makes it possible to correlate the new information obtained with the data already stored, improving and expanding the analytical capacity.


The platform should include charts, visualizations, and business activity analytics for better data analytics capabilities. For example, it would have to be able to update data, offer interactions, natively integrate visualizations or manage authentications.

Advanced big data analysis

Given the massive amount of data companies store, it’s best to choose a platform capable of performing advanced analytics, including, for example, reporting and scorecarding.


Another important element when choosing a data analytics platform is that it gives us the ability to scale based on business needs. The tool must be able to grow with the amount and variety of data the company collects.


Speed ​​is key as data can be constantly being collected. Speed ​​is now an important element not only in the collection and analysis, but also in the implementation. This means that we must be able to quickly implement the analysis tool we have chosen in the company.


The information we collect is confidential, so the platform must be secure and have systems that can handle any vulnerability. For this reason, it is necessary to check what the system of access to the tool is, what security systems it uses and whether these are compatible with the way the company works.


Finally, the platform should have a support team that can deal with any issue that arises in the tool, as failure of the platform can cause losses to the company.

Data analysis, big data, data, data management, artificial intelligence