In the last two decades, data analytics has evolved exponentially to the point of referring to data as the “New oil” and your analysis as “The refinery of the 21st century”. Although it has existed for many years, its incorporation into the business world is relatively recent.
“Data analytics has been democratized in recent years to allow companies of all kinds and sizes to access these services. Many of our clients, small and medium-sized companies, are dedicating all their efforts to become ‘data driven’ companies ”, aim Raul Escudero, managing partner of Stratesys, a technological hub between Spain and America.
As indicated by their competence center ‘Business Analytics’, led by Escudero, key trends in data analytics there are currently five:
- Big Data: Companies are alive and the same is true of the market. Selecting a few important data is no longer an option; For analytics to be efficient, the less we leave ourselves out, the better. Therefore, having a Big Data capable of managing and analyzing a large amount of internal and external data is key.
- Democratization of data: Now analytics reaches all areas of the company. People Analytics, risk management, supply chain optimization, cash management and, recently, sustainability and corporate responsibility projects are becoming more and more common. Thus, decisions are made under a clear, much more visual analytical trend based on the concept of dashboards, which leaves behind the flat paper reports and hundreds of pages we were used to.
- Data governance models: Managing so many users with diverse needs and large volumes of internal and external data is costly and can cause chaos that is difficult to manage. Data governance is essential to ensure that information flows correctly to the people who need it and that its quality is impeccable to ensure good decisions.
- Cloud, the perfect ally of Big Data: Flexibility, scalability, security, cost savings, and improved processing and communication times have made the cloud the perfect ally for Big Data and modern analytics. It is increasingly strange to find on-premise architectures that are proprietary to the client and the concept of Data Warehouse left behind. Now we see multicloud solutions that allow us to adapt to each need, integrating into them and ensuring that the user perceives the unique data they need.
- Advanced analytics: Machine Learning (ML), Deep Learning, Artificial Intelligence. These solutions allow you to predict what will happen and develop customer retention strategies, route optimization models, more effective maintenance plans, predict absenteeism or determine the people who will best fit in a vacant position.
Establish a transformation strategy towards a company data driven Today it is a necessity that not only will allow us to gain some advantages over the competition, but it will also be a strategic value that will favor the growth and health of our company in the long term.