Data Analytics is a technology tool that allows the public and private sectors to generate information and knowledge, factors that help achieve success in national and international markets.
Data Growth (Zettabytes)
It is about data, whose growth dynamics are exponential. According to Statista, in the most recent decade, its generation went from 2 to 59 zettabytes and according to Global DataSphere, it is expected that in 2025 it will reach 175 zettabytes.
Its use, based on data analysis, allows the creation of information and knowledge, a dynamic that has been reformulating the rules of the game for the competitiveness of nations and their productive apparatus.
For the latter, represented in companies in all economic activities, this tool is considered the main asset and its use generates revenue as outlined in a study by the Aberdeen Group According to which companies that introduced data integration strategies into their businesses achieved operating profits of 9 percent year over year compared to 4.6 percent of those that did not. This shows that this is the path to success in national and international markets.
How can companies leverage data analytics?
According to Leonardo Suárez, CEO of Clouxter, a leading Colombian technology company in the national cloud computing market, “with the application of data analytics, companies in any sector can strengthen their installed capacity, expand business, improve customer loyalty and increase the work productivity of collaborators, among other benefits.”Leonardo Suárez, CEO of Clouxter
To achieve this, companies can access services such as Data Lakes, a centralized repository that has attributes such as scalability, availability, security, and flexibility.
In addition to the above, its use contributes to the generation of a concept called data democratization that, among other actions, allows all employees of an organization to access information.
How does Data Analytics come about?
Data analytics arises as a response to the need of the actors in a society to take advantage of this accumulation of information. This is possible through the development of a process that includes the capture, storage, processing, analysis, and communication of data.
For this to flow, as he explains, suitable professionals are required within the organizations. This is how the Data Scientist has emerged, whose profile must focus mainly on areas of knowledge such as statistics, mathematics, programming, and communication, among others.
From this training base, this professional must have the ability to handle issues such as big data, generic algorithms, mining and databases, and neural networks, among others.
In the era of knowledge, the public and private sectors have data analysis as the key tool to be more competitive and contribute to the transformation of global society.