Definition of the Data Analyst

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Sep 30, 2021
introduction data analyst course

Still qualified as a data analyst or Big Data analyst, the Data Analyst is the last actor in the data processing process. Where the Data Architect comes first, the Data Engineer second and the Data Scientist third, the Data Analyst closes the data valuation chain by effectively communicating the results obtained from this chain to the business departments.


Depending on the size of the company, its sector of activity or the scope of the project, the work of the Data Analyst can in certain cases intervene directly after that of the Data Engineer or just after that of the Data Scientists, when the latter have put into production the expected deliverables of the project (usually data applications or statistical learning models). In other cases, the function of Data Analyst can replace that of Data Scientist. In this case, the Data Analyst acts both as Data Analyst and Data Scientist (although they are different professions, as we will see below).

You are moving towards this profession if you want to help companies on the front-end aspects of their Big Data project or more generally on the exploitation of their data, if you are not on a Big Data scale. The Data Analyst helps companies to actually consume the data formatted by the Data Engineer or the results returned by the Data Scientist models for effective decision making. It is a profession at the intersection of Business Intelligence and Big Data engineering.

The Data Analyst masters reporting and visualization tools (Microstrategy, Business Objects, Microsoft Power BI), the monitoring tool par excellence for decision-makers (Microsoft Excel), VBA, R programming, SQL, and has very good communication skills to exchange with the decision makers of the company on the meaning of the indicators calculated on the basis of the data. Its ultimate goal is the analysis of data for intelligence purposes  . It is a very fascinating profession for people who see themselves more as study managers, analysts than engineers .

It is a profession that is increasingly in demand in Big Data with the deployment of projects in production. Its demand is increasing due to a renewed interest in the market for Data Visualization .

The demand for this profession has been rising steadily since 2014 and is driven by 3 things:

  • The progressive awareness of companies of how data can be used to gain a competitive advantage in their business model
  • The deployment of Big Data projects in production
  • The increasingly growing transition of companies from their traditional Business Intelligence systems to Big Data systems and through the implementation of Data Lab .

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