Today, companies gather a huge amount of information or data. This large amount of information is known as big data. To get the most out of all this information about customers, products and company performance, a data analyst studies the data to identify what metrics each stakeholder needs to follow and how to act on it. For example, the data analyst can say which products of the company will help customers the most according to their profile, the supply chain strategy that will have the best results, or what to change in customer relationship management to achieve a higher retention rate. This is why people like Data Analytics jobs very much. The most searched and is the data scientist or data analyst. The New York Times has described this profession as “the sexiest of the 21st century. “
1. McKinsey has said that in the United States alone there will be almost 200,000 vacancies that will remain unfilled during 2018. Finding the right people is key at the moment, as companies today can access, in some cases for little money, many technologies to analyse what is happening, but many times they lack the professionals who interpret this flood of information. According to MIT, less than 0.5% of all data generated in companies is analyzed today.
2. Diego Rojo, a postgraduate professor of data science at the U-tad university center, says that a data scientist’s mission is to “generate value from large volumes of data”, and for this he must know “extract, understand, clean and apply analytical and machine learning techniques ”in order to support decision making in your organization.
3. In a bank, for example, a data analyst could identify future delinquent clients by analysing many variables or locate others who could, by their history, hire a pension fund. In the public sector, for example, a good data analyst could tell us, after analysing a good amount of variables, which students are most at risk of dropping out of studies and taking preventive measures. In this way, the problem of school failure, a tricky issue, could be softened.
4. In the movie The Big Short, which analysed the origins of the mortgage crisis in the United States, one of the characters was a peculiar data analyst played by Christian Bale that long before the system collapse realized that the disaster was coming. And it did so by analysing long lists of mortgage data in the pre-crisis phases. And, of course, he became a billionaire with his commitment to the fall of the brick market when no one, not even the most pessimistic, questioned its foundations.
5. Felipe Ortega, from the Rey Juan Carlos University, replied to people like Data Analytics, the EIM Consulting provider and data scientist must be a person “curious, creative, innovative, even challenging, able to face the prevailing status quo.
6. A study by the consulting firm Good Rebels also affects the idea that the data analyst will be one of the most promising professions of the next decade. All participants in
the study, including experts from Google or BBVA, ensure that the demand of these professionals will be “exponential”. Companies that do not take advantage of their data, the oil of the 21st century, run the risk of losing positions or even disappearing.
7. The Good Rebels report says that for an average Fortune 1000 company, where the first thousand US companies by volume of revenue, a 10% improvement in data accessibility will result in additional sales of $ 60 million per year. year. For his part, Emilio Soria, of the MBIT School, ensures that the returns on investment are less than one year in the projects in which data analysts are involved.
These are the reasons why people like Data Analytics as their job role and consider it the safest job for the future.
What is required to be a data scientist?
A good data analyst, in theory, must summarize knowledge of mathematics, statistics, and programming, and also know in detail the sector of activity of the company for which he works, in addition to being a good communicator to convince the board of directors of the value of their research. And what will that do for you? Well, to find patterns that go unnoticed and can help improve sales or change business processes for the better.
The Data Scientist’s Skills
– Statistics and mathematics. Must be able to analyze databases, build models, make statistical forecasts and distinguish the representative from what is not.
– Technology. Must be able to design algorithms and handle multiple computer languages and databases.
– Business analytics. You should know the sector and the activity of the company for which you work. Only then will you be able to know what problems are feasible to be solved by metadata management solutions.
– Communication. Transmitting the results of your work to company executives will require a conviction. Also, you will have to be able to disclose your results to managers without technical training.
– Other capabilities. It also assumes qualities such as creativity, intuition, flexibility, curiosity, empathy, and pragmatism.
