Data Science for Business: how to make the most out of data science

Many companies base their activities on data collection, made possible by modern technology, which allows for the creation and storage of an ever-increasing amount of information. To get an idea of ​​the amount of available data just think of the number of photos uploaded online on social networks, including Facebook and Instagram, or all the emails and files received daily by each of us.

This huge amount of data can offer advantages in terms of innovation and advantages over competitor companies all over the world, but only if we are able to interpret it and extract meaningful insights. This is where data science and business analytics come in.

 

 Data Science and Business Analytics 

Data science is the domain that deals with statistics, algorithms and knowledge in the field of computer science. Those involved in data science are the so-called data scientists, who combine a wide range of skills to analyse data collected from the web, smartphones, customers, sensors and other sources to find the solution to a given problem. Below are some of the key skills required in order to become a data scientist:

  • Statistical analysis – to be familiar with statistical tests and be able to detect patterns and anomalies.
  • Programming – since data scientists use large data sets, to find out the answers to problems, you will have to write programmes generally in programming languages ​​such as Python and R and use databases for saving data.
  • Machine learning – in order to learn about algorithms and statistical models related to the world of artificial intelligence.

In addition to the part relating to data manipulation, it is very important to know how to give the right interpretation to such data based on a specific business context. Business analytics is the bridge between business and data science, which requires a deep understanding of business, but also an understanding of data, statistics and information technology. More specifically, the skills required are:

  • Interpreting data – since it is important, as business analysts, to have the ability to filter non-relevant data and instead highlight the most significant ones.
  • Analytical reasoning – which consists of logical reasoning, critical thinking, communication, research and data analysis.
  • Mathematical and statistical skills – which give the possibility to collect, organise and interpret numerical data for modeling, estimation and forecasting in business analysis.

 

 Data Science vs Business Analytics 

The terms “Business Analytics” and “Data Science” are often misused as synonyms, but in the previous paragraph we explained their differences. However, there is an indisputable commonality: both sectors are experiencing dizzying growth. The market size in 2025 is expected to exceed $100 billion for both fields. This means we can expect increased demand for these two profiles very soon.

As a matter of fact, there are many aspiring professionals who wish to start a career in “Business Analytics” or “Data Science” but think that such jobs are too difficult or maybe do not find a way to obtain the necessary skills. If you are interested in these areas, you should consider the “Business Data Analysis Master” proposed by Talent Garden. Within 120 hours of lessons divided into 6 modules you will learn to read and interpret data, to visualise business insights and communicate them effectively, and finally to use dashboards to manage and analyse large volumes of data in a strategic way for business development.

Besides being growing and innovative sectors, the economic aspect is certainly a plus for these areas because salaries can exceed $100,000 a year in some countries. Hence, if you are fascinated by data science and business analytics, this is a field you must take into serious consideration.

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