In these times, information is one of the most precious intangibles. Knowing how to control it is the best way to be at the forefront of the vanguard. With it, organizations can structure their modus operandi and reduce risks. However, we must know how to extract the value of the data, and to do it properly. There are data science and data scientist. We explain what they consist of.
Data Science, a more than Broad Term
Before getting into the subject, we have to offer a definition of what is data science or data science. It is a set of tools that uses scientific methods, processes, algorithms, and systems to extract valuable information from raw data.
For its part, data science is a field that uses mathematics, statistics, and computer disciplines to develop its processes and also incorporates innovative techniques such as machine learning, mass analysis, and data extraction.
What knowledge does a Data scientist have?
Data analytics has been used in companies for a long time. We allow ourselves to quote W.E. Demming, who said that without data, you are nothing more than a person with an opinion. The digitalization of the economy, the rise of machine learning systems as well as the need for superlative user experience, has increased the figure of the data scientist, specialized in collecting, manipulating and making sense of that volume of information coming from multiple sources.
Entering the world of Big Data is not as simple as it seems. These professional profiles must have deep knowledge in various areas. On the one hand, those that include a series of technical skills or specific knowledge (Hard Skills) among which strong knowledge of mathematics and statistics stand out; Extensive computer knowledge, both programming, and machine learning and business knowledge, we must make an analysis and develop systems capable of helping the business, data analytics without business knowledge is an exceptionally dangerous area. Additionally, it is important to have skills related to emotional intelligence, the ability to communicate, or the ease of adapting to changes (Soft Skills).
Hard skills
- Extensive mathematical knowledge, statistical analysis, and commutability.
- Database control (Hive, Impla, SparlSQL, SQL, NoSQl or PL / SQL).
- Skills in different programming languages.
- Advanced management in computer programs such as Hadoop.
- Control of distributed storage systems.
Soft skills
- Interpretation of statistics and market parameters.
- Strong listening skills, public speaking, and the ability to develop visual presentations.
- Ability to acquire, display, and translate information to the company.
Benefits of Data Science for the Company
Despite the emergence of new data analysis techniques, the objective of companies has not changed a bit. For the system to work, every organization seeks to sell its products or services to a user. However, if you know how to take advantage, Data Science training in Bangalore, Big Data Hadoop training in Bangalore, and Artificial Intelligence attract multiple benefits to the company. Some of them:
- It serves as a system for predicting user behavior. In this way, the company can guide its operations based on more specific data that outline the range of success and reduce business risk.
- Avoid economic losses. Data science can also help detect cyber-attacks or possible frauds that can involve the company.
- From the point of view of marketing, data science allows the company to anticipate the needs of the user. In this way, they can send you content according to your personality, tastes, and interests. A clear example is Netflix, which, based on the series or movies that the user sees, proposes similar recommendations that could be included in your favorites list.
If you are looking to become a skilled data scientist, you can get in touch with Inventateq.com. It is a learning institution with dedicated programs for anyone looking to acquire certain computer networking and information technology skills. You can check through Data Science courses in Chennai to develop a clear idea of what you are getting into.