Data Science is the science of working with data. This is what will develop the world of programming, marketing, and also customers, only as much as the discovery of the steam generator and the particular network did. Data Science is now developing it, as evidenced by numerous startups in the area of big data and artificial intelligence.
What is Data Science?
It is the science of methods for analyzing data and extracting valuable information and knowledge from them. It overlaps closely with areas such as Machine Learning and Cognitive Science and, of course, Big Data technologies.
During the massive spread of technology, a person has generated a huge amount of data. One that he is not able to process and visualize:
- data about our calls and movements;
- online behavior;
- shopping preferences;
- man-made changes in the landscape;
- climatic processes.
It’s all Big Data. And great benefit can be derived from them when handled correctly.
At all times, computers previously received new opportunities through programming – a person created understandable algorithms for a machine that led to the expected result. This approach is deprecated.
To work effectively with big data, you need another, machine learning. In this case, a person only gives the computer some input, but the results of the operation of such an algorithm are not determined by a person. Man determines the way the machine learns, but the machine learns itself; she comes to one or another answer and analyzes the information. This is similar to how you and I learn. Machine learning isn’t just about artificial intelligence. This area includes genetic and evolutionary algorithms, and simpler problems associated with cluster analysis, for example.
Finally, Cognitive Science. It is an interdisciplinary science that studies the mechanisms of cognition and thinking. The results of such studies primarily form the basis for the development of various approaches to the creation of artificial intelligence.
Why is Data Science important?
Data Science and artificial intelligence technologies allow you:
· to learn more about what a person prefers (collecting and analyzing data);
· to get closer to him, creating more personalized interfaces (for example, selecting offers by what was previously interesting to the user, sending personalized newsletters ), etc.
For the IT industry, the ability to work with data represents such a big quantum leap that new startups cannot be imagined without this technology – it’s like continuing to use horses for transportation during the heyday of cars. But the term IT start-up itself implies innovation.
Automation, the introduction of new personalization capabilities allows you to increase the margin of your business. And if you don’t do it yourself, more technologically advanced competitors will simply squeeze you out of the market.
New and old professions
Any new field of activity gives rise to new professions. The data scientist, and machine learning specialist are the new most eligible people of the future data analytics consultancy. They are not programmers. They are brilliant mathematicians with a lot of cross-disciplinary knowledge and a superpower for analysis, backed by tenacity – because the chances of finding the perfect formula for teaching artificial intelligence the first time are close to zero. Among all the existing algorithms, they should look for the one that is better suited to solving the problems of the project and understand when something goes wrong, what exactly goes wrong.