Data science is the study of data to turn it into a valuable resource for companies. This information is used to create more accurate and effective strategies. Being able to break down the data and classify it is important for a company since it can make better decisions with its customers. It is important to take into account that it is the brands that have to adapt to consumer trends. 

This helps to better focus the marketing plan. Having an expert in data science makes the information can serve as an ally to a business or brand. To become a successful Data Scientist, you need to study hard at university and pass all the exams. You can ask for help from an essay writing service if you have difficulty with a thesis paper.

What is data science for?

Data scientists break down the information they obtain from different sources. Usually, companies get this data from browsing different sources such as social networks or websites like e-commerce or blogs. But the collection of all information does not bring value in itself to companies, so it is important for these types of scientists who study the data, to be able to interpret them and implement the necessary changes in marketing strategies.

It was in 1970 when this branch of computer science was created. But it was not until 2001 that it was introduced as an independent discipline. This was a breakthrough, as there were professionals in the industry learning from organized knowledge.

Data Science uses different tools that convert data into valuable information for companies. Perhaps this term can be confused with Big Data. This is the discipline that deals with solving data storage and management problems.

What does it mean to be Data Scientist?

Belonging to this professional field means having to use tools that can provide information for the company to benefit. Mathematics, data analysis, computer science, and statistics are used.

Thanks to this knowledge in this study of these data, it is possible to convert large amounts of information into solutions so that the company can reduce costs, increase profitability, have better planning in their strategies, and beat the competition.

Basic concepts of Data Science

Within this discipline, several algorithms are involved that make possible the precise study of all this information:

Machine Learning

This program is in charge of guiding the technology to predict the type of information users are looking for. For example, if an error occurs in a purchase, it will quickly show us the web page to find the solution.

Machine Learning is not the same as artificial intelligence, but this algorithm knows how to read information patterns and anticipate behavior patterns. In other words, it helps to know the user’s behavior.

Deep Learning

This algorithm can mimic the functioning of a human brain. It is composed of two levels. The first one is in charge of collecting information and the second one is the one that processes all this data.

The last and third stage is where all this information is found. Companies usually invest large amounts of money in this type of system. Some of the most used applications are facial recognition, voice recognition, and text processing.

Text Mining

This algorithm makes it possible to find information that did not previously exist by retrieving data and extracting information. It also uses the other algorithm, Data Mining to help in this complex objective.

Text Mining can recognize the sentiments implied by posts on social networks. At the enterprise level, it is used to understand trends or popular searches and produces summaries from this data.

Data Mining

This system makes it possible to analyze large amounts of information collected in an automated way. This algorithm uses statistical tools, algorithms associated with neural networks, and artificial intelligence. For example, this can be demonstrated if in e-commerce certain products are sold that only people with hypertension buy, then the algorithm deduces that this action is due to this cause.

Artificial Intelligence

It is said of programs and systems are capable of responding to stimuli as a person would. This algorithm does not need human command to know how to act. Artificial intelligence is a great advance in science since it allows the creation of sophisticated software that can know in-depth the human capabilities and imitate them. This type of intelligence can store new information daily and put it into practice when necessary.

Career opportunities for Data Scientists

This type of work is in increasing demand, so it is a good career for those who want to start in the technology area. Within this discipline there are different specialties:

  • Data Analyst. They are in charge of data analysis, data collection and retrieval. Their job is to process, study, and visualize all the information obtained.
  • Data Scientist. This is the expert in data extraction and information organization. They have extensive knowledge of other disciplines such as mathematics, programming, and statistics.
  • Data Engineer. Provides the information so that the data scientist can understand and manipulate it. Has the ability to know the tools for the development of Big Data applications.
  • Data Architect. In charge of integrating, centralizing, and maintaining data sources. In other words, he/she must organize the origin of the information obtained.
  • Chief Data Officer (CDO). This profile is in charge of maintaining and organizing the rest of the professionals. He/she is in charge of ensuring order in the work with these experts.

We hope that this article was interesting and useful for you. Data Science is a very promising career and if you choose it, you will need to work hard to become successful in this field. Good luck!