The story of Big Data, Data Science & Data Mining

Big Data, Data Science, and Data Mining are three of the most trending data related terms of today. Here’s a breakdown of what they are, how they are related, and what impacts they have on the future of business.

Data is a very valuable asset in today’s world. Something which was considered useless and merely a byproduct of a company’s daily operations just a couple of years ago now holds immense power over how companies work and decide their next moves. It seems like as time passes, the value of data just continues to increase and its importance in many industries continues to grow.

However, many people fail to realize why data is so important and are confused between the many terms related to it that are thrown around the tech industry nowadays. Big Data, Data Science, and Data Mining are some of these terms. Today we will look to explain what each term means, how they are related to each other, and whether they really hold any importance in today’s world or are they just mere buzzwords?

Big Data

Essentially, big data is just large amounts of data that can be categorized by the three Vs. This data is of a high Volume, comes with high Velocity, and has high Variety. This means that any data that is collected in large volumes, is continually changing, and contains a wide range of information can be described as Big Data.

For a long time, Big Data was considered to be useless. For many companies, it was data that was generated as a by-product of daily operations. On the face, it seemed completely useless. It was not possible for any human to make sense of the data or derive logical conclusions from it, even with the help of data management programs. It was due to the technological advancements in Artificial Intelligence (AI) in recent years that computers were able to take this data and, using machine learning, was able to realize very important patterns and cycles from it. It is important to realize that without AI, Big Data is almost completely useless. But when paired with the right technology, the patterns and conclusions that can be deduced from Big Data are invaluable and vital for any company to successfully predict future trends in the market.

 Data Science

Data science is a multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.

Data Science is actually a very broad term. It is basically an entire field that deals with extracting valuable information from data. So, Big Data is the actual ever growing and ever-evolving structured and unstructured data that is collected by companies. Data Science is a scientific study that encompasses all the techniques that are used to derive logical conclusions from a given set of data. It consists of Data Visualizations, Computational Social Sciences, Statistics, and Natural Language Processing among other areas.

 Data Mining

Data mining is concerned with finding trends from provided data sets. These are trends that cannot be determined in other ways and hence need specific dedicated algorithms and techniques to analyze the data and identify patterns.

As you might have noticed from the data mining definition, it is actually part of the wider field called Data Science. Data Mining operates as a subset of Data Science. Hence, comparing them would be futile, since they exist in completely different levels.