How Big Data Works in Data Science

To get started with data science, you first need to understand where the information you are going to use comes from. Data science is not possible without any data present, otherwise you would have nothing to analyze in the process. Moreover, with the infrastructure provided by different technologies, which efficiently process a lot of information, many companies are starting to take advantage of sources like the Internet to collect information. This is where Big Data will come in.

The definition of Big Data

Put simply, big data is a set of data that is too complex or too large to be captured and managed or processed in a bearable time using common tools. Using the relational database management system would not work because there is too much information to process, so it would take too long.

Since there wasn’t a lot of software to keep up with this pace and companies always wanted to be able to sift through all of this information to help make decisions, new database platforms were created.

When it comes to big data, there are five unique data characteristics.

The main three include:

Volume: This is the amount of data produced or received by the business in a day. This would be equivalent to terabytes. As a result, the volume of Big Data will be so large that it must be stored on several different servers. It can also present a considerable challenge, as it would take an unreasonable amount of time to analyze the data if it is done manually.

Speed: Big Data should be available as close to real time as possible. The faster the right people can access data, the more benefit they will have in making the right decisions for their business. The information you collected just an hour ago might end up losing its relevance by the time you can do anything with it.

Variety: Data should come from many different formats or sources. You might be able to get big data from GPS data from smartphones, internal devices, forums, social media trends, and even social media comments. The variety that you get your data from will provide you with a better data set.

Data types

There are three main types of data: structured, unstructured, and semi-structured.