Understanding The Three Types Of Big Data In Data Science


Big data is a collection of structured, semi-structured, and unstructured data collected by organizations and used in machine learning projects, predictive modeling, and other advanced analytics applications. This articles explains the three major types of big data along with examples.

There are three types of big data:

Structured Data

Unstructured Data

Semi-Structured Data

Data Structured:

Structured data is the most user-friendly. It is well-organized, with dimensions based on preset parameters.

Consider spreadsheets; each piece of information is organized into rows and columns. Specific elements defined by specific variables are easily found.

It's all quantitative data from you:

Age Billing Contact Address Expenses Credit/debit card information

Because structured data is already tangible numbers, a program can sort through and collect data much more easily.

Structured data adheres to schemas, which are essentially road maps to specific data points. These schemas describe where each datum is located and what it means.

Unstructured Data:

Not all data is as neatly packed and sorted with usage instructions as structured data. However, the general consensus is that no more than 20% of all data is structured. So, what are the other four-fifths of all available data? Because it isn't structured, we call it unstructured data. Unstructured data is all of your unorganized data: you might be able to figure out why it makes up so much of today's data library. Almost all computer activities generate unstructured data.

While structured data saves time in an analytical process, it takes time and effort to make unstructured data more readable.

Semi-Structured Data

Semi-structured data exists between structured and unstructured data. This usually translates to unstructured data with metadata attached. This can be inherent data collected, such as time, location, device ID stamp, email address, or a semantic tag added later to the data.

Assume you take a picture of your cat with your phone. It records the time the photo was taken, the GPS data at the time of capture, and your device ID. If you use a web service for storage, such as iCloud, your account information is attached to the file.

Final Words:

Big data paves the way for virtually any type of insight an enterprise could seek, be it prescriptive, descriptive, diagnostic, or predictive analytics. Big data analytics stands on the shoulders of giants: the potential of data harvesting and analysis has been known for decades, if not centuries. Do you want to work as a data scientist or a big data analyst? Learnbay provides the best data science course in Pune.