Big Data

Big data refers to extensive, diverse sets of information that are too voluminous to analyze with standard data processing software. Businesses can utilize big data to their advantage to identify trends. For instance, imagine an app with 1 million users. The company could employ big data to monitor multiple variables, such as the frequency with which each user logs into the app, the section of the app where users spend the most time, or the typical sequence of pages users navigate through on the app.

All of this data rapidly accumulates. Companies, therefore, need to implement effective strategies to manage big data, which often includes data mining. Data mining is the process of analyzing large amounts of information to discover new data, such as hidden trends, which then inform the company’s decision-making process. You are essentially mining and sifting through the data to discover new insights.

Study Tip: Data mining is the process of analyzing large amounts of information to discover new data.

We have the five Vs of big data:

1. Volume – How Much Data?

2. Velocity – How Fast is the Data Being Generated?

3. Variety – What is the Structure?

4. Veracity – > Is the Data Reliable?

5. Value – How Much Insight Can the Data Bring?

These help us to better understand and break down big data. First, we have Volume, which is the quantity of data we’re handling. Then there’s Velocity, representing how rapidly the data is generated. Variety refers to the structure of the data: Is it unstructured, meaning raw data that can’t yet be analyzed, or is it structured and already formatted for analysis?

The term Veracity refers to how reliable and dependable the data is. Lastly, Value asks how much insight or worth the data can provide us.