Big Data Characteristics

Big Data contains a large amount of data that is not being processed by traditional data storage or the processing unit. It is used by many multinational companies to process the data and business of many organizations. The data flow would exceed 150 exabytes per day before replication.

There are five v's of Big Data that explains the characteristics.

5 V's of Big Data

• Volume
• Veracity
• Variety
• Value
• Velocity

Volume

The name Big Data itself is related to an enormous size. Big Data is a vast 'volumes' of data generated from many sources daily, such as business processes, machines, social media platforms, networks, human interactions, and many more.

Facebook can generate approximately a billion messages, 4.5 billion times that the "Like" button is recorded, and more than 350 million new posts are uploaded each day. Big data technologies can handle large amounts of data.

Variety

Big Data can be structured, unstructured, and semi-structured that are being collected from different sources. Data will only be collected from databases and sheets in the past, But these days the data will comes in array forms, that are PDFs, Emails, audios, SM posts, photos, videos, etc.

The data is categorized as below:

1. Structured data: In Structured schema, along with all the required columns. It is in a tabular form. Structured Data is stored in the relational database management system.
2. Semi-structured: In Semi-structured, the schema is not appropriately defined, e.g., JSON, XML, CSV, TSV, and email. OLTP (Online Transaction Processing) systems are built to work with semi-structured data. It is stored in relations, i.e., tables.
3. Unstructured Data: All the unstructured files, log files, audio files, and image files are included in the unstructured data. Some organizations have much data available, but they did not know how to derive the value of data since the data is raw.
4. Quasi-structured Data:The data format contains textual data with inconsistent data formats that are formatted with effort and time with some tools.

Example: Web server logs, i.e., the log file is created and maintained by some server that contains a list of activities.

Veracity

Veracity means how much the data is reliable. It has many ways to filter or translate the data. Veracity is the process of being able to handle and manage data efficiently. Big Data is also essential in business development.

For example, Facebook posts with hashtags.

Value

Value is an essential characteristic of big data. It is not the data that we process or store. It is valuable and reliable data that we store, process, and also analyze.

Velocity

Velocity plays an important role compared to others. Velocity creates the speed by which the data is created in real-time. It contains the linking of incoming data sets speeds, rate of change, and activity bursts. The primary aspect of Big Data is to provide demanding data rapidly.

Big data velocity deals with the speed at the data flows from sources like application logs, business processes, networks, and social media sites, sensors, mobile devices, etc.