Introduction To Big Data | Importance, Types, Structure and Examples

Big data analytics enable organizations to take advantage of their data and identify new opportunities based on it. The article will give an introduction to big data and how it is benefiting the industry. 

 

What is Big Data?

Big Data refers to the vast quantities of data that are growing exponentially over time. Traditional data management tools are unable to process that huge amount of data. In computer science, big data is just like simple data, but it is much more plentiful. In the field of data science, big data plays an increasingly important role.  

 

Types Of Big Data

Depending on the structure, big data is divided into three parts.

 

  1. Structured
  2. Semi-structured
  3. Unstructured

 

Structured

Structure data is such kind of data that is stored in a specific format. As computer science has developed over time, it has been able to store and process large amounts of data. The development of techniques for working with well-known data formats has been more successful. However, when there is a rapid increase in data, this can cause problems.  

The amount of data is so large that storing and processing it is difficult. 

 

Semi-Structured

It consists of a combination of structured data and unstructured data. 

In particular, it pertains to data that hasn’t been classified under a specific repository (database). It contains vital information or tags which separate the data into individual elements. 

 

Unstructured

A data set that is unknown in form is referred to as unstructured data. Additionally, unstructured data poses multiple challenges in terms of processing for gaining value from it in addition to its size. A heterogeneous data source, such as a text file, an image, a video, etc is an example of unstructured data. 

 

Example of Big Data

You can take any social media platform as an example of big data. The Facebook database ingests a new terabyte of data every second. In general, this data is generated by uploading photos and videos, exchanging messages, and making comments.

 

Characteristics of Big Data

These characteristics of big data can be described as follows:

  • Volume
  • Variety
  • Velocity
  • Variability

 

Volume 

Even big data’s name makes it clear that the size is huge. Data value is highly dependent upon the size of the data. The volume of data may also determine whether it counts as Big data or not. Therefore, big data solutions need to consider ‘Volume’ as one key consideration.

 

Variety

In addition to its size, big data has a variety of uses. The type of data, whether structured or unstructured, varies according to the heterogeneity of sources. Before, people gathered useful data only with spreadsheets and databases. Applications today evaluate emails, photos, videos, monitoring devices, PDFs, audio, and other data forms. Storage, mining, and analysis of unstructured data can be challenging with this type of data.

 

Velocity 

‘Velocity’ refers to the rate at which data is generated. The amount of data that is generated and processed to meet the demands determines the actual potential of the data.

Business processes, application logs, network data, social media sites, sensors, mobile devices, etc are the sources of big data Velocity. 

 

Variability 

Data shows inconsistency at times which hamper managing data effectively. Sophisticated programs can help to understand the context in them and decode the exact meaning.

 

Big Data Applications

Retail traders, big banks, and companies use big data to analyze the trade market.  Here are some features of big data:

 

  • The government utilizes big data for cybersecurity & intelligence.
  • Social media can provide valuable information and predict how the market will react to certain products.
  • Big data analysis helps intelligence in crime prediction and takes efficient steps to prevent it.
  •  Call care centers’ data can help to influence the market, understanding the market sentiment. Big data solutions can provide valuable information of customers’ behavior through capturing and processing call content itself.
  • Big data has a great impact to improve scientific research.
  • Telecommunication operates find it difficult to deliver new revenue-generating services keeping the running costs under control. As a solution, they use big data analysis which helps to make the right decision to the service providers.

 

Benefits of Big Data Processing

A database management system that can handle big data offers several advantages, including:

 

Taking Valuable Decisions

Intelligence from outside can help businesses make informed decisions.

Organizations can fine-tune their business strategies by gaining access to social data from search engines and sites such as Facebook and Twitter.

 

Improving Customers’ Satisfaction Improved

New systems designed with Big Data technologies are replacing traditional customer feedback systems. To read and evaluate these consumer responses, Big Data and natural language processing technologies are used.

 

Identifying Risks

If there is a risk with the product/service, it should be identified early. Here, big data does the work by analyzing the risks and benefits.

 

Enhanced operational efficiency

Using Big Data technologies, a staging area can be created to determine which data should be migrated. As a result of this integration, an organization is able to offload infrequently accessed data to its data warehouse.

That’s all! The introduction of big data is the basics of big data and it will help you to demonstrate the whole process celarly.

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