Make Big Data Your New Best Friend

An introductory guide to understanding big data.

Contrary to popular opinion, big data isn’t about having a lot of data. It is about a lot of data being generated at a very fast rate and in a lot of different formats. Big data is gathered from a variety of sources in both structured or unstructured form.

Big data is ‘big’ because there’s a lot of it already and it is only increasing at a rapid rate.

 

So, what exactly is big data?

Big data is a young field, and our understanding of what big data is keeps evolving. To try and comprehend what Big Data is, we’ve divided it into the ‘Three Vs of Big Data’:

  • Volume: The size of the data and the number of data items
  • Velocity: How fast the data is being created and the pace at which it moves across networks
  • Variety: Variation between various data types including factors such as format, structure, and source

Recently, two more Vs were added to the definition to help businesses better understand the data available:

  • Veracity: The trustworthiness of the data in terms of quality and accuracy
  • Value: The benefit of the data to the organization and questions being asked. Simply put, how much of this data be turned into business value

Understanding the Vs of big data is essential. But, the people, the process, and the technology used to translate the data into meaningful information is the reason your project will succeed or fail.

 

The Biodata of Big Data 

Early Years:

The early days of data processing consisted of manually and selectively collecting data from a few reputable sources. Once the data had been collected, it would be fed into a computer where it became structured data.

Structured data is data in a known format by data size and type. For example, alphanumeric data for customer names, identification numbers, and sales numbers. It is data that is organized and meaningful.

 

New Data a.k.a Unstructured Data

Let’s fast forward a few years to when the world witnessed significant improvements to technology. Technologies such as Relational Database Management Systems (RDMS) to store and manage data evolved and excelled at managing structured data. Business Intelligence (BI) was developed to gain value from the data collected.

The use of new technologies helped discover a new data type: unstructured data.

Unstructured data is different compared to structured data in that its structure is unpredictable. This data type comes in many various types, sizes, and formats.

Examples of unstructured data are audio and video files, pictures, and images, unstructured text (mobile texts and social media posts).

 

Data Categorization 

To better understand the data you have at hand, it is important to categorize the data by different categories:

  • Traditional data: Data that is found in corporate databases and local data stores such as Excel spreadsheets. It tends to be structured data and is managed with traditional technologies.
  • Enrichment data: Data that is used to enhance, refine or otherwise improve traditional data.
  • Emerging data: Data which is unstructured, non-traditional format, new and comes from an external source. Examples would be: social media, log data, emails, and documents.

 Data is continuously evolving, and eventually, there will be more categories to categorize data by and newer technologies to manage the data.

 

How Big Data is Used in Business:

A common denominator between every business is that all businesses want to gain revenue, enhance operational effectiveness, reduce costs, reach new and existing customers with better products and services faster than the competition.

Big data holds critical and valuable information about the various business markets and customers. And, making sense of the data collected will provide vast opportunities for companies.

There are numerous ways businesses can use big data, and the user tends to be industry-specific, but here are some typical cases:

  • Business revenue generation
  • Risk reduction
  • Increasing operational efficiency
  • Reaching out to new customers
  • Increasing customer loyalty
  • Improving predictive maintenance in manufacturing environments
  • Service improvements in utilities and telecommunications
  • Identifying and reducing fraud in the insurance and financial sectors

Big data can be overwhelming to beginners or those who are not equipped with the right technologies. But for those who are prepared for big data, many new opportunities await.

 

To know more about how you can turn big data into your biggest advantage, download our e-book.

 

Data Ebook Guide

October 4, 2018
Marketing