Data is everywhere. The modernized technology boosted with the use of the internet can go further than people usually imagine.

A large volume of data, either structured or unstructured that floods a business daily, is termed as big data. When you are concerned about how to transform data into actual revenue, it is not the amount of data that is important. What is crucial is how organizations do with the data that matters. Big data can be used in the analysis of insights that result in better decisions and strategic business tactics.

Why is Big Data Important?
The importance of big data does not rely on how much data you have, but what you do worth it. Data sourcing and analysis should be used to enable cost reduction, time reduction, new product opportunities and optimized offerings, and better decision making. When you incorporate big data with advanced analytics, it can provide ease in accomplishing business-related tasks such as:
  
·       Defining root causes of failures, problems, issues, and deficiencies in a near-real-time manner.
·       Generating coupons at the point of sale based on the consumer's buying habits and decisions.
·       Recalculating risk portfolios wholly in minutes then provide lists of data with low or high risks.
·       Detecting frauds and inconsistencies before it can affect the organization.

How does it work?

Before understanding how data can work for your business, you should know first where it comes from. There are three categories of data sources:

Streaming data 
These are the data that reach your IT systems from a web of linked gadgets, often part of the IoT (internet of things). Upon the arrival of data, you can conclude which ones to keep, not to keep, and to further analyze.

Social media data

Data on social media interactions are continuously attracting set information, mostly for sales, marketing, and support functions. Usually, the data are unstructured or semi-structured in form, so it seeks further consumption, and analysis making it more challenging.

Publicly available sources 
A large amount of data can be generated via open data sources like the US government's data.gov, the CIA World Factbook or the European Union Open Data Portal. When all potential data sources are identified, consider the decisions you will need to make once you begin connecting information.

How to keep and manage data?
It is truly challenging when you travel and need to pack all of your stuff in single luggage. This is the same with big data, keeping them is quite a problem several years ago, there are now low-cost options to choose from for storing data if that is the best approach for your organization.

How much of it to analyze? 
Some organizations can do substantive analysis while some companies can include the entirety of data. Analysis of the whole set of data is now made possible with high-performance technologies such as grid computing or in-memory analytics. Another method is to identify and weigh the most relevant data at the moment before further analysis.

What is Data Monetization?

Data monetization is the process of converting the large unstructured or semi-structured volume of enterprise data into valuable insights to generate economic value to the business industry. It is also the use of data assets or data resources to gain value for the organization.

Monetization can be carried directly or indirectly. Direct monetization happens when a large amount of data generated can be packaged into data products and sold if it processed to extract insights it will be indirect monetization. Both can be used to support business decision making.

The data monetization market has been expanding due to the rising volume of data across multiple industries. Monetization of data drives the realization of significant financial value in any business industry.

ALSO READ: How US Universities Use Big Data to Drive Student Enrollment