Big Data and Analytics for Better Data Driven Decision Making

Big Data and Analytics are the two most used buzzwords of 21st century. Data Analytics helps to understand things in detail and how something works. Use of analytics help to increase productivity, make better data driven decisions, and gain an advantage on competitors and market activities.

What is Big Data?

Big Data is the most overused and misused buzzword in the digital age. Big Data has various definitions according to the context it represent. For example, in business Big Data means Data Analytics but in technological terms it is a data set that is too big to be processed.

Big Data is a term used to represent extremely large data sets with unstructured, semi-structured and structured data that has the potential to mined for information, trends and patterns, especial relating to human behavior and interactions. 

Why is it Valuable?

Big Data is the next frontier for innovation, competition and productivity. Success depends on measurement and understanding of something and it helps to improve the business and return on investment. 

Data is easily available from various touch points like Social(Facebook,twitter, Instagram..), email campaigns, websites, ticketing, merchandising, mobile app usage, etc; proper measurement and analysis helps to optimize the business performance by generating better financial results. It could be either for Saving the money by optimizing the existing process or making more money by understanding the new opportunities.

Analytics and Big Data

We will start with understanding the difference between Analytics and Big Data.

Form Wikipedia, "Analytics is the discovery, interpretation and communication of meaningful patterns in data". Analytics is built on the foundations of Statistics, Probability, Computer programs and operational research.

Analytics is the method used to find the meaningful information, trend and patterns from the large data sets and it can performed only if data is available. In simple, big data is useless if no proper analytics is performed.

Data can be captured from multiple touch points where a customer is connected with brands. It can then be analysed to make conclusions and patterns for deriving data driven decisions based on business objectives.

What are the Challenges in integrating Analytics into Business Decision Making?

The biggest challenges are setting up strategy, tools and technology and right talent to create business value.

Integration and Implementation of Analytics

Mapping out an analytics plan is difficult by creating the right strategy's based on analytics for business development and decision making. Also, the right people who understand the data and business to generate better results and value. 

What is working or not?

The other biggest challenge to find out what is working or not? Understanding the business in detail is critical for the success. 

It is important to find out what is working or not to improve the business, it depends on marketing, competition, operations, location and decisions etc. Data alone never shows what is working or not, but need analytics to find out how various categories of business can be improved.

Data Scientist is a new job role which is evolved as a result of these challenges. It combines the skill sets of business management, consultant, analyst and a programmer.

How to use Data and Analytics in Business Decision Making?

Big data calls for data driven decision making. Analytics can be used for decision making only if there is clear and present need,question,challenge.Until there is no crisp and clear statement or objective, analytics driven decision making is useless. 

Analytics is used in decision making based on the applicability of Analytics Frame work. Though data analytics used for Decision making process, the right decision has to taken and implement by business analysts or managers because data is just an element that make the BDM process more easier. 

At times, the data driven decisions can go wrong, only through the continuous analysis and understanding of the scenario bring out the better data driven results.

"Data will always helps to improve the performance but data alone never sufficient to show the best outcome in the biggest market"

Big Data and Analytics are the core part of any business decision making process as it helps to understand Needs, opportunities, performance, challenges and results. It can drive better outcomes by using the quantitative and qualitative methods. 

PS: Next blog is about how does "fan analytics" disrupt the business decision making. And, how does the implementation of Fan Analytics in the Sports and Entertainment Industry helped brands monetizing their Fans in a better way.