In 2018, data and data analytics can't be ignored. Data Analytics is quite big buzz these days. Analytics is the combination of analysis and logics. Analytics can't be performed without software's. By applying data analytics we can draw conclusion about the any given set of information.
Why do we need an Analysis Plan?
To make sure the questions and your data collection instrument will get the information you want.
To align your desired "report" with the results of analysis and interpretation.
To improve reliability-consistent measures over time.
So basically these are some of the aspects so data analysis plan is in demand.
Key Component of Data Analysis Plan:
Purpose of the evaluation should be mandate, so there are some goals and some needs in the business which required everything is most likely it would be driven around competitors or it could be driven around increasing your revenue or also there could be some challenges or problems with respect to sale different industries can have different aspects so we are talking mostly from our sales marketing point of view but let's say if you think about a healthcare industry or a pharmaceutical industry so they could be looking at how basically drugs react so they might have sample data for clinical data that talks about application of certain drugs. After that a certain set of questions comes into our mind we will resolve those questions with the help of best analysis technique. Once all the things done then data will be presented in such proper format.
What is business Analytics?
Business analytics refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics is used by companies to data driven decision making.
Importance of Business Analytics
Business analytics helps in:
Profitability of businesses.
Revenue of Businesses.
Enhances understanding of data.
Helps businesses to remain competitive.
Enables creation of informative reports.
Types of Analytics:
Following are the different types of data analytics:
Describes what has already occurred. It helps the business understand how things are going. This is the past data and we are just preparing the summary of this data to understand it. It is more reactive in nature and mostly deals with the past. In short it is something what we observe. This is useful to us because from the descriptive analytics we can learn from the past behaviors, and understands how they will influence the future.
"By Descriptive Analytics when you need to understand at an aggregate level what is going on in your company, and when you want to summarize and describe different aspects of your business."
It is the most popular and tells us what will probably happen in future as result of something that has already happened. This basically helps in decision making. They help the business forecast future behavior and result. It is proactive means what will happen in future. In short this is the prediction for the future. That's why the foundation of predictive analytics is based on possibilities. Use Predictive Analytics any time we get to know about the future.
"Organizations use predictive analytic to get the difficult problems solved and uncover the new opportunities".
This is the last but not the least point that helps business prescribe the right course of action. They not only tell us what probably will happen but, also what should be done if it happens. This is again a proactive in nature. In short this is the influencing factor and tells us the necessary steps what we should take. Use Prescriptive Analytics anytime you need to provide users with advice on what action to take.
"Predictive tells us what is going to happen next and descriptive tells the action what we should take to get something materialized".
Hence, in recent years, Data Analytics have become a buzzword for every business organization as information is the crucial resource for any organization which can provide a competitive edge to the company.