DATA ANALYSIS OVERVIEW

What is Data Analysis ???

Data Analysis = Study of Data 

Simply, it is the process of evaluating data using analytical and statistical tools to discover useful information and aid in business decision making.

Now , the definition/meaning of Data analysis is very much straight-forward and understandable.

Let us dive into the process of Data analysis in a very simplified manner .

Process of Data Analysis - 

• Defiine  the objective - at first we have to clearly define our business objectives . So many decisions will be taken in the future on that basis only .

• Set the Problem Statement - We have to set the question/problem statements for the analysis . e.g - if we are analyse some data on the basis of color of car and rate of accident , the our question might looks like "do Blue sports cars get into accidents more often than others?"

• Collection of Data - Data relevant to the question must be collected from the appropriate sources.

• Data Wrangling - Raw data may be collected in several different formats. The collected data must be cleaned and converted so that data analysis tools can import it.

• Analysis - This is the step where the cleaned and aggregated data is imported into analysis tools. These tools allow you to explore the data, find complex patterns in it, and ask and answer what-if questions through analytical tools . This is the process by which sense is made of data gathered in research by proper application of statistical methods.

• Prediction - After analyse the data using various tools and after getting insights from them , finally we can predict the answer of our defined problem statement . And when it directly connected with a business problem , we have to keep the objectives in mind before publishing any prediction. 

Some Methods of Data Analysis -

• TEXT ANALYTICS - It is about deriving high-quality structured data from unstructured text. Another name for text analytics is text mining. A good reason for using text analytics might be to extract additional data about customers from unstructured data sources to enrich customer master data, to produce new customer insight or to determine sentiment about products and services.

• DATA MINING - Data mining is a method of data analysis for discovering patterns in large data sets using the methods of statistics, artificial intelligence, machine learning and databases. The goal is to transform raw data into understandable business information.

• BUSINESS INTELLIGENCE - Business Intelligence (BI) is the use of computing technologies, applications, and practices for the collection, integration, analysis, and presentation of business information.

• DATA VISUALIZATION - It refers very simply to the visual representation of data. In the context of data analysis, it means using the tools of statistics, probability, pivot tables and other artifacts to present data visually. It makes complex data more understandable and usable.

Thanks for Reading :)