The What and How of Data Analytics

What is Data Analysis?

Data Analysis or Data Analytic is the procedure of screening, cleaning, converting and modeling data for the ultimate goal of finding out something useful from the data. This information is supposed to help form sound conclusions about the data and help make decisions based on these conclusions.

This seems like a very simple task at some point, but when we are dealing with data that consists of a huge variety of parameters and a huge collection of data, patterns can often be misleading.

 

Uses of Data Analysis

Data Analysis helps form conclusions about huge chunks of data. It also provides valuable insight into the contents of humongous amounts of data. This helps make decisions, not from instinct and unreliable factors, but from sound reasons with a scientific reasoning.

Data Analysis also helps businesses make sound policies and practice effective decision making that is guaranteed to bring about change in a positive direction.

Data Analysis can have immense impacts on various fields when applied correctly. An important thing to understand is that the skill of the Data Analyst plays a very important role as to how meaningful the analysis will turn out to be. So quality Data Analysts are also key factors of the whole analysis process.

Data Analysis applied to commercial stores could reveal trends of how different people tend to buy different products. This simple data can then be used to analyze patterns and find out repeating patterns. This could eventually lead the store manager to make a sound decision about the placement of certain commodities next to certain others, which could impact the chances of both products being sold on a major level.

Data Analysis helps decipher subtle patterns that lie in plain sight, but are too simple to be calculated across a million customers. Data Analysis similarly helps different sectors improve their productivity and performance efficiency in a huge number of ways only by simply analyzing simple, passive and non-important data.

 

How it is done?

Data Analysis requires data. Data needs to be obtained in a specific format that then will be easy to process and uniform in nature. Data may be collected from various sources. These sources could be sensors placed in the environment or recording devices or cameras, or it can also be material such as interviews or documentation.

Once obtained, processed and organized, the data could still be inconsistent. It may contain duplicates or could contain errors. The data needs to be cleaned hence, and various techniques are used to identify errors and fix them.

 Analysis follow cleaning. Analysts also apply various kinds of techniques depending on the objective of the analysis, type of data used in the analysis and size of data to obtain useful information.

The data that is analyzed can now be modeled for prediction purposes or for visual imaging.

Prediction aims at using the model generated to predict values. Visualization aims at creating a visual representation of the data for the ease of perception and understanding of the data.

 Enroll in Data analytics courses in Pune to find out how to enter the Data Analytics field.