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What is Data Analytics?

Data analytics, also known as data analysis, is a crucial component of modern business operations. It involves examining datasets to uncover useful information that can be used to make informed decisions. This process is used across industries to optimize performance, improve decision-making, and gain a competitive edge.

Data Collection :

It is the first step where raw data needs to be collected for analysis purposes. It consists of two steps in which data collection can be done. If the data are from different source systems then using data integration routines the data analysts have to combine the different data whereas sometimes the data are the subset of the data set. In this case, the data analyst would perform some steps to extract the useful subset and transfer it to the other compartment in the system.

Data Cleansing :

After collecting the data the next step is to clean the quality of the data as the collected data consists of a lot of quality problems such as errors, duplicate entries and white spaces which need to be corrected before moving to the next step. By running data profiling and data cleansing tasks these errors can be corrected. These data are organised according to the needs of the analytical model by the analysts.
Data Analysis and Data Interpretation: Analytical models are created using software and other tools which interpret the data and understand it. The tools include Python, Excel, R, Scala and SQL. Lastly this model is tested again and again until the model works as it needs to be then in production mode the data set is run against the model.

## Data Visualisation:

Data visualisation is the process of creating visual representation of data using the plots, charts and graphs which helps to analyse the patterns, trends and get the valuable insights of the data. By comparing the datasets and analysing it data analysts find the useful data from the raw data.

## 1. Qualitative Data Analytics

Qualitative data analysis doesn’t use statistics and derives data from the words, pictures and symbols. Some common qualitative methods are:

Narrative Analytics is used for working with data acquired from diaries, interviews and so on.
Content Analytics is used for Analytics of verbal data and behaviour.
Grounded theory is used to explain some given event by studying.

## 2. Quantitative Data Analysis

Quantitative data Analytics is used to collect data and then process it into the numerical data. Some of the quantitative methods are mentioned below:

Hypothesis testing assesses the given hypothesis of the data set.
Sample size determination is the method of taking a small sample from a large group of people and then analysing it.
Average or mean of a subject is dividing the sum total numbers in the list by the number of items present in that list.