Data Analytics

What is Data Analytics? 

Data Analytics is the process of collecting, organizing and studying data to find useful information understand what’s happening and make better decisions. In simple words it helps people and businesses learn from data like what worked in the past, what is happening now and what might happen in the future.

Importance and Usage of Data Analytics

• Helps in Decision Making: It gives clear facts and patterns from data which help people make smarter choices.
• Helps in Problem Solving: It points out what's going wrong and why making it easier to fix problems.
• Helps Identify Opportunities: It shows trends and new chances for growth that might not be obvious.
• Improved Efficiency: It helps reduce waste, saves time and makes work smoother by finding better ways to do things.

Process of Data Analytics

Data analysts, data scientists and data engineers together create data pipelines which helps to set up the model and do further analysis. Data Analytics can be done in the following steps which are mentioned below:

1. Data Collection : Data collection is the first step where raw information is gathered from different places like websites, apps, surveys or machines. Sometimes data comes from many sources and needs to be joined together. Other times only a small useful part of the data is selected.
2. Data Cleansing : Once the data is collected it usually contains mistakes like wrong entries, missing values or repeated rows. In this step the data is cleaned to fix those problems and remove anything that isn’t needed. Clean data makes the results more accurate and trustworthy.
3. Data Analysis and Data Interpretation: After cleaning the data is studied using tools like Excel, Python, R or SQL. Analysts look for patterns, trends or useful information that can help solve problems or answer questions. The goal here is to understand what the data is telling us.
4. Data Visualization: Data visualization is the process of creating visual representation of data using the plots, charts and graphs which helps to analyze the patterns, trends and get the valuable insights of the data. By comparing the datasets and analyzing it data analysts find the useful data from the raw data.