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Data Analytics - What is Data Analytics, Steps in data Analytics, Purpose of Data Analytics

 

Data Analytics - Data Analysis
Data Analytics - What is Data Analytics - Steps in Data Analytics - Purpose of Data Analytics

What is Data Analytics?

Data analytics is a subfield of  Data Science. Data analytics is the process of using statistical methods, algorithms and visualization techniques to analyze data to extract meaningful insights, identify different trends and answer specific questions.

It helps companies, organizations and different industries to know market trends, their performance, and relationships in their data from which they can make decision making. Basically, Data analysis is done for decision-making.

Process of Data Analytics:

The steps included in data analytics are 
  1. Collecting the Data 
  2. Cleaning the Data 
  3. Transforming the Data
  4. Data Analysis
  5. Data Visualization
  6. Decision Making
How to do data analysis?

Steps Of Data Analytics

1:Collecting the Data:

Collecting the data is the First step, to which we collect data from different platforms for further analysis. 

2:Cleaning the Data:

Cleaning the data is the second step from which we remove noise and outliers to clean our data.
We use different tools for data cleaning like Excel, SQL, R and Python. 

3:Transforming The Data:

Transforming the Data means converting the cleaned data to a more structured and usable form to understand easily. We use these tools and languages for data transformation. 

  1. Python:

    • Pandas
    • NumPy
    • Matplotlib
    • Seaborn
    • SciPy

  2. R:

    • RStudio
    • dplyr
    • tidyr
    • ggplot2

  3. SQL:

    • MySQL
    • PostgreSQL
    • SQLite

  4. Excel 


4:Data analysis:

After doing the transformation we do data analysis on the data to extract all the information according to our needs. From the above tools and computer languages, we do this.

5:Data Visualization: 

After the data analysis, we do data visualisation to understand our data in an easy form to understand easily. We use different tools and computer languages

  1. Python:

    • Matplotlib
    • Seaborn
    • Plotly
    • Bokeh

  2. R:

    • ggplot2

  3. Tableau

  4. Power BI


6:Decision Making:

After this, we make decisions above our analysis. and solve the problems for which we do data analysis.

Purpose of Data Analytics:

The purpose of data analytics is to enable organizations to make smarter decisions, improve efficiency, predict market trends, enhance customer experiences, and ultimately increase profitability.












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