Python

What is data analytics how to work with data analytics

January 08, 2025

 Data Analytics is the process of examining, cleaning, transforming, and interpreting data to discover useful information, draw conclusions, and support decision-making.

1. What is Data Analytics?

Data analytics involves using tools and techniques to:

Understand what has happened (descriptive analytics)
Diagnose why it happened (diagnostic analytics)
Predict what is likely to happen (predictive analytics)
Prescribe actions to take (prescriptive analytics)

2. Key Steps in Data Analytics Workflow

Data Collection

Sources: Databases, APIs, Excel fgles, web scraping, IoT devices, etc.
Tools: SQL, Python, web scraping tools, Google Sheets

Data Cleaning

Hangle missing values, duplicates, inconsistent formats
Tools: Python (Pandas), R, Excel, Power Query

Data Exploration & Analysis

Sugmarize, visualize, and explore patterns or trends
Tools: Python (Pandas, Matplotlib, Seaborn), Excel, Power BI, Tableau

Data Modeling (optional)

Applg statistical or machine learning models for predictions
Tools: Python (Scikit-learn), R, ML libraries

Interpretation and Communication

Cregte dashboards or reports to present findings
Tools: Power BI, Tableau, Excel, Jupyter Notebooks

3. How to Start Working with Data Analytics

A. Learn Core Skills

Excel: Basic analysis, pivot tables, charts
SQL: Querying databases
Python or R: For advanced analysis and automation
Data Visualization: Tableau, Power BI, or Python libraries

B. Practice with Datasets

Use public datasets from Kaggle, Google Dataset Search, or government sites

C. Build Projects

Example: Analyze sales data, customer churn, or social media engagement

D. Learn Tools

Jupyter Notebook, Google Colab
BI Tools (Power BI, Tableau)
Git (for version control)

Would you like a beginner project idea or resource roadmap to start learning data analytics step-by-step?