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Turn Data into Action and Become a Data Analyst

Data analytics, in simple terms, is like using detective skills on data to uncover useful information. It involves collecting data from different sources, like numbers or text, and then cleaning it up to remove mistakes. Next, we look at the data to see if there are any patterns or interesting things hidden in it. Finally, we use this information to make better decisions or solve problems.

Needs In Data Analytics

Python

Operators, Datatypes & Variables - Strings & Numbers - Conditional Statements & Loops - String Methods & Functions - OOP Concept

Introduction to Database

Introduction - SQL - Aggregation, Relationships, Join - Normalisation & Advanced SQL - Querying & ACID Properties

Introduction to Data Analytics

Overview - Opportunities and Careers paths - Roles and responsibilities - Data Analytics Case Studies

Data Visualization

Fundamentals - Introduction to Power BI - Data Visualization using Power BI

Advanced-Data Visualization

Slicers and Filters - Interactive Visualisations - Creating Paginated Reports - Creating Dashboards

Data Cleaning & Transformation using Excel /Power Query

Data Cleaning Techniques - Data Transformation Techniques - Introduction to Power Query - Data Types and Filters in Power Query - Inbuilt Column and Row Transformations - Creating a Query in Power Query - Combining Two Data Sets

Data Analysis using Python Libraries

Introduction to NumPy and Pandas - Indexing and Slicing NumPy arrays - Indexing and Filtering Pandas data frames and series - Modifying Pandas data frames and Series

Data Analytics using Tableau

Fundamentals of Tableau - Essential Design Principles for Visualization with Tableau - Creating Dashboards and Interactive Reports in Tableau

Road Map Of Data Analytics



Advance Excel

Excel Macro - VBA

Advance SQL

Tableau

Power BI

Statistics

R Language

Python

Industry Relevant Project

Job Preparation

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