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DATA ANALYTICS SYLLABUS
Key
Concepts of DA
Excel, SQL, Tableau, Power BI, and Python.
EXCEL
Working on Excel – Getting to know the interface.
Tabs, ribbons, and Formula bar
Challenges in Excel
Working on Data
Differences between various versions of excel.
Max & Mins
IF and Loopings in Excel
Pivot in Excel
Charts and Visuals in Excel.
Advanced concepts in Excel – Overview
SQL
Introduction to SQL
Introduction to Database
Knowledge on the data
DDL Queries
DML Queries
TCL Queries
DCL Queries
Functions in SQL (String, Numeric, Date, Conversion)
Joins concepts.
DBMS and RDBMS
ER Diagrams
Normalization and forms
Groups and Filtering
Sub Queries in SQL
TABLEAU
Installation
Tableau UI
Connecting to Datasets
Components of Tableau
Filters
Dashboard
Creating a Story
Formatting
Sorting
Joins in Tableau
Charts and types
Analytics on Tableau
Advanced Tableau – Measures and Dimensions
Clustering
Functions in Tableau
Table calculations (Type conversion & other Functions)
POWER BI
Introduction and Installation
Interface of Power BI
Introduction to Data sources and Challenges
Loading data
Creating visuals in different types
Aggregations in Power BI
Drill through data & Advanced drilling options
Solving challenges
Formatting Visual
Power Query Editor
Structuring the data
Transformation of data
Fill and Replace data
Split and Format data
Date and Time Transformations
Report and Dashboard
Relationships in Power BI
Cardinality and columns selection
Differences between the visuals
Ways of Interacting with Visuals
Bookmarks and Buttons
Data Source settings
Assignment and datasets for practice
PYTHON
What is Python?
Why Python?
Installation of Python
Python IDE
Jupiter Notebook overview
First Query of Python
Python Data Types
Lists
IF, Loops, Dictionaries, Arrays
Reading csv into notebook
Saving the project
Loading a saved project
Examples and practice
Role of Python in ML
No Interview Questions Found..
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