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Complete Data Analytics Training with Excel, SQL, Power BI, and Python
Gain in-demand skills to collect, analyze, and visualize data using top analytics tools and techniques. Learn data wrangling with Excel and SQL, perform statistical analysis with Python, and create impactful dashboards using Power BI for data-driven decision-making.
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6 LPA
Average annual salary for Data Analytics professionals
Source : Glassdoor
27k+
Career opportunities related to Data Analytics
Source : Linkedin
25%
Compound annual growth rate of the Data Analytics market
Source : Simplilearn
Overview
Industry-Oriented Data Analytics Training at DIGIT institute
Embark on a transformative journey into Data Analytics at DIGIT institute. Learn essential skills for managing, analyzing, and visualizing data using modern tools and methodologies.
- Learn Data Visualization using Tools like Power BI
Our expert instructors bring extensive real-world experience and personalized guidance, ensuring you not only understand the theory but also apply practical skills. Engage in hands-on projects, case studies, and mock assessments to prepare for a successful career in the dynamic field of data analytics.
- Build Skills in Excel, SQL & Python for Data Analysis
Course Details
Data Analytics Proficiency Path
Explore our Data Analytics curriculum, from Excel basics to advanced SQL, Python data analysis, visualization, and Power BI insights for real-world data mastery.
Excel
1
Introduction to Excel for Data Analysis
2
Overview of Excel interface
3
Basics of navigating and working with sheets
4
Introduction to cells, rows, columns, and ranges
5
Understanding basic functions (SUM, AVERAGE, COUNT)
6
Working with mathematical and statistical functions
7
Introduction to text functions for data manipulation
8
Advanced Formulas and Functions
9
Working with logical functions (IF, AND, OR)
10
Exploring lookup functions (VLOOKUP, HLOOKUP, INDEX, MATCH)
11
Introduction to array formulas
12
Identifying and handling missing data
13
Removing duplicates and dealing with errors
14
Text-to-columns and data-splitting techniques
15
Formatting data for analysis
16
Creating basic charts and graphs
17
Tips for effective data presentation
18
Introduction to PivotTables for dynamic data analysis
19
Creating PivotCharts for visual insights
20
Customizing and formatting PivotTables and PivotCharts
21
Time-saving shortcuts and productivity hacks
22
Excel with AI
1
Mastering advanced Excel functions and formulas
2
Using nested IFs and complex logical expressions
3
Dynamic named ranges using OFFSET and INDIRECT
4
Creating interactive dashboards with form controls
5
Advanced data validation techniques
6
Leveraging conditional formatting for insights
7
Working with advanced lookup techniques (XLOOKUP, XMATCH)
8
Understanding and applying array formulas
9
Using dynamic arrays and new Excel functions
10
Advanced PivotTable techniques and slicers
11
Creating calculated fields and calculated items
12
Using Power Query for data transformation
13
Merging and appending queries in Power Query
14
Creating data models using Power Pivot
15
Working with relationships and DAX basics
16
Optimizing workbook performance
17
Automating tasks with macros and VBA intro
18
Customizing Excel interface with macro buttons
19
Collaborating with shared workbooks and co-authoring
20
Advanced charting techniques for data storytelling
21
Securing workbooks and protecting data
22
Using Excel for business intelligence applications
Excel
1
Introduction to Excel for Data Analysis
2
Overview of Excel interface
3
Basics of navigating and working with sheets
4
Introduction to cells, rows, columns, and ranges
5
Understanding basic functions (SUM, AVERAGE, COUNT)
6
Working with mathematical and statistical functions
7
Introduction to text functions for data manipulation
8
Advanced Formulas and Functions
9
Working with logical functions (IF, AND, OR)
10
Exploring lookup functions (VLOOKUP, HLOOKUP, INDEX, MATCH)
11
Introduction to array formulas
12
Identifying and handling missing data
13
Removing duplicates and dealing with errors
14
Text-to-columns and data-splitting techniques
15
Formatting data for analysis
16
Creating basic charts and graphs
17
Tips for effective data presentation
18
Introduction to PivotTables for dynamic data analysis
19
Creating PivotCharts for visual insights
20
Customizing and formatting PivotTables and PivotCharts
21
Time-saving shortcuts and productivity hacks
22
Excel with AI
1
Mastering advanced Excel functions and formulas
2
Using nested IFs and complex logical expressions
3
Dynamic named ranges using OFFSET and INDIRECT
4
Creating interactive dashboards with form controls
5
Advanced data validation techniques
6
Leveraging conditional formatting for insights
7
Working with advanced lookup techniques (XLOOKUP, XMATCH)
8
Understanding and applying array formulas
9
Using dynamic arrays and new Excel functions
10
Advanced PivotTable techniques and slicers
11
Creating calculated fields and calculated items
12
Using Power Query for data transformation
13
Merging and appending queries in Power Query
14
Creating data models using Power Pivot
15
Working with relationships and DAX basics
16
Optimizing workbook performance
17
Automating tasks with macros and VBA intro
18
Customizing Excel interface with macro buttons
19
Collaborating with shared workbooks and co-authoring
20
Advanced charting techniques for data storytelling
21
Securing workbooks and protecting data
22
Using Excel for business intelligence applications
SQL
1
Introduction to SQL and Database Fundamentals
2
Overview of SQL and its applications
3
Introduction to Relational Databases
4
Basic SQL syntax and structure
5
Creating and modifying tables with CREATE and ALTER
6
Understanding data types and constraints
7
Retrieving Data with SELECT Statements
8
Basics of SELECT statements
9
Filtering data with WHERE clause
10
Sorting results with ORDER BY
1
Aggregation and Grouping
2
Understanding aggregate functions (SUM, AVG, COUNT)
3
Grouping data with GROUP BY
4
Working with complex WHERE conditions
5
Using operators (AND, OR, NOT, etc)
6
Window Functions and Analytic Queries
7
Introduction to window functions
8
Performing analytic queries with OVER clause
1
Joins and Subqueries
2
Performing INNER and OUTER joins
3
Using subqueries for complex queries
4
Case Statements and CTE Queries
5
Understanding and using CASE statements in SQL
6
Applying CASE statements in data analysis scenarios
7
Introduction to Common Table Expressions
8
Using CTEs for recursive queries and data manipulation
1
Time-saving shortcuts and productivity hacks
2
Optimization of queries
3
Optimization of queries using AI
4
Interview based SQL queries
5
Working on live project
6
Working on industry-oriented data
7
Problem-solving using SQL on industrial data
SQL
1
Introduction to SQL and Database Fundamentals
2
Overview of SQL and its applications
3
Introduction to Relational Databases
4
Basic SQL syntax and structure
5
Creating and modifying tables with CREATE and ALTER
6
Understanding data types and constraints
7
Retrieving Data with SELECT Statements
8
Basics of SELECT statements
9
Filtering data with WHERE clause
10
Sorting results with ORDER BY
1
Aggregation and Grouping
2
Understanding aggregate functions (SUM, AVG, COUNT)
3
Grouping data with GROUP BY
4
Working with complex WHERE conditions
5
Using operators (AND, OR, NOT, etc)
6
Window Functions and Analytic Queries
7
Introduction to window functions
8
Performing analytic queries with OVER clause
1
Joins and Subqueries
2
Performing INNER and OUTER joins
3
Using subqueries for complex queries
4
Case Statements and CTE Queries
5
Understanding and using CASE statements in SQL
6
Applying CASE statements in data analysis scenarios
7
Introduction to Common Table Expressions
8
Using CTEs for recursive queries and data manipulation
1
Time-saving shortcuts and productivity hacks
2
Optimization of queries
3
Optimization of queries using AI
4
Interview based SQL queries
5
Working on live project
6
Working on industry-oriented data
7
Problem-solving using SQL on industrial data
Python
1
Introduction to Python and Jupyter Notebooks
2
Overview of Python programming language
3
Introduction to Jupyter Notebooks for data analysis
4
Variables, data types, and basic operations
5
Lists, tuples, and dictionaries
6
Inbuilt functions
7
Data Manipulation with Python
8
Conditional statements and loops
9
User defined functions
10
Functions such as map, filter, lambda
1
Data Manipulation with Pandas
2
Overview of Pandas Library
3
Reading and writing data along with basic operations with Pandas
4
Data Cleaning and Preprocessing with Pandas
5
Handling missing data
6
Removing duplicates and dealing with outliers
7
Cleaning and adjustments in data
1
Exploratory Data Analysis (EDA) with Pandas
2
Descriptive statistics and data summarization
3
Grouping and aggregating data
4
SQL-like operations in data
5
Data Visualization with Matplotlib
6
Creating basic plots (line plots, scatter plots, histograms)
7
Customizing and styling visualizations
1
Introduction to NumPy for numerical operations
2
Working with arrays and matrices
3
Advanced Data Visualization with Seaborn
4
Creating informative and aesthetically pleasing visualizations
5
Pair plots, heatmaps, and advanced plotting techniques
1
Statistical Analysis with SciPy
2
Introduction to statistical tests and hypothesis testing
3
Implementing statistical tests in Python
4
Final Project and Case Studies
5
Participants work on a real-world data analysis project
6
Applying learned Python skills to analyze and visualize data
Python
1
Introduction to Python and Jupyter Notebooks
2
Overview of Python programming language
3
Introduction to Jupyter Notebooks for data analysis
4
Variables, data types, and basic operations
5
Lists, tuples, and dictionaries
6
Inbuilt functions
7
Data Manipulation with Python
8
Conditional statements and loops
9
User defined functions
10
Functions such as map, filter, lambda
1
Data Manipulation with Pandas
2
Overview of Pandas Library
3
Reading and writing data along with basic operations with Pandas
4
Data Cleaning and Preprocessing with Pandas
5
Handling missing data
6
Removing duplicates and dealing with outliers
7
Cleaning and adjustments in data
1
Exploratory Data Analysis (EDA) with Pandas
2
Descriptive statistics and data summarization
3
Grouping and aggregating data
4
SQL-like operations in data
5
Data Visualization with Matplotlib
6
Creating basic plots (line plots, scatter plots, histograms)
7
Customizing and styling visualizations
1
Introduction to NumPy for numerical operations
2
Working with arrays and matrices
3
Advanced Data Visualization with Seaborn
4
Creating informative and aesthetically pleasing visualizations
5
Pair plots, heatmaps, and advanced plotting techniques
1
Statistical Analysis with SciPy
2
Introduction to statistical tests and hypothesis testing
3
Implementing statistical tests in Python
4
Final Project and Case Studies
5
Participants work on a real-world data analysis project
6
Applying learned Python skills to analyze and visualize data
Power BI
1
Case Studies and Discussion & Power BI
2
Reviewing case studies of Python usage in data analysis
3
Q&A and discussions on best practices
4
Introduction to Power BI
5
Understanding the Power BI interface
6
Importing data from different sources
7
Transforming and shaping data within Power BI
1
Data Modeling and Relationships in Power BI
2
Creating a data model in Power BI
3
Understanding relationships between tables
4
Implementing calculated columns and measures
5
Using DAX (Data Analysis Expressions) for advanced calculations
6
Visualizations and Interactivity
7
Creating common visualizations (bar charts, line charts, etc.)
8
Customizing visualizations for better insights
9
Adding interactivity to reports and dashboards
10
Implementing drill-through actions for detailed analysis
11
The Art of Storytelling with Data
12
Principles of Effective Data Storytelling
13
Importance of narrative in data presentations
14
Building a cohesive narrative in Power BI
15
Using bookmarks and storytelling features
1
Real-Time Dashboards
2
Setting up real-time data streaming in Power BI
3
Creating dashboards for live data monitoring
4
Advanced Features and Custom Visuals
5
Exploring custom visuals and visuals from the marketplace
6
Leveraging advanced features like forecasting and clustering
7
Case Studies and Discussion
8
Reviewing case studies of effective Power BI usage
9
Q&A and discussions on best practices in storytelling with data
Power BI
1
Case Studies and Discussion & Power BI
2
Reviewing case studies of Python usage in data analysis
3
Q&A and discussions on best practices
4
Introduction to Power BI
5
Understanding the Power BI interface
6
Importing data from different sources
7
Transforming and shaping data within Power BI
1
Data Modeling and Relationships in Power BI
2
Creating a data model in Power BI
3
Understanding relationships between tables
4
Implementing calculated columns and measures
5
Using DAX (Data Analysis Expressions) for advanced calculations
6
Visualizations and Interactivity
7
Creating common visualizations (bar charts, line charts, etc.)
8
Customizing visualizations for better insights
9
Adding interactivity to reports and dashboards
10
Implementing drill-through actions for detailed analysis
11
The Art of Storytelling with Data
12
Principles of Effective Data Storytelling
13
Importance of narrative in data presentations
14
Building a cohesive narrative in Power BI
15
Using bookmarks and storytelling features
1
Real-Time Dashboards
2
Setting up real-time data streaming in Power BI
3
Creating dashboards for live data monitoring
4
Advanced Features and Custom Visuals
5
Exploring custom visuals and visuals from the marketplace
6
Leveraging advanced features like forecasting and clustering
7
Case Studies and Discussion
8
Reviewing case studies of effective Power BI usage
9
Q&A and discussions on best practices in storytelling with data
Unique Aspects
Exploring Course Essentials
Embark on a journey to understand the critical elements of our course.
Learn Online
Embark on a learning journey with our diverse courses, available online.
professional Instructors
Begin your learning journey with our accomplished instructors, professionals in their fields.
1:1 Mentorship
Experience personalized growth with our 1:1 mentorship, where dedicated mentors guide you toward success.
Low Student - Teacher Ratio
Benefit from personalized guidance and a supportive learning environment with our small class sizes.
Flexible Learning Options
Enhance your education with flexible choices that fit your schedule and preferences.
Hands-On Projects
Engage in practical, real-world projects to reinforce key skills and essential concepts.
Comprehensive Curriculum
Follow a meticulously designed curriculum that takes you from core fundamentals through advanced, real‑world applications.
Regular Assessments
Keep your learning on track with periodic quizzes and projects that reinforce concepts and measure your progress.
Career Support
Get expert career advice, resume building, and interview prep to launch your dream job.
Your Enrollment Journey
Track Your Progress Toward Enrollment
1. Registration
Register online, provide details, help admissions understand your career goals.
2. Test
Submit application, then an assessment ensures eligibility and program aptitude.
3. Offer Applicable
After review, eligible candidates get scholarship offers and confirmation email.
4. Fee Payment
Review your admission offer, promptly pay fee to confirm enrollment.
Certifications
Advance Your Career with Our Data Analytics Certification
Industry Recognition
Our certifications are well-regarded in the software industry, providing valuable opportunities for career advancement
Skill Validation
Our certifications validate your skills through practical application, equipping you for the workforce and demonstrating your expertise to employers.
Career Advancement
Achieve new heights in your professional journey with our certifications.
What Our Students Say
Shared Experiences from Our Students
Upcoming Sessions
Join Our Upcoming Batches
Secure your spot in the next batch. Limited seats available. Enroll now and start your learning journey with expert-led live training.
Contact for Next BatchesFAQs
Quick Answers to Common Questions
Can't find the answer you're looking for ? Our team is here to help you.
Contact UsNo prior experience is required, although familiarity with basic IT concepts and coding can be beneficial. Our course caters to beginners as well as those looking to enhance their existing skills.
Absolutely! We provide career support services including resume building, mock tests, mock interviews, and job placement assistance to help you kickstart your career in Data Analytics.
Yes, our course includes hands-on projects and practical assignments that simulate real-world scenarios. You'll have the opportunity to apply your skills and work on actual Data Analytics tasks and cloud configurations.
Yes, our online platform provides access to course materials, lectures, and resources, allowing you to study at your own pace.
Enrolling is easy! Simply visit our website or contact our admissions team for more information on course schedules, fees, and enrollment procedures.
This course equips you with the skills and knowledge needed to excel in Data Analytics, a field that is in high demand. With comprehensive training in data wrangling, statistical analysis, visualization, and more, you will be well-prepared for a variety of roles in the industry.