Data Analyst Course Near Manyata Tech Park
Looking for a data analyst course near Manyata Tech Park that helps you build practical, job-ready skills? Fast Learning Technologies
Live
Delivery Mode
3-4 Months
Duration
5+Live
Real time projects
24/7
Mentor support
About Data Analytics
Looking for a data analyst course near Manyata Tech Park that helps you build practical, job-ready skills? Fast Learning Technologies offers a professional data analyst training program designed for students, freshers, graduates, working professionals, and career changers who want to enter the growing field of data analytics. Our course focuses on real-world tools, hands-on projects, simple explanations, and career-oriented learning so you can understand how data is collected, cleaned, analyzed, visualized, and used for business decisions.
Manyata Tech Park is one of Bengaluru’s major IT and business hubs, surrounded by areas like Nagavara, Hebbal, Thanisandra, HBR Layout, Kempapura, Sahakar Nagar, RT Nagar, Kalyan Nagar, Jakkur, Yelahanka, and North Bengaluru. If you live or work near these locations and want to upgrade your career with data skills, Fast Learning Technologies provides a structured learning path close to your area.
Our data analyst training covers important tools such as Excel, SQL, Python, Power BI, Tableau, statistics basics, data visualization, dashboard creation, reporting, and real-time analytics projects. The course is designed to help learners understand not just the tools, but also how data analysts think, solve problems, and present insights clearly.
Why Choose Fast Learning Technologies for Data Analyst Training Near Manyata Tech Park?
1. Practical and Job-Oriented Training
Our data analyst course is built around real business use cases. You learn how to work with raw data, clean it, organize it, analyze it, and convert it into meaningful reports. Instead of only teaching theory, we guide you through practical examples used in industries like IT, finance, sales, marketing, operations, HR, retail, and customer support.
2. Beginner-Friendly Teaching Method
Many learners worry that data analytics is difficult because it includes tools, numbers, and technical concepts. At Fast Learning Technologies, we explain every topic in simple professional language. You do not need to be an expert in coding or mathematics before joining.
3. Hands-On Projects and Real-Time Practice
A strong data analyst profile needs practical project experience. Our training includes hands-on assignments and project-style tasks where you work with datasets, create reports, build dashboards, and explain insights.
Our Alumni's Are Placed At
Course Curriculum
1. Introduction
- MS Office versions: similarities and differences
- Interface of the latest available version
- Rows and columns
- Keyboard shortcuts for easy navigation
- Data entry using Fill Series
- Find and Select
- Clear options
- Ctrl + Enter
- Formatting options
- Font
- Alignment
- Clipboard
- Copy
- Paste Special
2. Referencing, Named Ranges, Uses, and Arithmetic Functions
- Mathematical calculations with cell referencing
- Absolute reference
- Relative reference
- Mixed reference
- Functions with named ranges
3. Logical and Lookup Functions
- LOOKUP
- VLOOKUP
- Nested VLOOKUP
- HLOOKUP
- INDEX
- Arithmetic functions
- SUM
- SUMIF
- SUMIFS
- COUNT
- COUNTA
- COUNTIFS
- AVERAGE
- AVERAGEIFS
- MAX
- MAXIFS
- MIN
- MINIFS
- Logical functions
- IF
- AND
- OR
- Nested IFs
- NOT
- IFERROR
- Usage of mathematical and logical functions nested together
4. Referring Data from Different Tables
- Various types of Lookup
- Nested IF
- INDEX with MATCH function
- INDIRECT
- OFFSET
5. Advanced Functions
- Combination of arithmetic functions
- Combination of logical functions
- Combination of lookup functions
- Data validation with dependent dropdown
6. Date and Text Functions
Date Functions
- DATE
- DAY
- MONTH
- YEAR
- YEARFRAC
- DATEDIF
- EOMONTH
Text Functions
- TEXT
- UPPER
- LOWER
- PROPER
- LEFT
- RIGHT
- SEARCH
- FIND
- MID
- TTC
- Flash Fill
7. Data Handling
- Data cleaning
- Data type identification
- Remove duplicates
- Formatting and filtering
- Number formatting with shortcuts
- Ctrl + T: converting data into an Excel table
- Formatting table
- Remove duplicates
- SORT
- Advanced Sort
- FILTER
- Advanced Filter
8. Data Visualization
Conditional Formatting
- Icon sets
- Highlighted colour sets
- Data bars
- Custom formatting
Charts
- Bar chart
- Column chart
- Line chart
- Scatter chart
- Combo chart
- Gantt chart
- Waterfall chart
- Pie chart
9. Data Summarization: Pivot Reports and Charts
- Pivot reports
- Insert Pivot Table
- Pivot interface
- Crosstable reports
- Filters
- Pivot charts
- Slicers
- Add slicers
- Connect slicers to multiple reports and charts
- Calculated field
- Calculated item
10. Data Summarization: Dashboard Creation, Tips, and Tricks
- Dashboard types
- Getting reports and charts together
- Use of slicers
- Power Query interface
- Power Query tabs
- Data cleaning
- Data transformation
- Design and placement
- Formatting tables
- Formatting charts
- Formatting sheets
- Proper use of colours and shapes
11. Connecting to Data: Power Query, Pivot, and Power Pivot
- Connecting data from other Excel files
- Connecting data from text files
- Connecting data from other sources
- Loading data into Excel Query
- Using loaded queries
- Merge and Append
- Insert Power Pivot
- Similarities and differences between Pivot and Power Pivot reporting
- Getting data from databases
- Getting data from workbooks
- Getting data from webpages
12. VBA and Macros
- View tab
- Add Developer tab
- Record Macro
- Macro name
- Macro storage
- Record macro to format table using absolute reference
- Format table of any size using relative reference
- Play macro by button
- Play macro by shape
- Play macro as command in a new tab
- Editing macros
13. VBA Basics
- Introduction to the basics of working with VBA for Excel
- Subs
- Ranges
- Sheets
- Comparing values and conditions
- IF statements
- Select Case
- Repeat processes using loops
- For loops
- Do While loops
- Do Until loops
- Communicating with end-users
- Message boxes
- Input boxes
- User Forms
1. Introduction to MySQL
- Introduction to databases
- Introduction to RDBMS
- Explanation of RDBMS through normalization
- Different types of RDBMS
- Software installation
- MySQL Workbench
2. SQL Commands and Data Types
- Types of SQL commands and their applications
- DDL
- DML
- DQL
- DCL
- TCL
- Data types in SQL
- Numeric
- Character
- Date and time
3. DQL and Operators
- SELECT
- LIMIT
- DISTINCT
- WHERE
- AND
- OR
- IN
- NOT IN
- BETWEEN
- EXISTS
- IS NULL
- IS NOT NULL
- Wildcards
- ORDER BY
4. CASE WHEN THEN and Handling NULL Values
- Usage of CASE WHEN THEN to solve logical problems
- Handling NULL values
- IFNULL
- COALESCE
5. Group Operations and Aggregate Functions
- GROUP BY
- HAVING clause
- COUNT
- SUM
- AVG
- MIN
- MAX
- String functions
- Date and time functions
6. Constraints
- NOT NULL
- UNIQUE
- CHECK
- DEFAULT
- Primary Key
- Foreign Key
- Column-level foreign key
- Table-level foreign key
7. Joins
- INNER JOIN
- LEFT JOIN
- RIGHT JOIN
- CROSS JOIN
- SELF JOIN
- FULL OUTER JOIN
8. DDL Commands
- CREATE
- DROP
- ALTER
- RENAME
- TRUNCATE
- MODIFY
- COMMENT
9. DML and TCL Commands
DML Commands
- INSERT
- UPDATE
- DELETE
TCL Commands
- COMMIT
- ROLLBACK
- SAVEPOINT
- Data partitioning
10. Indexes and Views
- Indexes
- Different types of indexes
- Views in SQL
11. Stored Procedures
- Procedure with IN parameter
- Procedure with OUT parameter
- Procedure with INOUT parameter
12. Functions and Constructs
- User-defined functions
- Window functions
- RANK
- DENSE_RANK
- LEAD
- LAG
- ROW_NUMBER
13. Union, Intersect, and Sub-query
- UNION
- UNION ALL
- INTERSECT
- Subqueries
- Multiple queries
14. Exception Handling
- Handling exceptions in a query
- CONTINUE handler
- EXIT handler
15. Triggers
- Triggers before DML statement
- Triggers after DML statement
1. Introduction to Tableau
- What is Tableau?
- What is Data Visualization?
- Tableau products
- Tableau Desktop variations
- Tableau file extensions
- Data types
- Dimensions
- Measures
- Aggregation concept
- Tableau Desktop installation
- Data source overview
- Live vs Extract
2. Basic Charts and Formatting
- Overview of worksheet sections
- Shelves
- Bar Chart
- Stacked Bar Chart
- Discrete Line Chart
- Continuous Line Chart
- Symbol Map
- Filled Map
- Text Table
- Highlight Table
- Formatting options
- Remove grid lines
- Hide axes
- Convert numbers to thousands and millions
- Shading
- Row divider
- Column divider
- Marks Card
3. Filters
- What are filters?
- Types of filters
- Extract filter
- Data source filter
- Context filter
- Dimension filter
- Measure filter
- Quick filter
- Order of operation of filters
- Cascading filters
- Apply filters to worksheets
4. Calculations
- Need for calculations
- Types of calculations
- Basic calculations
- LOD calculations
- Table calculations
- Examples of basic calculations
- Aggregate functions
- Logical functions
- String functions
- Tableau calculation functions
- Numerical functions
- Date functions
- LOD calculations with examples
- Table calculations with examples
5. Data Combining Techniques
- What are data combining techniques?
- Types of data combining techniques
- Joins
- Relationships
- Blending
- Union
6. Custom Charts
- Dual Axis
- Combined Axis
- Donut Chart
- Lollipop Chart
- KPI Cards
- Simple KPI Cards
- KPI Cards with Shape
7. Groups, Bins, Hierarchies, Sets, and Parameters
- Groups
- Purpose of groups
- Bins
- Purpose of bins
- Hierarchies
- Purpose of hierarchies
- Sets
- Purpose of sets
- Parameters
- Purpose of parameters
- Examples of parameters
8. Analytics and Dashboard
- Reference Lines
- Trend Line
- Overview of Dashboard
- Tiled layout
- Floating layout
- Overview of all dashboard objects
- Layout overview
- Dashboard creation with formatting
9. Dashboard Actions and Tableau Public
- Dashboard actions
- Filter action
- Highlight action
- URL action
- Sheet action
- Parameter action
- Set action
- How to save the workbook to Tableau Public website?
Hands-On Projects to Strengthen Your Portfolio
End-to-End Customer Churn Analysis and Prediction System (Domain: Telecom)
Tools Used: Python, Power BI, Excel, SQL Collect and clean telecom customer data, analyze usage patterns, identify churn reasons, build predictive models, and create interactive dashboards for business insights.
Hospital Management and Patient Insights Analytics Project (Domain: Healthcare)
Tools Used: Python, Power BI, Excel, SQL Perform complete analysis of patient admissions, doctor performance, treatment costs, disease trends, and hospital resource utilization with real-time dashboards.
E-Commerce Business Sales and Customer Analytics Platform (Domain: Retail & E-Commerce)
Tools Used: Python, Power BI, Excel, SQL Analyze customer purchasing behavior, sales performance, product demand, profit margins, and regional sales trends to improve business decision-making.
Employee Performance and HR Analytics Management System (Domain: Human Resources)
Tools Used: Python, Power BI, Excel, SQL Analyze employee attendance, productivity, salary trends, attrition rates, and recruitment data to optimize workforce management.
Banking Loan Risk and Financial Fraud Detection Analysis (Domain: Banking & Finance)
Tools Used: Python, Power BI, Excel, SQL Analyze customer financial history, loan approvals, repayment behavior, and suspicious transactions to identify fraud risks and improve loan decision processes.
Trainer profile
Arun
Data Analytics Trainer | 12 Years Experience
He helps students understand analytics concepts, tools, and real-time business applications with ease.
Kiran
Data Analytics Trainer | 8 Years Experience
He guides learners through practical examples, dashboards, reports, and analytical techniques.
Dibya Jyoti
Data Analytics Trainer | 4 Years Experience
He explains concepts clearly and supports learners with hands-on practice and project-based learning.
Nishanth
Data Analytics Trainer | 5 Years Experience
He specializes in practical training with tools, case studies, and real-world data examples.
Sathish
Data Analytics Trainer | 6 Years Experience
He trains students to develop job-ready skills through practical sessions and industry-based examples.
Praveen
Data Analytics Trainer | 3 Years Experience
He helps students gain confidence in data analysis, visualization, and basic analytics tools.
Course batch schedule
| Date | Course | Batch | Timings |
|---|---|---|---|
| 18 May | Python | New Batch | 8 AM - 9 AM |
| 18 May | SQL | New Batch | 6 PM - 7 PM |
| 21 May | Excel | New Batch | 9 AM - 10 AM |
| 21 May | Power BI | New Batch | 2 PM - 3 PM |
| 23 May | AWS | New Batch | 5 PM - 6 PM |
| 23 May | Frontend | New Batch | 10 AM - 11 AM |
| 27 May | Linux | New Batch | 4 PM - 5 PM |
| 30 May | Data Science | New Batch | 8 AM - 9 AM |
| 30 May | Machine Learning | New Batch | 5 PM - 6 PM |
| 03 Jun | AI | New Batch | 8 AM - 9 AM |
Get Certified & Prove Your Industry Readiness
Once you complete the course, submit your projects, and pass the assessments, you’ll receive a certificate that proves your technical skills and industry readiness, recognized by the Govt of India.
Shareable, Credible, and Official
Add your certificate to LinkedIn and share it on WhatsApp, email, or other platforms to make your profile stand out to recruiters.
Boost Your Career Opportunities
Our certificate validates your skills, increasing your chances of landing jobs with better salaries and growth potential.
Students Placements
Data Analytics Course Fee and Duration
Classroom Sessions
35,000/- including taxes
- Fees payable in up to 3 installments
- 0% Interest EMI – Pay in Easy Installments (though education financing partners)
- Cost-effective courses with high ROI, making it worth every penny you invest.
Frequently Asked Questions (FAQ)
Fast Learning Technologies offers a practical data analyst course near Manyata Tech Park for learners who want hands-on training in Excel, SQL, Python, Power BI, Tableau, data cleaning, dashboard creation, and real-time projects.
Students, freshers, graduates, working professionals, MIS executives, Excel users, and career changers can join. The course starts with basics, so learners from both technical and non-technical backgrounds can understand it.
Yes. Manyata Tech Park and nearby areas have many IT and business companies where analytics, reporting, dashboarding, SQL, Excel, and BI skills are useful. The course prepares learners for data analyst, reporting analyst, MIS, and BI-related roles.
You will learn Excel, SQL, Python, Power BI, Tableau, data cleaning, basic statistics, reporting, dashboard creation, business analysis concepts, real-time projects, resume preparation, and interview questions.