DATA ANALYTICS COMBO (WITHOUT PYTHON)

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The Data Analytics Combo (Without Python) course is designed for learners who want to build practical data analysis skills using SQL, Advanced Excel, and Microsoft Power BI. The training covers data cleaning, SQL queries, Excel analysis, dashboards, data visualization, reporting, and business insights through practical exercises and real-world datasets. Learners gain the skills to work with data, identify useful trends, and present findings clearly for better decision-making. This course is ideal for freshers, students, business analysts, finance professionals, MIS executives, and working professionals looking to start or advance their career in data analytics without learning Python.

Duration of Training : 60 Hours
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Detailed Syllabus • Hands-on Labs • Assignments • Support-Focused • Implementation

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Overview

The Syllabus

Curriculum Designed by Experts

Program Snapshot

• Recommended Duration: 140–180 Hours
• Level: Beginner to Advanced
• Primary Stack: SQL | Advanced Excel | Power Query | Power Pivot | Power BI | DAX
• Learning Model: Concepts + Hands-On Labs + Assignments + Mini Projects + Capstone + Job Scenarios
• Target Roles: Data Analyst, BI Analyst, Reporting Analyst, MIS Analyst, Power BI Analyst, SQL Analyst,
Junior BI Developer

Course Overview

• End-to-end workflow: understand business questions, profile and clean data, query with SQL, analyze
with Excel, transform with Power Query, model data, build DAX measures, create dashboards, validate
results and communicate insights.

Why Job-Oriented

• Every major module includes practical work, assignments and workplace scenarios. Learners work with
raw, inconsistent and multi-source datasets and produce portfolio-ready deliverables.

1. COURSE OVERVIEW & CAREER ROADMAP

1. Course Overview & Career Roadmap

Learning Roadmap

• 1. Analytics fundamentals
• 2. Excel fundamentals
• 3. Advanced Excel
• 4. PivotTables & dashboards
• 5. Power Query
• 6. Power Pivot/data modeling
• 7. SQL fundamentals
• 8. SQL joins, CTEs and subqueries
• 9. Advanced SQL and window functions
• 10. Power BI fundamentals
• 11. Power BI modeling
• 12. DAX
• 13. Advanced DAX
• 14. Power BI Service, security and governance
• 15. Integrated projects
• 16. Capstone and interview preparation

Career Outcomes

• Analyze business data
• Write analytical SQL
• Build advanced Excel models
• Automate preparation with Power Query
• Design Power BI semantic models
• Create DAX KPIs and time intelligence
• Troubleshoot reporting issues
• Present insights to technical and non-technical stakeholders

Program Deliverables

• SQL query portfolio
• Advanced Excel workbooks
• Power BI dashboards
• Data model documentation
• KPI dictionary
• Project presentations

3. PREREQUISITES & ANALYTICS FUNDAMENTALS

3. Prerequisites & Analytics Fundamentals

Job-Oriented Scenarios

• Reconcile two reports with different revenue totals
• Explain a sales decline despite increased order volume
• Define daily operational KPIs for management

Module 1 — Data Analytics Fundamentals

• Descriptive, diagnostic, predictive and prescriptive analytics
• Structured vs semi-structured data
• Dimensions, measures and attributes
• KPIs, metrics, targets and benchmarks
• Data quality: accuracy, completeness, consistency, uniqueness and timeliness
• Data profiling and validation
• Business questions vs analytical questions
• Mean, median, mode, variance and standard deviation
• Outliers, trends, seasonality
• Correlation vs causation
• Data storytelling

Hands-On Labs

• Sales KPI Definition Lab
• Data Quality Profiling Lab
• Outlier Identification Lab
• Business Question-to-KPI Mapping Lab

Assignment

• Create a KPI dictionary, analytical questions and data-validation checklist.

Mini Project

• Retail Sales Diagnostic Analysis — identify revenue trends, weak products, regions and customer
segments.

Job-Oriented Scenarios

• Reconcile two reports with different revenue totals
• Explain a sales decline despite increased order volume
• Define daily operational KPIs for management

4. EXCEL FUNDAMENTALS FOR DATA ANALYTICS

4. Excel Fundamentals For Data Analytics

Module 2 — Excel Fundamentals

• Workbook and worksheet management
• Tables and structured references
• Relative, absolute and mixed references
• Sorting, filtering and advanced filtering
• Data validation
• Text-to-Columns and Flash Fill
• Remove duplicates and data cleaning
• Conditional formatting
• Charts and visual selection
• Formula auditing
• CSV and text imports

Core Formulas

• SUM, AVERAGE, MIN, MAX, COUNT, COUNTA
• IF, AND, OR
• SUMIF/SUMIFS, COUNTIF/COUNTIFS, AVERAGEIF/AVERAGEIFS
• ROUND, ROUNDUP, ROUNDDOWN
• LEFT, RIGHT, MID, LEN, TRIM, CLEAN, SUBSTITUTE
• CONCAT, TEXTJOIN, TEXT, DATE, YEAR, MONTH, DAY

Hands-On Labs

• Sales Data Cleaning Lab
• Employee Attendance Analysis Lab
• Customer Master Cleanup Lab
• Monthly MIS Report Lab

Assignments

• Build a sales tracker with validation and KPI formulas
• Clean a 10,000-row customer dataset and document the process

Mini Project

• Monthly Sales MIS Dashboard — revenue, orders, target achievement and regional performance

Job-Oriented Scenarios

• Prepare daily MIS from CSV exports
• Identify duplicate customer records
• Create exception reports for invalid transactions

5. ADVANCED EXCEL ANALYTICS

5. Advanced Excel Analytics

Module 3 — Advanced Excel

• XLOOKUP
• INDEX + MATCH
• Multi-criteria lookups
• Nested logical formulas
• Dynamic arrays: FILTER, SORT, UNIQUE
• LET
• Advanced date calculations
• Text standardization
• IFERROR
• Scenario and sensitivity analysis
• Goal Seek
• Data Tables
• Scenario Manager
• Forecasting concepts

Hands-On Labs

• Advanced Lookup & Reconciliation Lab
• Dynamic Array Reporting Lab
• Target vs Actual Variance Lab
• Sales Forecasting Lab
• What-If Pricing Model Lab

Assignments

• Build a multi-source reconciliation workbook
• Create a dynamic region/product/month report
• Build a price-volume-margin scenario model

Mini Project

• Financial Planning & Variance Analysis — actual vs budget, variance drivers and scenarios

Job-Oriented Scenarios

• Finance month-end reconciliation
• Dynamic management report by region/product
• Revenue impact of multiple pricing scenarios

6. PIVOTTABLES, PIVOTCHARTS & EXCEL DASHBOARDS

6. Pivottables, Pivotcharts & Exce Dashboards

Module 4 — Excel Reporting

• PivotTables
• Calculated fields
• Date grouping
• Slicers and timelines
• PivotCharts
• KPI cards
• Dashboard layout and visual hierarchy
• Conditional formatting for exceptions
• Presentation-ready reporting

Hands-On Labs

• Sales Pivot Analysis Lab
• Customer Segmentation Lab
• Inventory Aging Lab
• Executive Excel Dashboard Lab

Assignments

• Create a regional sales PivotTable with slicers
• Build an executive dashboard with at least five KPIs and three analytical views

Mini Project

• Retail Executive Dashboard — sales, margin, product mix, customer segment and monthly trend

Job-Oriented Scenarios

• Weekly business review dashboard
• Slow-moving inventory analysis
• Refreshable monthly management report

7. POWER QUERY & DATA PREPARATION

7. Power Query & Data Preparation

Module 5 — Power Query

• ETL workflow
• Excel, CSV, folder and database connections
• Data profiling and data types
• Remove/replace/split/merge
• Fill and group
• Merge and append
• Pivot and unpivot
• Conditional/custom columns
• Parameters
• Refreshable transformations
• Introduction to M language

Hands-On Labs

• Folder-Based Monthly Consolidation
• Customer Master Cleaning
• Sales-Product Merge
• Operational Report Unpivot
• Parameterized Data Load

Assignments

• Combine 12 monthly files into one refreshable dataset
• Standardize customer and product data
• Build a reusable monthly refresh process

Mini Project

• Automated Sales Data Preparation Pipeline using Power Query

Job-Oriented Scenarios

• Consolidate files from 20 branches
• Handle changing date/currency formats
• Replace manual daily copying with a refreshable process

8. POWER PIVOT & DATA MODELING

8. Power Pivot & Data Modeling

Module 6 — Power Pivot & Modeling

• Fact and dimension tables
• Primary and foreign keys
• Relationships
• Star schema
• One-to-many relationships
• Date dimension
• Calculated columns vs measures
• Power Pivot model
• Model size and performance
• Relationship validation

Hands-On Labs

• Sales Star Schema Lab
• Date Dimension Lab
• Customer-Product Model Lab
• Power Pivot KPI Model Lab

Assignments

• Design an e-commerce star schema
• Build a sales model
• Correct duplicate keys and relationship issues

Mini Project

• Multi-Table Retail Analytics Model — transactions, customers, products and calendar

Job-Oriented Scenarios

• Incorrect totals caused by relationships
• Reusable model design
• Optimize a slow workbook

9. SQL FUNDAMENTALS

9. Sql Fundamentals

Module 7 — SQL Fundamentals

• Relational database concepts
• Tables, rows, columns and keys
• SELECT and DISTINCT
• WHERE and ORDER BY
• Aliases and calculated columns
• CASE
• NULL handling
• LIKE, IN and BETWEEN
• Aggregate functions
• GROUP BY and HAVING
• Date and string functions

Hands-On Labs

• Customer Database Exploration
• Sales Filtering & Aggregation
• KPI Query
• Date-Based Sales Analysis

Assignments

• Write 30 retail SQL queries
• Calculate revenue, order count, AOV and top products
• Identify invalid and duplicate records

Mini Project

• SQL Retail Sales Analysis — answer management questions using SQL

Job-Oriented Scenarios

• Top 10 customers by revenue
• Month-wise sales and target comparison
• High-volume but low-revenue products

10. SQL JOINS, SUBQUERIES & INTERMEDIATE ANALYTICS

10. Sql Joins, Subqueries & Intermediate
Analytics

Module 8 — SQL Intermediate

• INNER JOIN
• LEFT JOIN
• RIGHT/FULL OUTER JOIN concepts
• Self and cross joins
• Multi-table joins
• Subqueries and correlated subqueries
• EXISTS/NOT EXISTS
• UNION and UNION ALL
• INTERSECT/EXCEPT concepts
• CTEs
• Conditional aggregation
• Date analysis
• Cohort concepts

Hands-On Labs

• Multi-Table Sales Join
• Customer 360 SQL
• Product Profitability Query
• CTE-Based KPI

Assignments

• Join five related business tables
• Find customers absent from a comparison period
• Build a CTE-based monthly product report

Mini Project

• Customer 360 Analysis — customer, order, product and support data

Job-Oriented Scenarios

• Preserve unmatched customers
• Find customers inactive for 90 days
• Identify high-revenue/low-margin products

11. ADVANCED SQL FOR ANALYTICS

11. Advanced Sql For Analytics

Module 9 — Advanced SQL

• Window functions
• ROW_NUMBER, RANK, DENSE_RANK
• LAG and LEAD
• Running totals and moving averages
• PARTITION BY
• Advanced CTEs
• Views
• Stored procedure concepts
• Temporary tables
• Transactions and ACID concepts
• Indexes and execution-plan concepts
• Duplicate detection
• Data reconciliation
• Query optimization fundamentals

Hands-On Labs

• Top-N per Category
• Customer Ranking
• Running Sales Total
• Month-over-Month Growth
• Deduplication
• SQL Performance Investigation

Assignments

• Regional ranking query
• Month-over-month growth using windows
• Duplicate detection/resolution
• Optimize a deliberately slow query

Mini Projects

• Advanced SQL Business Performance Analysis — executive KPIs, ranking, trends and exceptions

Job-Oriented Scenarios

• Second/third-highest performer by region
• Previous vs current purchase analysis
• First and latest transaction per customer

12. POWER BI FUNDAMENTALS & DATA ACQUISITION

12. Power Bi Fundamentals & Data Acquisition

Module 10 — Power BI Fundamentals

• Power BI Desktop and Service
• Reports, dashboards and semantic models
• Excel, CSV, SQL and folder connections
• Import vs DirectQuery concepts
• Power Query in Power BI
• Basic transformations
• Visual selection
• Filters and slicers
• Formatting and themes
• Interactions
• Publishing

Hands-On Labs

• Power BI Desktop Setup
• Excel-to-Power BI Import
• SQL-to-Power BI Connectivity
• Basic Sales Dashboard

Assignments

• Connect Power BI to a relational sales database
• Create a three-page summary, trend and detail report

Mini Project

• Power BI Sales Performance Dashboard

Job-Oriented Scenarios

• Convert Excel MIS to Power BI
• Build a SQL-driven management report
• Create drillable sales reporting

13. POWER BI DATA TRANSFORMATION & MODELING

13. Power Bi Data Transformation & Modeling

Module 11 — Power BI Modeling

• Merge and append
• Query folding concepts
• Parameters
• Fact/dimension design
• Star schema
• Cardinality
• Filter direction
• Date tables
• Import vs DirectQuery decisions
• Model validation and performance

Hands-On Labs

• Multi-Source Integration
• Star Schema Modeling
• Date Table
• Relationship Troubleshooting
• Model Optimization

Assignments

• Transform five raw sources
• Design a retail star schema
• Correct relationship-driven totals

Mini Project

• Enterprise Sales Semantic Model — reusable sales/customer/product/region/calendar model

Job-Oriented Scenarios

• Duplicate totals
• Automated monthly appends
• Reusable semantic model across reports

14. DAX FUNDAMENTALS

14. Dax Fundamentals

Module 12 — DAX

• Measures vs calculated columns
• SUM, AVERAGE, COUNT, DISTINCTCOUNT
• CALCULATE
• FILTER and ALL
• IF and SWITCH
• DIVIDE
• Variables
• Date tables
• YTD, MTD and QTD
• Previous-period analysis
• Variance and growth

Hands-On Labs

• KPI Measures
• Revenue & Margin
• Target vs Actual
• YTD/MTD/QTD
• Dynamic KPI

Assignments

• Create 20 business measures
• Build revenue, margin, target and growth measures
• Create time-intelligence measures

Mini Project

• Sales KPI Semantic Model

Job-Oriented Scenarios

• Same-period-last-year comparison
• Region-sensitive KPI
• Target achievement without double counting

15. ADVANCED DAX & POWER BI ANALYTICS

15. Advanced Dax & Power Bi Analytics

Module 13 — Advanced DAX

• Filter context and row context
• Context transition
• SUMX and AVERAGEX
• Advanced ranking
• Top-N
• Dynamic titles
• Disconnected tables
• What-if parameters
• Dynamic segmentation
• Retention/cohort concepts
• Pareto analysis
• Rolling averages
• Advanced time intelligence
• DAX performance

Hands-On Labs

• Top-N Product Analysis
• Pareto Customer Analysis
• Rolling 12-Month Sales
• Dynamic Segmentation
• What-If Parameter

Assignments

• Dynamic Top-N selector
• Rolling 12-month KPI
• Customer segmentation measure
• 80/20 cumulative-revenue analysis

Mini Project

• Customer & Product Profitability Analytics

Job-Oriented Scenarios

• Dynamic Top 10
• Rolling revenue trend
• Identify customers contributing 80% of revenue

16. POWER BI DASHBOARDS, SERVICE & GOVERNANCE

16. Power Bi Dashboards, Service & Governance

Module 14 — Advanced Power BI Reporting

• Executive dashboard design
• Drill-down and drill-through
• Tooltips
• Bookmarks and buttons
• Page navigation
• Conditional formatting
• Custom visuals
• Mobile layout concepts
• Power BI Service
• Workspaces
• Publishing and sharing
• Scheduled refresh concepts
• Gateway concepts
• Row-Level Security
• Governance concepts

Hands-On Labs

• Executive Dashboard
• Drill-Through
• Tooltip Page
• Bookmark Navigation
• Row-Level Security
• Publish & Refresh

Assignments

• Build a five-page executive report
• Implement regional RLS
• Create refresh and deployment checklist

Mini Project

• Regional Sales Command Center

Job-Oriented Scenarios

• Regional data restriction
• Executive drill-through to root cause
• Investigate a failed refresh

17. INTEGRATED PROJECTS & BUSINESS CASE STUDIES

17. Integrated Projects & Business Case Studies

Mini Projects

• Retail Sales Analytics — Excel + SQL + Power BI
• HR Workforce Analytics — Excel + Power BI
• Inventory & Supply Chain Dashboard — SQL + Power BI
• Banking Customer Analytics — SQL + Excel
• E-Commerce Customer 360 — SQL + Power BI
• Finance Budget vs Actual — Advanced Excel + Power BI
• Marketing Campaign Performance — SQL + Power BI
• Service Desk KPI Analytics — Excel + SQL + Power BI

Project Lifecycle

• Requirement gathering
• KPI definition
• Source identification
• Data profiling
• Cleaning
• SQL extraction and validation
• Excel reconciliation
• Power Query
• Data modeling
• DAX measures
• Dashboard design
• UAT
• Documentation
• Stakeholder presentation

Deliverables

• Business Requirement Document
• KPI Dictionary
• Source-to-Target Mapping
• SQL Query Pack
• Excel Workbook
• Power BI Semantic Model
• Interactive Dashboard
• Test Checklist
• User Guide
• Project Presentation

Job-Oriented Scenarios

• Stakeholder changes a KPI definition
• Late or missing source data
• Business users challenge dashboard numbers and the analyst traces calculations to source

18. CAPSTONE PROJECT & REAL-TIME JOB SCENARIOS

18. Capstone Project & Real-time Job Scenarios

Capstone Options

• Enterprise Sales & Profitability Analytics
• E-Commerce Customer 360
• Financial Performance & Budget Analytics
• Supply Chain & Inventory Intelligence
• HR Workforce Analytics
• Marketing Campaign & Conversion Analytics
• Service Desk KPI Dashboard

Recommended Capstone

• Enterprise Sales & Profitability Analytics Platform using SQL + Excel/CSV + Power Query + Power BI
• SQL extraction, joins, validation and advanced analysis
• Excel reconciliation and exception analysis
• Power Query automation
• Star-schema semantic model
• DAX KPIs for revenue, margin, growth, targets and rankings
• Executive dashboard with regional/product/customer drill-through
• Regional security concept and documentation

Real-Time Job Scenarios

• Daily sales dashboard
• Month-end revenue reconciliation
• Sales target and incentive analysis
• Customer retention analysis
• Inventory aging
• Marketing ROI
• Finance variance reporting
• Operations SLA reporting
• Executive KPI reporting
• Ad-hoc SQL analysis
• Power BI refresh investigation
• Dashboard performance optimization
• Excel/SQL/Power BI mismatch investigation
• New KPI implementation

19. TROUBLESHOOTING, INDUSTRY TOOLS & BEST PRACTICES

19. Troubleshooting, Industry Tools & Best Practices

Troubleshooting Scenarios

• Duplicate SQL joins
• NULL-related analytical errors
• Slow SQL queries
• Broken Excel lookups
• Formula errors after source changes
• Power Query refresh/type issues
• Duplicate rows after merge/append
• Power BI relationship ambiguity
• Many-to-many issues
• Incorrect DAX totals/filter context
• Date intelligence problems
• Refresh/gateway issues
• RLS validation problems
• Slow Power BI visuals

Industry Tools

• Microsoft Excel / Microsoft 365
• Power Query
• Power Pivot
• Power BI Desktop
• Power BI Service
• SQL Server / Azure SQL concepts
• MySQL / PostgreSQL concepts
• SQL Server Management Studio (SSMS)
• Visual Studio Code
• Git / GitHub
• Jira / Azure DevOps
• Microsoft Teams

Best Practices

• Define KPIs before visuals
• Validate source data
• Use consistent naming
• Build reusable transformations
• Prefer star-schema modeling
• Use measures efficiently
• Document business definitions
• Reconcile dashboards to source totals
• Avoid visual clutter
• Optimize SQL and data models
• Protect sensitive data
• Maintain versioned documentation

20. CERTIFICATIONS, INTERVIEWS, RESUME & PLACEMENT

20. Certifications, Interviews, Resume & Placement

Recommended Certifications

• Microsoft Certified: Power BI Data Analyst Associate (PL-300)
• Microsoft Office Specialist: Excel Expert (Microsoft 365 Apps) — MO-211
• Microsoft Certified: Azure Data Fundamentals (DP-900) as a complementary credential
• Relevant vendor SQL certifications for the target database platform

Mock Interviews

• SQL technical rounds
• Advanced Excel problem-solving
• Power BI/DAX scenarios
• Dashboard case studies
• Data validation scenarios
• Stakeholder communication
• Live SQL coding/debugging
• Power BI model review

Resume Preparation

• ATS-friendly Data Analyst resume
• Project-focused descriptions
• SQL + Excel + Power BI skill positioning
• Power BI portfolio guidance
• GitHub/project documentation
• LinkedIn optimization
• Achievement-oriented bullets

Placement Assistance

• Job-role mapping
• Resume screening and optimization
• Mock interviews
• Technical assessment preparation
• Portfolio presentation support
• Job application strategy
• Mentoring and career counseling

💼 Target Job Roles

• Data Analyst
• Business Intelligence Analyst
• Power BI Analyst
• Reporting Analyst
• MIS Analyst
• SQL Analyst
• Business Analyst
• Junior BI Developer
• Data Visualization Analyst
• Reporting & Dashboard Specialist

Final Outcome

• Learners should be able to take a business requirement, clean and validate data, write analytical SQL,
perform advanced Excel analysis, build a Power BI model, develop DAX measures, create executive
dashboards, troubleshoot reporting issues and present actionable insights.

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Why Radical Technologies

Live Online Training

Highly practical oriented training

Installation of Software On your System

24/7 Email and Phone Support

100% Placement Assistance until you get placed

Global Certification Preparation

Trainer Student Interactive Portal

Assignments and Projects Guided by Mentors

And Many More Features

Course completion certificate and Global Certifications are part of our all Master Program

Live Classroom Training

Weekend / Weekdays / Morning / Evening Batches

80:20 Practical and Theory Ratio

Real-life Case Studies

Easy Coverup if you missed any sessions

PSI | Kryterion | Redhat Test Centers

Life Time Video Classroom Access ( coming soon )

Resume Preparations and Mock Interviews

And Many More Features

Course completion certificate and Global Certifications are part of our all Master Program

Self Paced Training

Self Paced Learning

Learn 300+ Courses at Your Own Time

50000+ Satisfied Learners

Course Completion Certificate

Practical Labs Available

Mentor Support Available

Doubt Clearing Session Available

Attend Our Virtual Job Fair

10% Discounted Global Certification

Course completion certificate and Global Certifications are part of our all Master Program

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Radical Technologies is the leading IT certification institute in Bangalore, offering a wide range of globally recognized certifications across various domains. With expert trainers and comprehensive course materials, it ensures that students gain in-depth knowledge and hands-on experience to excel in their careers. The institute’s certification programs are tailored to meet industry standards, helping professionals enhance their skillsets and boost their career prospects. From cloud technologies to data science, Radical Technologies covers it all, empowering individuals to stay ahead in the ever-evolving tech landscape. Achieve your professional goals with certifications that matter.

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Data Analytics Combo (without Python) Course Certification With Training In Bangalore

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