What will i learn?
- Advanced SQL Queries for Efficient Data Analysis
- Python for Data Analysis (Pandas, NumPy) for Handling Complex Data
- Data Visualization Tools: Power BI / Tableau for Creating Professional Dashboards
- Real-Time Projects for Practical, Industry-Relevant Experience
- Industry-Recognized Certification by Udeck Services for Career Advancement
Curriculum for this course
85 Lessons
00:00:00 Hours
Duration
4 Lessons
00:00:00 Hours
- Course Duration: 3 Months 00:00:00
- Mode: Available in Offline & Online 00:00:00
- Level: Beginner to Intermediate 00:00:00
- Get 40% OFF by enrolling in the online training mode! 00:00:00
Module 1: Introduction to Data Analytics & Business Intelligence
6 Lessons
00:00:00 Hours
- What is Data Analytics? 00:00:00
- Importance of Data in Modern Business 00:00:00
- Types of Data Analytics (Descriptive, Diagnostic, Predictive, Prescriptive) 00:00:00
- Introduction to Data Science vs Data Analytics 00:00:00
- Overview of Business Intelligence Tools 00:00:00
- Role of a Data Analyst vs BI Developer 00:00:00
Module 2: Data Analytics Process & Data Lifecycle
6 Lessons
00:00:00 Hours
- Data Collection Methods (Primary / Secondary) 00:00:00
- Data Storage & Warehousing Basics 00:00:00
- Data Preparation & Cleaning Importance 00:00:00
- Data Lifecycle Management 00:00:00
- Data Ethics, Privacy, & Security 00:00:00
- Real-World Business Use Cases 00:00:00
Module 3: Advanced Excel for Data Analysis (Optional but Valuable)
7 Lessons
00:00:00 Hours
- Data Handling Techniques 00:00:00
- Functions & Formulas (Lookup, Index, Match, IF, etc.) 00:00:00
- Pivot Tables, Pivot Charts 00:00:00
- Conditional Formatting 00:00:00
- Data Validation & Cleaning 00:00:00
- Excel for Quick Data Insights 00:00:00
- Dashboards with Excel 00:00:00
Module 4: Advanced SQL for Data Analysis
8 Lessons
00:00:00 Hours
- Introduction to RDBMS & Relational Data Models 00:00:00
- Advanced SQL Queries: Joins, Subqueries, CTEs 00:00:00
- Aggregations, Window Functions, Case Statements 00:00:00
- Data Manipulation (INSERT, UPDATE, DELETE) 00:00:00
- Functions, Stored Procedures, Views 00:00:00
- Data Import/Export Techniques 00:00:00
- Real-Life Business Query Examples 00:00:00
- Mini Project: Sales / Inventory Reporting Using SQL 00:00:00
Module 5: Python for Data Analysis (Pandas, NumPy, Seaborn, Matplotlib)
8 Lessons
00:00:00 Hours
- Python Basics Refresher (Data Types, Loops, Functions) 00:00:00
- Working with DataFrames using Pandas 00:00:00
- Data Wrangling, Cleaning, Merging, Concatenating 00:00:00
- Handling Missing Data, Outliers 00:00:00
- Exploratory Data Analysis (EDA) Techniques 00:00:00
- NumPy for Numerical Operations 00:00:00
- Visualizing Data: Matplotlib, Seaborn 00:00:00
- Case Study: Retail or Finance Dataset EDA 00:00:00
Module 6: Data Visualization with Power BI
8 Lessons
00:00:00 Hours
- Power BI Interface Overview 00:00:00
- Connecting to Data Sources 00:00:00
- Power Query for Data Preparation 00:00:00
- DAX Basics (Measures, Calculated Columns) 00:00:00
- Data Relationships & Modeling 00:00:00
- Creating Reports, Dashboards, and Visualizations 00:00:00
- Publishing & Sharing Reports Online 00:00:00
- Power BI Best Practices 00:00:00
Module 7: Data Visualization with Tableau
7 Lessons
00:00:00 Hours
- Tableau Basics: Interface, Worksheets, Dashboards 00:00:00
- Connecting to Structured & Semi-Structured Data 00:00:00
- Visualization Techniques: Charts, KPIs, Maps 00:00:00
- Calculated Fields, Parameters, Sets 00:00:00
- Data Relationships & Joins in Tableau 00:00:00
- Storytelling with Data in Tableau 00:00:00
- Real-World Dashboards for Business Scenarios 00:00:00
Module 8: Data Cleaning, Processing & Quality Control
6 Lessons
00:00:00 Hours
- Importance of Data Cleaning 00:00:00
- Detecting & Handling Duplicates, Missing Values 00:00:00
- Data Transformation & Standardization 00:00:00
- Using SQL & Python for Data Quality Checks 00:00:00
- Real-World Data Hygiene Practices 00:00:00
- Data Validation Processes for Reporting 00:00:00
Module 9: Exploratory Data Analysis (EDA) & Insights Generation
6 Lessons
00:00:00 Hours
- Understanding Business Problem Statements 00:00:00
- Analyzing Trends, Correlations, Patterns 00:00:00
- Creating Visual Narratives from Data 00:00:00
- Statistical Methods in Data Analysis 00:00:00
- Hypothesis Testing Basics 00:00:00
- Presenting Actionable Insights to Stakeholders 00:00:00
Module 10: Real-Time Industry Projects & Case Studies
6 Lessons
00:00:00 Hours
- Real Industry Data (Retail, E-commerce, Banking, Healthcare) 00:00:00
- End-to-End Analytics Workflow: SQL, Python, Visualization 00:00:00
- Building Dashboards for Management Decisions 00:00:00
- Reporting Solutions for Marketing, Finance, Operations 00:00:00
- Live Presentation of Project Reports 00:00:00
- Building a Strong Portfolio for Job Interviews 00:00:00
Module 11: Reporting Techniques for Business & Decision Making
6 Lessons
00:00:00 Hours
- Business KPIs: What to Measure 00:00:00
- Visualizing Business Performance Effectively 00:00:00
- Creating Reports for Stakeholders, Managers, Investors 00:00:00
- Executive Dashboards for Different Industries 00:00:00
- Tools Comparison: Excel vs Power BI vs Tableau 00:00:00
- Storytelling with Data: Communicating Complex Information Simply 00:00:00
Module 12: Career Readiness & Certification
7 Lessons
00:00:00 Hours
- Resume Building for Data Analytics Jobs 00:00:00
- Building an Online Portfolio (LinkedIn, GitHub, Kaggle) 00:00:00
- Preparing for Technical Interviews: 00:00:00
- SQL Interview Questions 00:00:00
- Python for Analytics Interview 00:00:00
- Power BI / Tableau Scenarios 00:00:00
- Certification by Udeck Services 00:00:00
Requirements
- Laptop or desktop system
- Basic knowledge of data
- Willingness to practice coding consistently
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Description
Udeck Services offers industry-leading IT training through its Advanced Data Analysis Training program, specially designed for students, graduates, and working professionals looking to upgrade their skills in the dynamic field of data analytics. This comprehensive course covers SQL for database management, Python libraries such as Pandas and NumPy for data analysis, and Power BI / Tableau for professional data visualization.
The training is structured to deliver hands-on learning through live projects, enabling participants to solve real-world data challenges with confidence. By the end of the program, learners will be equipped to analyze complex datasets, create impactful dashboards, and deliver meaningful, data-driven business insights.
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Thu, 17-Jul-2025sangam kumar
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