Business Intelligence and Data Analysis (BIDA)

Week 1: Introduction to Microsoft Excel

Day 1: Navigation, Ribbon, and Workbook Structure

• Overview of Microsoft Excel interface
• Navigating the Ribbon and understanding workbook components
• Creating, saving, and managing Excel workbooks

Day 2: Working with Worksheets

• Inserting, deleting, and renaming sheets
• Organizing data across multiple worksheets
• Hands-on exercise: Setting up your first Excel workbook

Week 2: Excel Data Management and Analysis

Day 1: Cell Formatting and Data Entry

• Cell formatting: Fonts, alignment, borders, and number formats
• Inputting and modifying data
• Basic formulas and functions: SUM, AVERAGE, MIN, MAX, COUNT

Day 2: Advanced Data Techniques

• Data validation: Setting rules and restrictions
• Advanced Paste Special: Transposing and linking data
• Working with ranges: Sorting and filtering data
• Using named ranges for efficient data management
• Practical exercise: Cleaning and organizing a dataset

Week 3: Introduction to Data & Power BI

Day 1: Understanding Data as a Strategic Asset

• The importance of data in business
• Data storytelling and categories of data analytics
• Roles and tasks of data analysts

Day 2: Getting Started with Power BI

• Introduction to Power BI ecosystem: Desktop, Service, Mobile
• Importing data from various sources
• Navigating the Power BI interface
• Hands-on exercise: Setting up your first Power BI project

Week 4: Data Modeling & DAX Formula Language

Day 1: Data Modeling Essentials

• Defining tables and configuring table properties
• Designing relationships and implementing role-playing dimensions
• Creating a star schema data model

Day 2: Introduction to DAX

• Basics of Data Analysis Expressions (DAX)
• Creating calculated columns and measures
• Practical exercise: Building a simple data model with DAX

Week 5: Data Cleaning & Data Preparation in Power BI

Day 1: Connecting and Transforming Data

• Identifying and connecting to data sources
• Using Power Query for data transformation
• Resolving data inconsistencies and quality issues

Day 2: Advanced Data Preparation

• Shaping and transforming tables
• Combining queries and applying naming conventions
• Configuring data loading and handling import errors
• Hands-on project: Preparing a dataset for analysis

Week 6: Data Visualization & Data Analysis in Power BI

Day 1: Creating Interactive Visualizations

• Designing effective charts, maps, and tables
• Customizing visuals for better insights
• Using slicers and filters for interactive reports

Day 2: Building Comprehensive Dashboards

• Combining multiple visuals into cohesive dashboards
• Enhancing dashboards with themes and layouts
• Publishing and sharing reports via Power BI Service
• Practical exercise: Developing a Power BI dashboard

Week 7: Advanced Power BI Techniques

Day 1: Advanced DAX and Calculations

• Deep dive into advanced DAX functions: CALCULATE, FILTER, ALL
• Implementing time intelligence functions for trend analysis
• Creating complex measures and calculated tables

Day 2: Power BI Service and Collaboration

• Utilizing Power BI Service features: workspaces, apps, sharing
• Implementing row-level security
• Collaboration and version control in Power BI
• Hands-on exercise: Publishing and managing reports in Power BI Service

Week 8: Data Visualization Best Practices and Optimization

Day 1: Enhancing Report Interactivity

• Using the Q&A feature for natural language queries
• Creating custom tooltips and interactive visuals
• Configuring bookmarks and navigation within reports

Day 2: Optimizing Power BI Performance

• Identifying and removing unnecessary rows and columns
• Reducing cardinality levels to improve performance
• Best practices for designing efficient data models
• Practical exercise: Optimizing an existing Power BI report

Week 9: Introduction to SQL for Data Management

Day 1: Getting Started with Transact-SQL

• Introduction to Transact-SQL and RDBMS concepts
• Writing and executing basic SELECT statements
• Understanding SQL data types and handling NULLs

Day 2: SQL Built-In Functions

• Using scalar functions in queries
• Aggregate functions: COUNT, SUM, AVG, MAX, MIN
• Grouping data with GROUP BY and HAVING clauses

Week 10: Advanced SQL Techniques

Day 1: Sorting and Filtering Query Results

• Sorting results with ORDER BY
• Limiting returned rows using TOP clause
• Filtering results with WHERE and DISTINCT

Day 2: Modifying Data in SQL

• Inserting data into existing tables
• Using IDENTITY and SEQUENCE for auto-populating columns
• Updating and deleting data with SQL statements
• Appending data using UNION

Week 11: Advanced SQL: Joins and Subqueries

Day 1: Working with Joins

• Understanding INNER JOIN, OUTER JOIN, and CROSS JOIN
• Querying multiple tables using JOIN operations
• Practical exercise: Combining data from different tables

Day 2: Subqueries and Advanced Data Retrieval

• Writing subqueries and nested queries
• Using Common Table Expressions (CTEs)
• Optimizing queries for performance
• Hands-on project: Building complex SQL queries for data analysis

Week 12: Capstone Project & Career Preparation

Day 1: Capstone Project Overview

• Introduction to the capstone project: choosing a problem or fictitious company
• Project planning and team formation
• Setting objectives and deliverables tailored to your background

Day 2: Capstone Project Execution and Presentation

• Managing your project with instructor guidance
• Applying Excel, Power BI, and SQL skills to real-world data challenges
• Presenting project outcomes and insights to stakeholders
• Career preparation: Resume building, interview tips, and certification guidance

Upon successfully completing the BIDA course, students will have developed a strong foundation in business intelligence and data analytics, equipped with practical skills in Excel, Power BI, and SQL. Graduates will:

• understand enterprise-scale data environments, enabling them to work in larger companies that use data warehousing for business decisions.
• be prepared to tackle real-world data challenges and drive strategic initiatives.
• gain a stronger grasp of data modeling, ensuring they can design and optimize databases for analysis.
• fluently use advanced SQL for querying and managing larger datasets more effectively.
• have more advanced Excel skills, making them versatile in both traditional and modern BI toolsets.
• pursue advanced certifications to further their careers in the dynamic field of data analytics
• collaborate confidently with data engineers and IT teams.

At EdgeStride, we are about your success. Thus, your convenience is at the center of our services. We provide an array of payment options to suit everyone:

• Full Payment
• Flexible Payment
  • PayPal
    • PayPal Credit
    • Buy Now Pay Later (3 time installment payments)
  • In-House
    • Half Payment (i.e. 50% at registration and 50% by the end of the 4th week).*
    • 3-time Part Payment - pay in the ratio 50:25:25 (i.e. you will be able to split the payment into 3 parts and pay 50% at registration, 25% by the end of the 4th week and 25% by the end of the 6th week). *

* subject to availability and minimum cost condition