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Business Analystics
Business Analytics (BA) is essential for making data-driven decisions, improving efficiency, and staying competitive in today's fast-paced market. It enables businesses to analyze large datasets, uncover trends, optimize operations, and enhance customer experiences.
With the Help of Our Courses, You Will Be Able To:
✔️ Apply Business Analytics concepts to real-world problems.
✔️ Analyze and interpret data to identify key business trends.
✔️ Optimize business operations using SQL and advanced analytics techniques.
✔️ Develop dashboards and reports to communicate insights effectively.
Course Prerequisites
This course is designed for beginners and professionals looking to transition into Business Analytics. A
basic understanding of business processes and IT systems is helpful but not mandatory.
Recommended prerequisites:
✅ Basic knowledge of Excel (Pivot Tables, Formulas)
✅ Familiarity with business operations & decision-making
✅ (Optional) Basic understanding of SQL databases (not mandatory)
1. Introduction to Business Analytics
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What is Business Analytics?
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Difference Between Business Intelligence (BI) & Business Analytics
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Role of a Business Analyst vs. Data Analyst vs. Data Scientist
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Key BA Responsibilities in Different Industries
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Types of Analytics:
o Descriptive Analytics (Historical Data Analysis)
o Diagnostic Analytics (Root Cause Analysis)
o Predictive Analytics (Forecasting & Modeling)
o Prescriptive Analytics (Decision Optimization)
2. Data Warehousing
- Introduction to data warehousing concepts.
- Data modeling and schema design.
- Extract, Transform, Load (ETL) processes.
- Data integration techniques.
3. Data Visualization
- Principles of data visualization.
- Tools like Tableau, Power BI, or QlikView for creating visualizations.
- Designing effective dashboards and reports.
- Best practices for presenting data visually.
4. Data Analysis Techniques
- Statistical analysis methods.
- Predictive modeling and forecasting.
- Regression analysis.
- Clustering and segmentation techniques.
5. Data Mining
- Introduction to data mining concepts.
- Association analysis.
- Classification and regression trees.
- Cluster analysis.
6. Advanced Analytics
- Machine learning algorithms and their applications in business.
- Deep learning concepts (neural networks, etc.) for analytics.
- Natural Language Processing (NLP) for text analysis.
- Sentiment analysis and social media analytics.
7. Business Intelligence Tools and Technologies
- In-depth training on specific BI tools like Tableau, Power BI, MicroStrategy, etc.
- Hands-on exercises and projects using these tools.
- Customizing and optimizing BI solutions for different business needs.
8. Data Governance and Ethics
- Ensuring data quality and integrity.
- Privacy and security considerations.
- Data governance frameworks.
- Compliance with regulations such as GDPR, CCPA, etc.
9. Case Studies and Real-world Applications
- Analyzing real-world business cases.
- Applying BI and BA techniques to solve business problems.
- Discussion on successful BI implementations and lessons learned.
10. Capstone Project
- A hands-on project where participants apply all the skills and knowledge gained throughout the course to solve a business problem or address a specific challenge.
- Presentation of findings and recommendations.
These modules can vary in depth and focus depending on the specific course and its target audience, whether it's aimed at beginners, intermediate learners, or advanced professionals. Additionally, courses may include guest lectures from industry experts, workshops, and practical exercises to enhance learning and skill application.
Curriculum
181 Lessons
What is SQL Server?
Why SQL?
DBMS vs RDBMS
SQL Syntax
SQL | WHERE Clause
SQL | SELECT Query
SQL | ORDER BY
SQL | GROUP BY
SQL | Aliases
HAVING Clause
Eliminating Duplicate Rows
Table/Column/Row/Cell
Relationship
Types of Relationships
Data Types
String Data Types
Numeric Data Types
Date and Time Data Types
Constraints
NOT NULL Constraint
UNIQUE Constraint
DEFAULT Constraint
PRIMARY Key
FOREIGN Key
CHECK Constraint
Functions
Mathematical Functions
String Functions
Date and Time Functions
Conversion Functions
Operators
Assignment operator
Arithmetic operator
Comparison operator
Logical operator
Set operator
SQL Commands
DDL (Data Definition Language)
DML (Data Manipulation Language)
TCL (Transaction Control Language)
DCL (Data Control Language)
SQL Commands / Statements
Sub Query
Types of Sub Query
Single Row Sub Query
Multiple row sub query
Joins
Left Outer Join
Right Outer Join
Full Outer Join
Self Join
CROSS Join
Inner Join
Views
Simple view (Updatable view)
Complex view (Non-Updatable view)
SQL | Triggers
CTE in SQL
What is Visualization?
What is BI?
Why we need BI
What is Power BI?
Power BI Architecture
Installation of Power BI
Components of Power BI
Types of Data Loading
Import Mode
Direct Query Mode
Import vs Direct Query Mode
Composite Models
Most Commonly Used Data Sources
Excel /Text / CSV / MS Access / Web Link / PDF /SQL Server / Oracle / SSAS (Analysis Service) /SharePoint List / Online / Folder / Folder
TRANSFORMS
Remove Columns
First Row Header
Duplicate Columns
Split Columns
Remove Duplicate
Replace Value
Change Data Type
Group BY
Formatting data
Add Custom Columns
Invoke Function
Append Queries
Merge Queries
Combine Files(Folder)
Parameters
Other Query Features
Introduction to Data Modeling
Deployment Cycle
Data Model Engine
What is Data Model
Relationships in Power BI
One to One / One to Many / Many to Many
Tables and Relationship
Grouping / Binning
Drill Through Reports
What IF Parameter
Bidirectional filters
Overview
Best Practice
Visualization types
Custom visuals
Creating power BI Visuals
Bar Chart and Line Chart
Combining charts
Adding slicers for filters
Tabular data / Matrix
Cards / Multi Cards
Categorical data
Data Trends
Categorical and Trends Data Together (Combo)
Geographical Data and Maps
Filters
Report Level
Page Level
Visual Level
Bidirectional filters
Synonyms
Custom Colors, Color Picker
What is Power BI SERVICE?
Licensing (Free Vs Pro Vs Premium)
App workspace
What is Report Server
Installing SQL Server with Tabular Mode
Installing Visual Studio
Installing SSDT
Creating a new Tabular Model
Data Modelling in SSAS Tabular
Deploy the Model
Processing Tabular Model
Schedule Processing (SQL Server Agent & SSIS)
Power BI Desktop vs SSAS Tabular
Mobile Power BI Overview
Designing the reports and Dashboard for Mobile
Interacting with Mobile Power BI App
Introduction to DAX
Calculated Columns
Calculated Tables
Calculated Columns vs Measures
Evaluation Contexts (ROW & FILTER Contexts)
Aggregated Functions (SUM,MIN,MAX,AVG,COUNT)
Relate Functions (RELATED & RELATED TABLE)
Iterative Functions (SUMX, AVGX, COUNTX)
Variables (VAR)
Logical functions (IF, SWITCH)
Table Functions
FORMAT FUNCTION, FIND, SEARCH, SUBSTITUE, VALUE, CALCULATE,UNION,ROW,ADDCOLUMNS,SUMM ARIZE
Handling Blanks (ISBLANK,NOTISBLANK)
Rank Functions (RANKX)
Date Functions(DATEADD,DATEDIFF,TODAY Required Date Formats)
Calendar Functions (CALENDAR, CALENDAT AUTO)
Time Intelligence functions
SEMI ADDITIVE
Dynamic Measures, Dynamic Filters & Dynamic chart Axis
What is Business Intelligence (BI) ?
BI Process
What is KPI?
Visual Analysis
Data Visualization Tools
Tableau vs Power Bi
Why Tableau
Loading tableau
About Tableau
Tableau Products
Building Visualization
Mark Field
Color Palette
Clear – undo
Share – filters
Group – hierarchy
Sorting Data
Dashboard and share your work
Data Aggregations and calculations
Quick table calculations
Joins
Parameters
Analytics Pane