What is Business Intelligence and Advanced Analytics?

Business Intelligence (BI) refers to the technologies, applications, and practices used to collect, integrate, analyze, and present business information. Advanced Analytics refers to the use of statistical, mathematical, and machine learning techniques to extract insights from data. This program covers both BI and Advanced Analytics topics.

What are the prerequisites for this program?

To enroll in this program, you should have basic knowledge of statistics, mathematics, and programming. Experience in using Microsoft Excel, SQL, and data visualization tools like Tableau or Power BI is recommended.

What kind of jobs can I get after completing this program?

This program prepares you for a variety of roles in the fields of business intelligence, data analysis, and data science. Some of the job titles that you can pursue after completing this program include Data Analyst, Business Intelligence Analyst, Data Scientist, Business Intelligence Developer, Data Engineer, and more.

What are the benefits of learning Business Intelligence and Advanced Analytics?

Learning Business Intelligence and Advanced Analytics can help you gain insights from data and make data-driven decisions that can improve business outcomes. This skillset is in high demand in today's job market, and learning it can open up new career opportunities for you.

Business Intelligence

Data Analytics and Business Intelligence Masters Program

Datavalley

Last Update November 13, 2024

21326 already enrolled

Free

Level

All Levels

Lectures

85 lectures

Subject

Business Intelligence

About This Course

Master the skills needed to excel in the field of Business Intelligence and Advanced Analytics with our comprehensive training program. You will gain an in-depth understanding of the latest tools and techniques used in the industry, and learn how to use them to extract valuable insights from data.

In this program, you will:

Learn the fundamentals of Business Intelligence, Microsoft’s powerful business analytics service, and how to create stunning reports and visualizations
Discover how to build relationships between data sources and group data for better insights
Learn how to perform advanced data analytics using SQL, Excel and Python
Learn python language and all the packages used for advanced Data analytics
Become an expert in Microsoft’s Power BI tools
Also, master the Tableau for powerful visualizations
Master advanced Business Intelligence techniques, such as using bookmarks, integrating with Azure, and data modeling
Customize your visualizations in Business Intelligence to suit your needs and the needs of your audien .
learn about the different Object Storage Services offered by AWS, identify when to use a specific service, how to store/transfer data using these services and optimize the storage cost.

Got questions?

Fill the form below and a Learning Advisor will get back to you.

Learn advanced data transformation techniques with Power Query, and how to optimize data models for better performance
Master DAX formulas and functions for data analysis in Business Intelligence , including advanced DAX techniques and data modeling with DAX
Learn how to build real-time projects and gain hands-on experience with the tools and techniques used in the industry

By the end of the course, you will have a solid understanding of the tools and techniques used in Business Intelligence and Advanced Analytics, and be well-prepared to pursue a career in this exciting field.

Business Intelligence Course Syllabus

Data Analytics ,Math and Stats Foundations

LIVE TRAINING

Learning objective: Develop a comprehensive understanding of business intelligence concepts and methodologies, with a focus on Power BI ,Excel , Tableau as a powerful data visualization and analysis tool. Gain hands-on experience in leveraging Power BI or Tableau to transform raw data into meaningful insights, enabling informed decision-making and driving business performance.

Week

1-2

Modules

Skills

Course Content

Introduction to Course

Introduction to Business Intelligence

Introduction to Data Analysis

Data Manipulation and Analysis
Data Visualization
Statistical Analysis
Machine Learning Fundamentals
Business Intelligence Tools and Techniques

Advanced Analytics and Big Data
Data Governance and Ethics

Excel for Data Analysis

LIVE TRAINING

Learning objective: Acquire proficiency in utilizing Excel’s powerful tools and functions for data manipulation, visualization, and interpretation. Through hands-on practice, learners will gain the ability to analyze data, discover patterns, make informed decisions, and present insights effectively using Excel.

Week

1-2

Modules

Skills

Course Content

Introduction to Data Analysis and Excel:

Overview of data analysis and its importance in business intelligence.
Introduction to Microsoft Excel and its features for data analysis.
Understanding data formats, data types, and basic Excel functions.

Data Import and Cleaning:

Importing data from different sources into Excel.
Cleaning and transforming data for analysis.
Dealing with missing values, duplicates, and outliers.

Data Manipulation and Formulas:

Using formulas and functions in Excel for data manipulation.
Sorting, filtering, and conditional formatting of data.
Working with logical functions, text functions, and date functions.

Data Visualization:

Creating charts and graphs to visually represent data.
Customizing and formatting charts to enhance their effectiveness.
Using PivotTables and Pivot Charts for dynamic data analysis.
Advanced Data Analysis Techniques:
Performing statistical analysis using Excel.
Regression analysis and forecasting.
What-if analysis and scenario planning.

Data Integration and External Data Sources:

Combining data from multiple sources into Excel.
Working with external databases and SQL queries.
Connecting Excel to external data sources like CRM systems or web APIs.

Excel Add-Ins and Power Tools:

Introduction to Excel add-ins for data analysis.
Using Power Query for data transformation and cleansing.
Utilizing Power Pivot for advanced data modeling and analysis.

Data Presentation and Reporting:

Creating interactive dashboards and reports in Excel.
Using slicers, filters, and dynamic charts to build interactive interfaces.
Sharing and distributing data analysis results.

Automation and Macros:

Introduction to Excel macros and VBA (Visual Basic for Applications).
Automating repetitive tasks and data processing.
Building custom functions and user interfaces.

Case Studies and Real-world Applications:

Applying data analysis concepts to real-world business scenarios.
Analyzing sales data, customer behavior, and financial data.
Solving business problems using Excel and data analysis techniques.

SQL for Data Analysis

LIVE TRAINING

Learning objective: Acquire a solid foundation in Microsoft SQL Server and database management, including data modeling, querying, and administration. Develop practical skills in designing and implementing efficient databases, optimizing query performance, and ensuring data integrity and security within a Microsoft SQL Server environment.

Week

2-3

Modules

Skills

Course Content

Level 1: Introduction to SQL

Introduction to Databases and SQL
Basic SQL Queries
Data Manipulation with SQL

Level 2: Advanced SQL Queries

Working with Multiple Tables
Aggregating Data
Working with Data Types and Functions

Level 3: Database Design and Optimization

Creating and Modifying Database Structure
Data Integrity and Constraints
Advanced Query Optimization

Level 4: SQL for Data Analysis

Window Functions
Common Table Expressions (CTEs)
Advanced Data Analysis Techniques

Level 5: SQL for Administration and Security

User Management and Security
Backup and Recovery
Performance Monitoring and Tuning

Level 6: Advanced Topics

Transactions and Concurrency Control
Stored Procedures and Functions

Advanced Data Analysis with Python

LIVE TRAINING

Learning objective: Comprehensive introduction to Python programming, catering to beginners. It covers core concepts like data types, variables, and control structures, enabling learners to write basic Python scripts. The course aims to build a strong foundation for further exploration and application of Python in various domain.

Week

2-4

Modules

Skills

Course Content

Python Essentials

Introduction to Python and IDEs
Python Basics
Object Oriented Programming
Hands-on Sessions And Assignments for Practice

Advanced Data analysis with Python

Data Manipulation and Analysis with Pandas
Data Visualization with Matplotlib and Seaborn
Exploratory Data Analysis (EDA)
Data Transformation and Feature Engineering
Statistical Analysis and Hypothesis Testing
Machine Learning for Business Intelligence
Time Series Analysis
SQL Integration and Database Connectivity
Business Intelligence Dashboards and Reporting
Data Integration and API Integration

Power BI Certification Program

LIVE TRAINING

Learning objective: The learning objectives for the Microsoft Power course are to equip participants with the skills to create powerful data analyses, build interactive reports and dashboards, automate tasks with Power Automate, and model data with Power BI. Participants will gain proficiency in leveraging Microsoft Power to enhance data-driven decision-making and productivity.

Week

3-4

Modules

Skills

Course Content

Introduction to Power BI:

What is Power BI?
Key features and benefits
Power BI ecosystem and components
Getting started with Power BI Desktop
Installation of Power BI for Desktop
Understanding the Power BI interface
Three views of Power BI
Four Main Pillars of Power Bi ( In Detailed )
Arctecture of Power BI
The components of Power BI

Connecting to Data Sources:

Importing data from Excel, CSV, databases and All other data sources
Connecting to cloud services (e.g., Azure, SharePoint)
Understanding DirectQuery and Live Connection options

Data Transformation and Modeling:

Data Transformation Techniques ( All Functionalities )
Two Types Of Tables in Power BI ( Dimensions & fact )
Transforming and cleaning data using Power Query Editor
Data modeling concepts (tables, relationships, measures)
Data modeling and shaping using Power Query Editor
Creating calculated columns and measures
First Approch of date Table creation
Types of Data Model
Introduction to DAX (Data Analysis Expressions) language

Data Visualizations and Interactions: ( Basic to Advanced )

Creating visualizations
Formatting and customizing visuals ( all functionalities & dynamic interactions )
Adding interactive features (filters, slicers, drill-through)
Creating calculated tables and hierarchies
Conditional formatting using tables & other KPI’s
Grouping DAX Measures and Data Tables
Phase Level Filters , Visual Level Filters , Report Level Filters , Tool Tips
Tree Maps , Water fall vision , funnels and Ribbon chart
Visual Tool Tips , Bookmarks , page Navigation ,
Synch slicers ,Show/Hide Options

Advanced Data Analysis:

Implementing advanced DAX functions
Working with time intelligence functions
Aggregators, iterators, Time Intelligence & Other important functions
Important AI visuals ( Cortana, Decomposition tree & Key influencers)
Embedding R and Python scripts in a Power BI report
How to connect Power BI with a SQL server & other databases ( data sources)
Understanding the importance of updated Key plugins in Visual pane of Power BI
Implementing calculations for ranking, forecasting, and segmentation

Advanced Visualizations:

Custom visuals and marketplace options(How to create a Power BI dashboard)
Using bookmarks and report navigation techniques
Enhancing visualizations with themes and conditional formatting
Power BI mobile app and responsive design considerations

Power BI Service and Collaboration:

Publishing reports to Power BI service
How to generate quick insights , user metrics report
How to share a Power BI report with others (top level management & end users)
How to pin a visual
How to embed a Power BI report / dashboard
Sharing reports and dashboards with others
Collaborating with colleagues (workspaces, sharing settings)
Creating and configuring data gateways

Power BI Administration and Security:

Power BI security architecture and best practices
Row-level security (RLS) implementation
Managing workspaces, apps, and datasets
Administering Power BI tenant settings

Data Refresh and Scheduled Refresh:

Configuring data refresh options
Troubleshooting refresh issues
Working with large datasets and optimizing performance
Power BI report performance optimization

Advanced Topics and Integrations:

Power BI and Excel integration
Power BI Embedded for application developers
Power Automate (formerly Microsoft Flow) integration
Power BI REST API and PowerShell automation

Tableau Certification Program

LIVE TRAINING

Learning objective: Learn Tableau with an objective-driven course! Master data visualization, dashboard creation, and interactive analytics. Acquire skills in data connection, blending, and presentation. Explore real-world projects and gain hands-on experience. Unlock insights and become proficient in Tableau’s powerful tools for data analysis and business intelligence.

Week

3-4

Modules

Skills

Course Content

Introduction to Tableau

Overview of Tableau and its role in data visualization.
Understanding the Tableau interface and workflow.
Connecting to data sources and importing data into Tableau.

Data Exploration and Visualization

Exploring data using Tableau’s data pane and visualizations.
Creating basic charts and graphs such as bar charts, line charts, and scatter plots.
Applying filters and sorting data in Tableau.

Advanced Visualization Techniques

Creating interactive dashboards and storyboards.
Implementing advanced chart types like heat maps, tree maps, and dual-axis charts.
Using parameters and actions to enhance interactivity.

Data Preparation and Transformation

Cleaning and transforming data in Tableau.
Working with calculated fields and table calculations.
Joining and blending data from multiple sources.

Advanced Analytics in Tableau

Applying statistical analysis techniques in Tableau.
Creating forecasts and trend lines.
Using clustering and advanced analytics features.

Geographic Mapping and Spatial Analysis

Visualizing data on maps using Tableau’s mapping capabilities.
Working with geographic data and geocoding.
Performing spatial analysis and creating custom territories.

Data Storytelling and Presentation

Building compelling data stories using Tableau.
Designing effective visual narratives and annotations.
Presenting data insights and findings to stakeholders.

Advanced Tableau Features and Integration

Utilizing advanced features like sets, groups, and hierarchies.
Implementing calculations with level of detail (LOD) expressions.
Integrating Tableau with other tools and platforms.

Tableau Server and Collaboration

Publishing and sharing dashboards on Tableau Server.
Configuring permissions and access controls.
Collaborating with team members using Tableau’s collaboration features.

Case Studies and Real-world Applications

Applying Tableau to real-world business scenarios and datasets.
Analyzing sales data, marketing campaigns, and customer behavior.
Solving business problems using Tableau’s visual analytics capabilities.

AWS Cloud services for Data Analysis

LIVE TRAINING

Week

3-4

Modules

Skills

Course Content

Introduction to AWS Cloud Computing
AWS Fundamentals for Data Analysis
Data Storage and Data Movement
Data Ingestion
Data Warehousing
Data Processing
Serverless Data Processing
Data Analysis and Visualization
Advanced Analytics
Real-time Analytics
Monitoring and Performance Optimization
Data Governance and Security
Big Data and AI Solutions
Building End-to-End Data Solutions

Group Project

LIVE TRAINING

Learning objective: In this group project, students will collaboratively analyze diverse datasets and apply advanced business intelligence techniques. The objective is to extract valuable insights, generate data-driven recommendations, and design comprehensive visualizations for informed decision-making. Through teamwork, they will enhance their data analysis and BI skills while tackling real-world challenges.

Week

2-3

Tools Covered

Job market overview

Ready to become a BI Developer? With an average salary of $91,153 per year, this role is financially rewarding and intellectually stimulating. As a BI Developer, you will be responsible for designing and developing data models, building reports and dashboards to help organizations make data-driven decisions.

Now, What are you waiting for? Our training program is designed to help you master the skills needed to become a successful BI Developer. Enroll in our training program today and take the first step towards a rewarding career in Business Intelligence. Start your success story with us!

What you will learn

The objective of a Business Intelligence and Advanced Analytics Masters Program is to equip learners with the necessary skills to gather, analyze, and interpret complex data, and communicate insights to stakeholders effectively. Upon completion of the program, learners will have a strong foundation in data analysis, data visualization, and reporting, and be proficient in using various business intelligence tools and technologies. Specifically, learners can expect to learn:

Advanced data modeling and querying techniques in tools like Power BI , Excel and Tableau

Analyzing and interpreting data to extract valuable insights and make data-driven decisions

Creating effective reports and dashboards for different audiences

Collaborating and sharing insights with stakeholders using business intelligence tools

Applying structured approaches to requirement gathering and project management

Understanding the fundamentals of functional system analysis

Troubleshooting project issues and finding solutions to problems

Overall, learners will gain expertise in the use of business intelligence and advanced analytics tools and technologies, and be able to leverage data to make informed business decisions.

Course Format

Live classes
Hands-on trainings
Mini-projects for every module
Recorded sessions (available for revising)
Collaborative projects with team mates in real-world projects
Demonstrations
Interactive activities: including labs, quizzes, scenario walk-throughs

What this course includes

3-4Weeks of live classes
Collaborative projects
Slide decks, Code snippets
Resume preparation from the 2nd week of course commencement
1:1 career/interview preparation
Soft skill training
On-call project support for up to 3 months
Certificate of completion
Unlimited free access to our exam engines

Our students work at

Prerequisites

Basic programming knowledge in SQL, Python.
Working knowledge with Excel
Basics of statistics/mathematics

Why Take Course With Us

Project-Ready, Not Just Job-Ready!

By the time you complete our program, you will be ready to hit the ground running and execute projects with confidence.

Authentic Data For Genuine Hands-On Experience

Our curated datasets sourced from various industries, enable you to develop skills in realistic contexts, tackling challenges in your professional journey.

Personalized Career Preparation

We prepare your entire career, not just your resume. Our personalized guidance helps you excel in interviews and acquire essential expertise for your desired role.

Multiple Experts For Each Course

Multiple experts teach various modules to provide you diverse understanding of the subject matter, and to benefit you with the insights and industrial experiences.

On-Call Project Assistance After Landing Your Dream Job

Get up to 3 months of on-call project assistance from our experts to help you excel in your new role and tackle challenges with confidence.

A Vibrant and Active Community

Get connected with a thriving community of professionals who connect and collaborate through channels like Discord. We regularly host online meet-ups and activities to foster knowledge sharing and networking opportunities.

FAQs

Course Completion Certification

Upfront Payment

27% off

Pay upfront and save 27% on tuition fee

1299 GBP

Monthly Payment

20% off

Pay monthly and save 20% on tuition fee

INR 10,000
Total up to 60,000

Scholarship

67% off

Avail upto 67% Scholarship

Learning Objectives

Advanced data modeling and querying techniques in tools like Power BI and Excel

Analyzing and interpreting data to extract valuable insights and make data-driven decisions

Creating effective reports and dashboards for different audiences

Collaborating and sharing insights with stakeholders using business intelligence tools

Applying structured approaches to requirement gathering and project management

Understanding the fundamentals of functional system analysis

Troubleshooting project issues and finding solutions to problems

Target Audience

Computer Science or IT Students or other graduates with passion to get into IT
Data Warehouse, Database, SQL, ETL developers who want to transition to Data Engineering roles

Data Analytics and Business Intelligence Masters Program

About This Course

Got questions?

Business Intelligence Course Syllabus

Data Analytics ,Math and Stats Foundations

Course Content

Excel for Data Analysis

Course Content

SQL for Data Analysis

Course Content

Advanced Data Analysis with Python

Course Content

Power BI Certification Program

Course Content

Tableau Certification Program

Course Content

AWS Cloud services for Data Analysis

Course Content

Group Project

Tools Covered

Job market overview

What you will learn

Course Format

What this course includes

Our students work at

Prerequisites

Why Take Course With Us

FAQs

Course Completion Certification

Upfront Payment

Monthly Payment

Scholarship

Learning Objectives

Target Audience

Managing Microsoft SQL Server and Databases

Introduction to SQL Server and configuration

Mastering SQL Fundamentals

Building Business Intelligence and Data Science Solutions

Building Dynamic Reports with Power BI

Introduction to Power BI

Getting Started with Power BI

Data Preparation and Modeling

Power BI Reporting

Power BI Job Roles

Power BI Certification

Designing Effective Reports: Foundations and Best Practices

Setting up Power BI Desktop

Data Sources and Visual Types

Creating and Customizing Visuals

Sharing and Exporting Reports

Power BI Ecosystem and Architecture

Creating Visual Relationships and Grouping Data in Power BI

Introduction to Slicers

Customizing Slicers

Advanced Slicer Techniques

Binning and Grouping Data

Organizing and Selecting Data for Power BI Reports

Introduction to Filters

Creating and Customizing Filters

Working with Drill-Downs

Using Drill-Thru Filters

Advanced Filter Techniques

Advanced Power BI Techniques: Bookmarks, Azure Integration, and Data Modeling

Data Import and Querying

Data Modeling in Power BI

Drill-Through Filters and Page Navigation

Using Bookmarks in Power BI

Azure Database Access and Deployment

Web and Mobile View in Power BI

Customizing Visualizations for Professional Reports in Power BI

Data Visualization Techniques for Effective Communication

Enhancing Data Visualization with Advanced Charting Techniques

Transforming and Cleaning Data with Power Query in Power BI

Mastering Power Query Fundamentals for Efficient Data Transformations

Exploring Advanced Power Query Techniques for Complex ETL Operations

Advanced Data Transformation with Power Query in Power BI

Data Cleaning with Power Query

Advanced Data Transformations with Power Query

PIVOT and UNPIVOT Transformations

Date and Time Transformations