Fundamentals of Business Intelligence Online Course (5 credits)


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Business intelligence (BI) comprises various analysis-based methods to extract knowledge and actionable insights from a business that can help identify new opportunities and make informed business decisions. It seeks to extract information from historical data and apply it to future solutions in order to increase enterprises' profit. This process provides practical knowledge as a consultant to managers, business owners, and all business decision-makers. Businesses leverage BI to reduce their costs and risks and improve their communications with customers. BI tools and methodologies lie at the intersection of business analytics, data mining, statistical analysis, data visualization, data infrastructure, and other practices to enable businesses to make effective data-driven decisions.

TechClass Fundamental of Business Intelligence online course will introduce you to the concept of BI and its importance while you will be gradually acquainted with the essential BI topics and concepts as your very first step in your journey to the BI world. By the end of this course, you will learn to think outside the box using BI and aptly state your BI-based attitude toward business problems using the appropriate methods discussed in the course. Moreover, you will get familiar with the BI tools you need to learn to land an exceptional career in the business.

Learning outcomes

  • Learn the basic concepts of business intelligence
  • Get familiar with stages of business intelligence
  • Learn the importance of business intelligence in the modern data-driven world
  • Get familiar with the primary concepts of statistics like population, sample, mean, median, mode
  • Get acquainted with some BI tools like Excel and Power BI
  • Get familiar with some databases like MySQL and SQL server
  • Get familiar with some storage tools like DynamoDB and Mongo DB.
  • Get familiar with the importance of visualization
  • Learn about data science-related topics
  • Get familiar with the data science pipeline

Table of contents

Chapter 1: Beginning with This Course

  • 1.1. Our Approach in This Course
  • 1.2. About TechClass Digital Marketing Department
  • 1.3. Your Expectations, Goals, and Knowledge

Chapter 2: Introduction to Online Advertising

  • 2.1. What Is Online Advertising?
  • 2.2. Online Advertising Models
  • 2.3. Types of Online Advertising
  • 2.4. Contextual Advertising
  • 2.5. Targeted Advertising
  • 2.6. Banner or Display Advertising
  • 2.7. Mobile Advertising
  • 2.8. Push Notifications

Chapter 3: Search Engine Marketing

  • 3.1. What is Search Engine Marketing?
  • 3.2. Search Engine Advertising
  • 3.3. SEA vs. SEO
  • 3.4. What Is Google Ads?
  • 3.5. How Does Google Ads Work?

Chapter 4: Creating Your First Google Ad

  • 4.1. Understanding The Google Ads Account Hierarchy
  • 4.2. Creating First Google Ads Account
  • 4.3. Create Your First Campaign
  • 4.4. Creating Your First Ad
  • 4.5. Selecting Keywords For Your Ad
  • 4.6. Location Targeting
  • 4.7. Setting Budget

Chapter 5: Launching A Campaign in Expert Mode

  • 5.1. Google Ads in Expert Mode
  • 5.2. Campaign Goal
  • 5.3. Campaign Types
  • 5.4. Google Search Ads Campaigns
  • 5.5. Google Shopping Campaigns
  • 5.6. Advertising On The Display Network
  • 5.7. Video Campaigns
  • 5.8. Advertising Campaigns For Mobile Applications
  • 5.9. Smart Ad Campaigns

Chapter 6: Practical Example of Google Ad

  • 6.1.. Define Your Goals
  • 6.2. Ads' General Settings
  • 6.3. Targeting and Audience Segments
  • 6.4. Budget and Bidding
  • 6.5. The Ad Auction
  • 6.6. Set Up the Ad Group
  • 6.7. Keyword Match Types
  • 6.8. Negative Keywords Match Type
  • 6.9. Create Your Ad

Chapter 7: Final Tasks

  • 7.1. Final Project
  • 7.2. Self-study Essay
  • 7.3. Congrats! You did it!

Chapter 1: Beginning with This Course

  • 1.1. Our Approach in This Course
  • 1.2. About TechClass AI Department
  • 1.3. Your Expectations, Goals, and Knowledge

Chapter 2: Business Intelligence (BI)

  • 2.1. What is Business Intelligence?
  • 2.2. The History of BI
  • 2.3. Why is BI Important to Business?
  • 2.4. BI Key Success Factors
  • 2.5. Data Collection

Chapter 3: How to Prepare for Business Intelligence?

  • 3.1. How to Become an Expert in BI
  • 3.2. The Business Rules Approach
  • 3.3. Analytical skills
  • 3.4. Basic Statistical Knowledge
  • 3.5. An Overview of Microsoft Excel
  • 3.6. Quiz

Chapter 4: Toward Business Intelligence

  • 4.1. The BI Process
  • 4.2. Data Warehouse
  • 4.3. Data Integration
  • 4.4. Data Mining
  • 4.5. Metadata
  • 4.6. Parallelism
  • 4.7. Data Enhancement
  • 4.8. Quiz

Chapter 7: Database in Business Intelligence

  • 5.1. Data Models
  • 5.2. Database Sources
  • 5.3. Extract, Transform, Load (ETL)
  • 5.4. Online Analytical Processing (OLAP)
  • 5.5. SQL Server for BI
  • 5.6. MySQL for BI
  • 5.7. Query and Reporting
  • 5.8. Quiz

Chapter 6: Applied Business Intelligence

  • 6.1. BI Environment
  • 6.2. The Best BI Tools
  • 6.3. Data Preparation
  • 6.4. Data Visualization
  • 6.5. Microsoft Power BI

Chapter 7: Improve BI Performance by Introducing Data Science

  • 7.1. Data Science and Business Intelligence
  • 7.2. Structured Data and Unstructured Data
  • 7.3. Data Science Modules in Python
  • 7.4. Introduction to Machine Learning
  • 7.5. Quiz

Chapter 8: Data Science Pipeline

  • 8.1. Problem Statement
  • 8.2. Exploratory Data Analysis (EDA)
  • 8.3. Data Collection and Wrangling
  • 8.4. Data Cleaning and Profiling
  • 8.5. Split Data to Train and Test
  • 8.6. Feature Engineering
  • 8.7. Modelling
  • 8.8. Evaluate
  • 8.9. Communication
  • 8.10. Quiz

Chapter 9: Final Tasks

  • 9.1. Final Project
  • 9.2. Self-study Essay
  • 9.3. Congrats! You did it!

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