Kick-start your career in the BI field with the Business Intelligence (BI) Essentials course that equips you with the fundamental skills and knowledge needed to work with data and BI tools effectively.

You will learn:

The concept of BI, the key components and challenges involved, and the career options in this field.
Data analytics and its significance in BI, including its role in extracting insights from data.
How to evaluate different business intelligence tools and technologies to assess the business context and requirements of a BI project.
How to develop actionable insights using appropriate tools and techniques for data gathering, wrangling, analyzing, mining, visualizing, and reporting.

Course Overview

This course offers an in-depth introduction to BI, covering its core concepts, components, and the advantages and challenges of deploying BI solutions. It also explores career paths and roles within the BI field, along with the essential skills and qualifications needed.

Explore the data ecosystem, the BI analytics landscape, data repositories, and the extract, transform, and load (ETL) process for managing data. Additionally, you will be introduced to the role of statistical analysis in mining and visualizing data to identify patterns and trends and how to weave a compelling story with data.

The course provides practical experience through hands-on activities and a final project that enables you to apply your knowledge in real-world scenarios.

Course Syllabus

Module 0 - Introduction

· Video: Course Introduction

· Reading: General Information

· Reading: Learning Objectives and Syllabus

· Reading: Grading Scheme

· Video: Overview of IBM BI Analyst Professional Certificate

· Video: Expert Viewpoints: BI Career Path

· Reading: Helpful Tips for Course Completion

Module 1: Introduction to Business Intelligence (BI)

· Reading: Module 1 Introduction and learning objectives

· Video: What Is Business Intelligence?

· Video: BI, Data Analytics, Data Science, and Data Engineering: A Comparison

· Video: Benefits of Business Intelligence

· Video: Expert Viewpoints: Skills of a BI Analyst

· Lab: Storyline Activity: Advantages of BI

· Video: Expert Viewpoints: What Is BI and Why Is It Exciting?

· Video: Data Professional Roles

· Reading: Differences Between BI Analyst, Data Analyst, Data Engineer, and Data Scientist Roles

· Video: Roles in Business Intelligence

· Video: Career Opportunities and Paths in BI Analytics

· Video: A Day in the Life of a BI Analyst

· Lab: Storyline Activity: Journey of a BI Analyst

· Video: Expert Viewpoint: Key Tasks in a Day in the Life of a BI Analyst

· Reading: Summary and Highlights Module 1: Introduction to Business Intelligence (BI)

· Practice Quiz: Module 1: Introduction to Business Intelligence (BI)

· Graded Quiz: Module 1: Introduction to Business Intelligence (BI)

· Reading: Module 1 Glossary: Introduction to Business Intelligence (BI)

· Discussion Prompt: Breaking the Ice

Module 2: The Data Ecosystem

· Reading: Module 2 Introduction and learning objectives

· Video: Overview of the Data Analyst Ecosystem

· Video: Types of Data

· Video: Understanding Different Types of File Formats

· Video: Sources of Data

· Video: Viewpoints: Working with Varied Data Sources and Types

· Video: Languages for Data Professionals

· Reading: Metadata and Metadata Management

· Video: Overview of Data Repositories

· Video: RDBMS

· Video: NoSQL

· Video: Data Marts, Data Lakes, ETL, and Data Pipelines

· Video: (Optional): Data Lakehouses Explained

· Video: Introduction to Data Modeling

· Video: Foundations of Big Data

· Video: Big Data Processing Tools: Hadoop, HDFS, Hive, and Spark

· Video: Viewpoints: Considerations for Choice of Data Repository

· Video: Data Integration Platforms

· Video: Viewpoints: Tools, Databases, and Data Repositories of Choice

· Reading: Summary and Highlights Module 2: The Data Ecosystem

· Practice Quiz: Module 2: The Data Ecosystem

· Graded Quiz: Module 2: The Data Ecosystem

· Reading: Module 2 Glossary: The Data Ecosystem

Module 3: BI Analytics Landscape

· Reading: Module 3 Introduction and learning objectives

· Video: Key Performance Indicators (KPIs) and Metrics

· Lab: Storyline Activity: Identifying Suitable Key Performance Indicators (KPIs)

· Video: Descriptive Analytics

· Video: Diagnostic Analytics

· Video: Predictive Analytics

· Video: Prescriptive Analytics

· Reading: Differences between the four types of analytics

· Lab: Storyline Activity: Differentiate between descriptive, diagnostic, predictive, and prescriptive analytics

· Video: Challenges in Implementing Business Intelligence

· Video: Expert Viewpoints: Types of Analytics and Metrics

· Video: Key Components of BI

· Lab: Storyline Activity: Explore Components of BI

· Reading: Overview of BI Ecosystem

· Video: Categories of BI Tools

· Reading: (Optional) Some Dashboard and Visualization Tools

· Video: Understanding Business Context and Requirements for BI Projects

· Video: Privacy and Security Issues Regulatory Compliance

· Video: Expert Viewpoints: Responsible Business Intelligence Practices

· Reading: Summary and Highlights Module 3: BI Analytics Landscape

· Practice Quiz: Module 3: BI Analytics Landscape

· Graded Quiz: Module 3: BI Analytics Landscape

· Reading: Module 3 Glossary: BI Analytics Landscape

Module 4: Gathering and Wrangling Data

· Reading: Module 4 Introduction and learning objectives

· Reading: Introduction to the Business Intelligence Process

· Video: Identifying Data for Analysis

· Video: Data Sources

· Video: How to Gather and Import Data

· Video: What is Data Wrangling?

· Video: Tools for Data Wrangling

· Video: Data Cleaning

· Video: Viewpoints: Data Preparation and Reliability

· Reading: Summary and Highlights Module 4: Gathering and Wrangling Data

· Practice Quiz: Module 4: Gathering and Wrangling Data

· Graded Quiz: Module 4: Gathering and Wrangling Data

· Reading: Module 4 Glossary: Gathering and Wrangling Data

Module 5: Mining and Visualizing Data and Communicating Results

· Reading: Module 5 Introduction and learning objectives

· Video: Overview of Statistical Analysis

· Video: What is Data Mining?

· Video: Tools for Data Mining

· Video: Overview of Communicating and Sharing Data Analysis Findings

· Video: Viewpoints: Storytelling in Data Analysis

· Video: Introduction to Data Visualization

· Video: Introduction to Visualization and Dashboarding Software

· Video: Viewpoints: Visualization Tools

· Video: Data Visualization Techniques

· Reading: Effective Communication of BI Insights

· Reading: Summary and Highlights Module 5: Mining and Visualizing Data and Communicating Results

· Discussion Prompt: Visualizing Data and Communicating Findings

· Practice Quiz: Module 5: Mining and Visualizing Data and Communicating Results

· Graded Quiz: Module 5: Mining and Visualizing Data and Communicating Results

· Reading: Module 5 Glossary: Mining and Visualizing Data and Communicating Results

Module 6: Applying BI Techniques and Final Project

· Reading: Module 6 Introduction and learning objectives

· Video: Expert Viewpoints: Advice for Aspiring BI Analysts

· Reading: Applying BI Techniques and Tools

· Video: Developing a Comprehensive BI Project

· Reading: Case Study: Developing a BI Project

· Video: Expert Viewpoints: Applying BI Techniques

· Lab: Exploring Job Listings for BI Professionals

· Video: Expert Viewpoints: Showcasing Acquired Skills and Knowledge

· Reading: Summary and Highlights Module 6: Applying BI Techniques and Final Project

· Reading: Final Project: Scenario

· Final Project Assignment

· Reading: Course Glossary: Business Intelligence (BI) Essentials

· Reading: Instructions for the Final Exam

· Final Exam: Business Intelligence (BI) Essentials

· Reading: Re-take exam

Recommended Skills Prior to Taking this Course

This specialized program is tailored for individuals interested in pursuing a career as a BI analyst, and no prior data analytics experience or degree is required. Basic computer skills and familiarity with data handling are beneficial but not mandatory.

Business Intelligence (BI) Fundamentals

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