- Course type: Self-paced
- Available Lessons: 100
- Average Lesson Length: 8 min
- New lessons are still being added
Watch a preview:chapter 1 / lesson 1What is Business Intelligence? - Definition & Examples
Course SummaryThis engaging Analytics 102: Business Intelligence and Data Mining course includes a series of easy-to-follow lessons designed by experts. These resources are in a mobile-friendly format that makes it easy to review this topics for homework help or to prepare for an exam.
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- Comprehensive test covering all topics
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About This Course
In our Analytics 102: Business Intelligence and Data Mining course, we've provided short, accessible chapters and lessons designed to help you meet your goals. Whether you're looking to build your knowledge before a test or just want to learn more about analytics, this course has something for you. Take your time and work at your own pace as you review subjects such as data management for business intelligence, data warehousing and modeling, descriptive and predictive analytics and much more.
Along with each lesson, we've included a helpful multiple-choice quiz you can use to guide your study. At the end of each chapter, you'll find a comprehensive test you can use to check your knowledge before you move on. In order to help you study at your leisure, any mobile device or computer with an internet connection can be used to review these materials. Feel free to reach out to one of our experts in the Dashboard if you struggle with any of the concepts or have questions you'd like to go over.
|Introduction to Business Intelligence & Data Analysis||Explains data analysis and business intelligence, the processes used in data mining, and the tools used in data analytics|
|Business Intelligence Concepts||Outlines structured and unstructured data, business intelligence strategy, secondary data in marketing research, and the difference between competitive intelligence and business intelligence|
|Overview of Big Data||Covers the basics, concepts and uses of big data; the 4 V's of big data; and how data is used in business decisions|
|Data Management for Business Intelligence||Identifies database concepts and structures, specialized information systems, types of MIS reports. and group decision support systems (GDSS)|
|Data Mining Techniques & Applications||Examines the advantages and disadvantages of data mining, techniques for data mining, the bag of words approach, and the difference between big data and data mining|
|Data Warehousing & Business Intelligence||Details data warehouse administration, the purpose of data lakes, types and designs for data marts, and an gives overview of data consolidation|
|Data Warehousing & Business Intelligence||Discusses hierarchical databases, designing rational databases, data modeling techniques for business intelligence, and abstract data models|
|Data Analysis for Business Intelligence||Describes tools and reports used for business performance analysis, the difference between quantitative and qualitative analysis in business decisions, and using big data analytics to make business decisions|
|Predictive & Descriptive Analytics||Illustrates marketing analytics and metrics, methods for business forecasting, the impact of business decisions on stakeholders, and examples of categorical data|
|Data Visualization for Business Intelligence||Outlines different types of data visualization, the difference between data visualization and data analytics, trends in data visualization, and its importance in business|
|Challenges in Business Intelligence & Data Mining||Covers the impact of technology on privacy, database security management, big data and privacy as it relates to social media, and the security risks associated with big data|
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