- Course type: Self-paced
- Available Lessons: 103
- Average Lesson Length: 8 min
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Watch a preview:chapter 1 / lesson 1What is Business Intelligence? - Definition & Examples
Course SummaryFor an overview of business intelligence fundamentals, take Business Intelligence 101. This self-paced online course offers you a quick way to learn and review the basics of business intelligence for academic, personal or professional uses, such as test preparation or skill development.
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Course Practice TestCheck your knowledge of this course with a 50-question practice test.
- Comprehensive test covering all topics
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About This Course
In this course, you'll find a collection of simple and engaging lessons that discuss the purpose and applications of business intelligence (BI). As you progress through the course, you'll become familiar with BI data collection, organization, warehousing, mining, modeling and analysis methods. Our expert instructors also discuss data challenges in BI, as well as important concepts pertaining to big data.
The course can be a helpful test preparation resource for business students, and it can also help working professionals develop a high-level understanding of business intelligence tools/techniques. In addition to the lessons, the course offers short quizzes that reinforce important BI terms and concepts. The course is accessible at any time that fits your schedule, and you can study on any computer or mobile device.
|Introduction to Business Intelligence||Define business intelligence; discuss the benefits of business intelligence; explain how business intelligence differs from competitive intelligence and knowledge management.|
|Business Intelligence Data Overview||Explain what data is in the context of business intelligence; compare and contrast different types of data, such as primary data, quantitative data and structured data.|
|Big Data in Business Intelligence||Differentiate between data and big data; identify the core components of big data, as well as its applications, advantages and challenges.|
|Data Collection & Quality||Describe different data collection approaches; explain the importance of data quality and evaluate related issues.|
|Business Intelligence Data Organization||Explain the meaning of a database; discuss basic database management concepts; determine how databases can be used to support business decision making.|
|Data Warehousing for Business Intelligence||Identify the components of data warehouses; evaluate several issues that are associated with data warehousing.|
|Data Mining for Business Intelligence||Define the concept of data mining; compare a variety of basic data mining techniques; assess issues pertaining to data mining in business.|
|Data Modeling for Business Intelligence||Discuss the applications of data modeling in business intelligence; compare and contrast the different types of databases, including subject databases, SQL databases, relational databases and hierarchical databases.|
|Data Analysis & Applications||Describe various approaches to data analysis, including several statistical methodologies that are used to analyze business intelligence; differentiate between qualitative and quantitative analysis; assess big data analytics tools/techniques.|
|Descriptive & Predictive Analytics||Explain the purpose and methods of predictive analytics in business intelligence; compare different predictive analytics forms.|
|Web Analytics for Business Intelligence||Compare various forms of web analytics and explain their applications in business intelligence contexts; discuss the basics of SEO, PPC and social media marketing metrics.|
|Data Displays in Business Intelligence||Explain different data display approaches and assess their relative strengths and weaknesses; describe the ways in which data visualization applies to dashboards, business intelligence and data analysis; discuss various data visualization trends.|
|Data Challenges in Business Intelligence||Explain the ethical and legal challenges that businesses can face regarding the collection and management of data; assess big data security risks and privacy issues.|
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