Know Data Analytics, Data Mining & Business Intelligence
Know Data Analytics, Data Mining & Business Intelligence, available at $29.99, has an average rating of 4.2, with 35 lectures, 2 quizzes, based on 44 reviews, and has 903 subscribers.
You will learn about You will gain an understanding of the key concepts, tools, and processes in data analytics and business intelligence. Understand a range of analytical techniques including descriptive, diagnostic, predictive, & prescriptive analytics, & understand their l business applications Learn how companies use time series analysis, sensitivity analysis, and simulation models help make informed decisions and predictions based on historical data. Learn how companies effectively visualize data and communicate findings and insights in a clear and impactful manner, using various tools and best practices. This course is ideal for individuals who are This course is of interest to those seeking a professional development credits. It is particularly useful for This course is of interest to those seeking a professional development credits.
Enroll now: Know Data Analytics, Data Mining & Business Intelligence
Summary
Title: Know Data Analytics, Data Mining & Business Intelligence
Price: $29.99
Average Rating: 4.2
Number of Lectures: 35
Number of Quizzes: 2
Number of Published Lectures: 35
Number of Published Quizzes: 2
Number of Curriculum Items: 39
Number of Published Curriculum Objects: 39
Original Price: $29.99
Quality Status: approved
Status: Live
What You Will Learn
- You will gain an understanding of the key concepts, tools, and processes in data analytics and business intelligence.
- Understand a range of analytical techniques including descriptive, diagnostic, predictive, & prescriptive analytics, & understand their l business applications
- Learn how companies use time series analysis, sensitivity analysis, and simulation models help make informed decisions and predictions based on historical data.
- Learn how companies effectively visualize data and communicate findings and insights in a clear and impactful manner, using various tools and best practices.
Who Should Attend
- This course is of interest to those seeking a professional development credits.
Target Audiences
- This course is of interest to those seeking a professional development credits.
This course is constructed using the Learning Outcomes to be tested in the Certified Management Accounting Part 1 Exam – specifically Section F4 Data Analysis. The course also serves to provide you with a Professional Development Certificate upon completion.
In the digital age, the ability to analyze and interpret data has become a crucial skill for success in the business world. This comprehensive course, “Data Analytics and Business Intelligence,” is specifically designed to equip professionals, students, and business leaders with the expertise needed to navigate the data-driven landscape effectively. This course delves into the realms of data analytics, data mining, and BI, offering a blend of theoretical knowledge and practical application.
Students will learn the essentials of data analytics, starting with an introduction to its importance and key concepts, and progressing to more advanced topics such as big data, data mining, and various analytical models. The course is meticulously structured into modules, each focused on a vital aspect of data analytics and BI.
This course begins by explaining the complexities of big data, exploring the four Vs (volume, velocity, variety, and veracity), and delving into the opportunities and challenges presented by this data revolution. Participants will gain a deep understanding of how structured, semi-structured, and unstructured data are leveraged by businesses to create value.
Through a combination of theoretical foundations and hands-on exercises, learners will progress from data to information to knowledge to insight to action. They will learn data management practices, recognize data as a strategic asset, and develop competencies in data governance and quality assurance.
Data mining, a pivotal component of BI, will be thoroughly explained, and participants will grasp the challenges, iterative nature, and artistic-science blend that characterize data mining. They will also discover how query tools like Structured Query Language (SQL) are used for efficient data retrieval.
Predictive analytics will be another focal point, with participants learning various analytic models such as clustering, classification, and regression. They will develop the capability to analyze data, reveal patterns, and provide actionable insights.
Time series analysis, sensitivity analysis, and simulation models will be demystified, empowering learners to make accurate predictions and sound decisions based on historical data.
Course Curriculum
Chapter 1: Introduction to this course
Lecture 1: Introduction
Lecture 2: Overview of course content
Lecture 3: Creating Your Profession Development Portfolio
Chapter 2: Module 1. Introduction to Data Analytics and Business Intelligence
Lecture 1: Introduction to Data Analytics and Business Intelligence
Lecture 2: Importance in the modern business environment
Lecture 3: Key terms and concepts
Chapter 3: Module 2: Introduction to Big Data and Data Types
Lecture 1: Defining Big data and the four V's
Lecture 2: Opportunities and Challenges
Lecture 3: Structured, semi-structured, and unstructured data
Lecture 4: Case studies of Big Data applications
Lecture 5: Real-world examples and case studies
Chapter 4: Module 3: From Data to Action – The DIKW Pyramid
Lecture 1: Data, Information, Knowledge. Wisdom and action
Lecture 2: Case studies illustrating the DIKW Pyramid in action
Lecture 3: Progression
Chapter 5: Module 4 Business Intelligence (BI)
Lecture 1: Definition and components of BI
Lecture 2: BI tools and applications in business
Lecture 3: Hands-on BI tool demonstrations
Chapter 6: Module 5 – Data Mining
Lecture 1: Definition and process of data mining
Lecture 2: Challenges and iterative nature of data mining
Lecture 3: Practical applications in various industries
Chapter 7: Module 6 – SQL and Query Tools
Lecture 1: Basics of SQL
Lecture 2: Using SQL for data retrieval and management
Lecture 3: Practical exercises
Chapter 8: Module 7 Overview of Analytical Types
Lecture 1: Overview of descriptive, diagnostic, predictive, and prescriptive analytics
Lecture 2: Application in business scenarios
Chapter 9: Module 8 -How these tools are Used in the retail Industry
Lecture 1: Amazon
Lecture 2: Walmart
Chapter 10: Module 9 – How these tools are Used in Social Media
Lecture 1: Google
Lecture 2: Facebook
Lecture 3: Tic Tok
Chapter 11: Module 10 – How these tools are used in Manufacturing
Lecture 1: General Electric
Lecture 2: Ikea
Chapter 12: Section 11 – How these tools are used in Fintech
Lecture 1: Paypal
Lecture 2: Kabbage
Chapter 13: Conclusion and Course Certificate
Lecture 1: Conclusion
Instructors
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Dr. John Daniel Mclellan
Professor of Management Accounting and Cantrol
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 0 votes
- 3 stars: 8 votes
- 4 stars: 15 votes
- 5 stars: 20 votes
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