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Know Data Analytics, Data Mining & Business Intelligence

Business

Rating4.2
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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

  • Dr. John Daniel Mclellan
    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

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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Tags: $29.99, Business, Business Strategy, Dr. John Daniel Mclellan, Know Data Analytics, Data Mining & Business Intelligence
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