Big Data & Business Intelligence
Big Data & Business Intelligence, available at $44.99, has an average rating of 4.1, with 35 lectures, based on 137 reviews, and has 866 subscribers.
You will learn about Describe the purpose and uses of Business Intelligence & Big Data in the business world today • Identify the terminology used in Big Data and quantitative analysis programs in general • Build a dataset based on gathering data from multiple sources and merging those databases into a single unified set • Clean a database through automated methods like winsorizing and evaluation of univariate metrics to determine accuracy of inputs • Identify key risk issues involved in Big Data and the role that information governance plays. This course is ideal for individuals who are This course will provide an introduction to the practices and procedures involved with Business Intelligence and applied Big Data analysis. Participants will learn what Big Data is and why it is being discussed as a revolutionary approach to many aspects of business and finance. Participants will get hands-on experience with gathering, merging, and cleaning Big Data databases. The program will also entail critical evaluation of existing datasets to check for potential problems or concerns over data integrity. The course will also include a discussion of information governance. It is particularly useful for This course will provide an introduction to the practices and procedures involved with Business Intelligence and applied Big Data analysis. Participants will learn what Big Data is and why it is being discussed as a revolutionary approach to many aspects of business and finance. Participants will get hands-on experience with gathering, merging, and cleaning Big Data databases. The program will also entail critical evaluation of existing datasets to check for potential problems or concerns over data integrity. The course will also include a discussion of information governance.
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Summary
Title: Big Data & Business Intelligence
Price: $44.99
Average Rating: 4.1
Number of Lectures: 35
Number of Published Lectures: 35
Number of Curriculum Items: 35
Number of Published Curriculum Objects: 35
Original Price: $27.99
Quality Status: approved
Status: Live
What You Will Learn
- Describe the purpose and uses of Business Intelligence & Big Data in the business world today
- • Identify the terminology used in Big Data and quantitative analysis programs in general
- • Build a dataset based on gathering data from multiple sources and merging those databases into a single unified set
- • Clean a database through automated methods like winsorizing and evaluation of univariate metrics to determine accuracy of inputs
- • Identify key risk issues involved in Big Data and the role that information governance plays.
Who Should Attend
- This course will provide an introduction to the practices and procedures involved with Business Intelligence and applied Big Data analysis. Participants will learn what Big Data is and why it is being discussed as a revolutionary approach to many aspects of business and finance. Participants will get hands-on experience with gathering, merging, and cleaning Big Data databases. The program will also entail critical evaluation of existing datasets to check for potential problems or concerns over data integrity. The course will also include a discussion of information governance.
Target Audiences
- This course will provide an introduction to the practices and procedures involved with Business Intelligence and applied Big Data analysis. Participants will learn what Big Data is and why it is being discussed as a revolutionary approach to many aspects of business and finance. Participants will get hands-on experience with gathering, merging, and cleaning Big Data databases. The program will also entail critical evaluation of existing datasets to check for potential problems or concerns over data integrity. The course will also include a discussion of information governance.
This course is broken up into four modules.
The first module will prepare participants to begin business intelligence projects at their own firm. The focus of the course is a hands-on approach to gathering and cleaning data. After taking this course, participants will be ready to create their own databases or oversee the creation of databases for their firm. The focus in this course is on “Big Data” datasets containing anywhere from tens of thousands to millions of observations. While the tools used are applicable for smaller datasets of a few hundred data points, the focus is on larger datasets. The course also helps participants with no experience in building datasets to start from scratch. Finally, the course is excellent for users of Salesforce, Tableau, Oracle, IBM, and other BI software packages since it helps viewers see through the “black box” to the underlying mechanics of Business Intelligence practices.
The second module will prepare participants to begin business intelligence projects at their own firm. The focus of the course is a hands-on approach to structuring data including generating new variables based on comparative and relative metrics. The structuring of these variables will be done in Excel, SAS, and Stata to give viewers a sense of familiarity with a variety of different software package structures. The focus in this course will be on financial data though the techniques are also applicable to more general forms of data like that used in marketing or management analyses.
The third module will prepare participants to begin running data analysis on databases. Both univariate and multivariate analysis will be covered with a particular focus on regression analysis. Regression analysis will be done in Excel, SAS, and Stata to give viewers a sense of familiarity with a variety of different software package structures. The focus in this course will be on financial data though the techniques are also applicable to more general forms of data like that used in marketing or management analyses.
The fourth and final module will prepare participants to review, analyze, and make decisions based on results from business intelligence projects. The course will cover reading and interpreting regression analysis. The course will also give participants the skills to critically analyze and identify potential limitations on analysis. The course will also cover predicting changes in business outcomes based on analysis and identifying the level of certainty or confidence around those predictions. This paves the way for future detailed courses in predictive analytics.
Course Curriculum
Chapter 1: Introduction to Big Data and Business Intelligence
Lecture 1: Introduction
Lecture 2: Introduction to Big Data and Business Intelligence Part 2
Lecture 3: Introduction to Big Data and Business Intelligence Part 3
Lecture 4: Introduction to Big Data and Business Intelligence Part 4
Lecture 5: Introduction to Big Data and Business Intelligence Part 5
Lecture 6: Introduction to Big Data and Business Intelligence Part 6
Lecture 7: Introduction to Big Data and Business Intelligence Part 7
Chapter 2: Data Collection and Cleaning
Lecture 1: Data Collection and Cleaning Part 1
Lecture 2: Data Collection and Cleaning Part 2
Lecture 3: Data Collection and Cleaning Part 3
Lecture 4: Data Collection and Cleaning Part 4
Lecture 5: Data Collection and Cleaning Part 5
Lecture 6: Data Collection and Cleaning Part 6
Chapter 3: Structuring Data
Lecture 1: Structuring Data Part 1
Lecture 2: Structuring Data Part 2
Lecture 3: Structuring Data Part 3
Lecture 4: Structuring Data Part 4
Lecture 5: Structuring Data Part 5
Lecture 6: Structuring Data Part 6
Chapter 4: Fundamentals of Data Analysis
Lecture 1: Fundamentals of Data Analysis Part 1
Lecture 2: Fundamentals of Data Analysis Part 2
Lecture 3: Fundamentals of Data Analysis Part 3
Lecture 4: Fundamentals of Data Analysis Part 4
Lecture 5: Fundamentals of Data Analysis Part 5
Lecture 6: Fundamentals of Data Analysis Part 6
Lecture 7: Fundamentals of Data Analysis Part 7
Chapter 5: Using Data Analysis
Lecture 1: Using Data Analysis Part 1
Lecture 2: Using Data Analysis Part 2
Lecture 3: Using Data Analysis Part 3
Lecture 4: Using Data Analysis Part 4
Lecture 5: Using Data Analysis Part 5
Lecture 6: Using Data Analysis Part 6
Chapter 6: Exercises and Cases
Lecture 1: Case 1
Lecture 2: Case 2
Lecture 3: Basics of Business Intelligence Analysis Exercise
Instructors
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Michael McDonald
Finance Professor and Corporate Consultant
Rating Distribution
- 1 stars: 4 votes
- 2 stars: 14 votes
- 3 stars: 47 votes
- 4 stars: 41 votes
- 5 stars: 31 votes
Frequently Asked Questions
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