Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
4 Hour(s) 16 Minute(s)
Language
English
Taught by
Michael McDonald
Rating
Course Overview
Everything You Need To Know About Big Data and Business Intelligence for the Modern Workplace
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 Content
- 6 section(s)
- 35 lecture(s)
- Section 1 Introduction to Big Data and Business Intelligence
- Section 2 Data Collection and Cleaning
- Section 3 Structuring Data
- Section 4 Fundamentals of Data Analysis
- Section 5 Using Data Analysis
- Section 6 Exercises and Cases
What You’ll 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.
Skills covered in this course
Reviews
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CCarlo Vecchio
The course has a financial orientation; it is understandable even for a non-mother tongue speaker. Very basic slides with text and a few screenshots. Some concepts are repeated several times. I was not particularly satisfied.
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WWill Healey
This course was very helpful - thank you. As newcomer to the world of big data and analysis, I appreciated the way the instructor built upon each lesson, summarizing the key points from previous modules before moving ahead into subsequent models. The .xls worksheet and instructions (about the data analysis add-ins) were also helpful and I intend to continue taking additional courses.
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CCarlos Javier Garcia Alvarez
tiene algún módulo repetido, y algunos conceptos no están bien detallados o explicados y hay que tirar de google o la wikipedia. Se centra mucho más en Business Intellegence que en Big Data, más en conceptos estadísticos que en procesamiento.
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SSalvador García Raro
Very poor presentation - just slides with plain text. No documents that can be downloaded for later study Code snippets without enough context and applicability that come up a few times. Content has a financial orientation, not applicable for other types of business intelligence.
