Data Analytics


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Analyze and Forecast Using Large Data Sets
Gain confidence in building reliable data analyses to make projections of business intelligence and performance. Utilize the fundamental analytical tool - regression - for discovering, analyzing and forecasting relationships. Acquire a solid understanding of the methods, using intuitive graphical approaches to explain and motivate regression and forecasting models.
Benefits
- Discover, analyze and forecast relationships among large data sets (“Big Data”)
- Apply regression to uncover trends, patterns and data correlations
- Analyze case studies to gain a thorough consideration of the models applications and gain confidence when using data to make analyses, forecasts and projections
- Model customer retention rates, develop an optimal bidding strategy in a sealed bid process, hedge your firm’s revenue, or forecast future profitability of individual customers, monthly sales, or daily stock prices by charting a successful course with regression and forecasting methods
- Apply regression to past relationships, looking for trends, seasonal patterns and hidden correlations that can predict the future reliably
- Develop the acumen to competently evaluate findings and analyses presented by others
- Interact with data executives on the topic of data-driven business intelligence
Enrollment Options
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Group and Custom Enrollment
Enroll as a team, or customize this program for your organization.

Upcoming Sessions
Class Details
Business Analytics
Date
10/31/22 - 11/01/22
2 Days
Instructors
Thomas Sager
Thomas Shively
Location
UT Campus
Data Analytics |
Business Analytics |
|
Date 10/31/22 - 11/01/22 2 Days |
Instructors Thomas Sager Thomas Shively
|
Location UT Campus |
Class |
Concentration |
Date |
Location |
Instructors |
|
---|---|---|---|---|---|
Data Analytics |
Business Analytics |
10/31/22 - 11/01/22 2 Days |
UT Campus |
Thomas Sager Thomas Shively
|
Topics
The following topics will be covered in this course.
- Forecasting models
- Random samples
- Random walks
- Autoregression
- Moving averages
- ARIMA (Autoregressive Integrated Moving Average)
- Regression analytics
- Regression case studies
Both professors were clear, knowledgeable and kept things practical and basic enough for those of us who aren't experts. Case studies were very helpful.

Who Should Attend?
This course is designed for professionals with limited to moderate knowledge of statistics who want a refresher in the tools and models in pracitcal application.
It is not just for those who are analyzing data and making recommendations. This course is also a good fit for any leader who wants to be more conversant in data analytics and to find new ways to leverage data analytics to solve complex problems.
This course is appropriate for a variety of professionals across verticals. Whether you work for a global corporation or a small business, we can help.
There are no prerequisites for this course.
Demonstrate Your Expertise with a Certificate

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Reimbursement Options
Learn more about course credits and options for course reimbursement. Get tips on the best way to approach your manager and download a customizable template to facilitate making the ask.

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Course Location
In person courses take place at the AT&T Executive Education and Conference Center and adjoining Rowling Hall on the UT campus in Austin. These world-class facilities provide a comfortable and convenient learning environment, with direct access to the 40 acres of campus and within walking distance of downtown Austin. Live online and on-demand course options are available for many courses.
Other Business Analytics Courses
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Utilize data from past success to predict and realize future success.
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Across industries, routine decisions and competitive strategies increasingly rely on data-driven business intelligence.
Resources
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How AI and Machine Learning Transform Business Decision-Making
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The Science Behind Acquiring Developing, and Retaining Top Talent
Learn how organizations are using big data combined with a people-analytical approach to compete and succeed in the marketplace.
