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Join the University of Akron's Business Analytics Innovation Summit to explore how digital transformation enabled businesses from different industries to better understand their data, make predictions, create visualizations, and derive insights.
Analytics Everywhere
Friday, September 30, 2022
Quaker Station, The University of Akron
Presenters
Mark Ruffing
Assistant Director in Enterprise Analytics
Cleveland Clinic
Sean Mancini
Director Digital Supply Chain Analytics
Signet Jewelers
Nate Turner
Data Scientist
FirstEnergy Corp
Matt Fernandez
Innovation Center Business Analyst
FirstEnergy Corp
R.J. Nemer
Dean
The University of Akron College of Business
Mike Conley
Chief Information Officer and Senior Vice President
Cleveland Cavaliers
Workshops
Power BI Desktop and Artificial Intelligence
Macauley Kloetzly
Microsoft Learning Consultant
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Understand the building blocks of Power BI Desktop
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Explore the data prep capabilities of Power Query
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Write formulas and model your data
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Begin visualizing data and formatting a report
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Connect to a sample Power BI dataset
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Explore how to make confident decisions using artificial intelligence capabilities
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Create a report with the Power BI service
Objectives:
​You will learn how to setup a full data lake house architecture, from soup to nuts. You will build out the components in Azure using automated scripts, including metadata driven pipelines to saturate your data lake. You will also build out tables and connect Power BI to them to utilize the data.
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Build components in Azure with PowerShell scripts
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Build and run metadata driven pipeline to build data lake
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Build table/view in Synapse workspace
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Connect to table with Azure services
Building Lakehouse with Azure Synapse Analytics
Hope Foley
Microsoft Cloud Solution Architect
Objectives:
Objectives:
Objectives:
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Understand the basic elements of R programming, including how to create different types of data objects such as vectors, matrices, lists, and data frames and how to create custom functions
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Gain hands-on skills with the R interactive environment, including how to load the package and how to load structured data from data files, databases, and the web
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Gain hands-on experience on how to examine, summarize, and visualize data, how to perform and improve linear regression modeling, and how to transform data
R Programming: A Hands-On Tutorial
Dr. Liping Liu
Professor of Management and Information Systems
Objectives:
