Data Analytic Tools for Financial Management (FINC8900)

Description:

This seminar is a condensed, quick paced overview on the principles, tools, techniques, and applications of data analytics within a contemporary financial management environment. Large amounts of electronic data present an enormous challenge and opportunity to identify trends, correlations, compliance, cost/expense activity, risks, possible fraud, errors, and otherwise hidden actions, and effects in financial and operational performance. This seminar will demonstrate the application of software and a case study to demonstrate the power of available tools to extract, sort and identify specific information from databases and the cloud. This seminar will also explore approaches to using data to identify risks and outliers, monitor activity, display, and chart results for reporting.

For the virtual version, students must have Excel-with the Data Analysis ToolPak activated (this is included with Excel software).

This course is part of the Master Certificate in Federal Financial Management.

Who Should Attend?

Financial managers, analysts, internal control administrators and evaluators.

Tuition:

$579.00

Credits:

8.0 CPE's

Class Type:

This course is currently being offered in the following training modalities:

• Online
  • Virtual Instructor-Led - FINC8900A
    • Class Length: This class is listed as a 1 day course.
• On-site
  • Contact our Business Development department for more information.
  • For in-person training sessions, participants are required to download the course materials to a personal device (e.g., laptop or tablet) and bring their device to class for use during classroom instruction.

Learning Outcomes:

• Explain the importance of data analytics in financial management, performance assessment and accountability
• Identify patterns and outliers quickly to make decisions on what to analyze
• Describe the difference between structured and unstructured data
• Use the Data Analysis Maturity Model and identify your organization’s maturity
• Practice on multiple case studies doing analysis with financial assessment specific data analysis tools
• List common data analysis tools that can be used in financial, activity and performance assessment
• Explain various trends in data analysis, data architecture, data governance