Introduction to a much easier and immediate way auditors can harness generative AI and Python for data analytics
(October 3, 2023 9AM NY time)
FREE TUESDAY WEBCLASS 9AM EST
This webclass will share an exciting new application of generative AI for data analysis. In order to extract meaningful insights from messy, raw data, auditors and data professionals must perform a variety of time-consuming technical tasks. Generative AI and visual methods to interact with your data dramatically speed up the tedious parts of the process and reduce barriers to technical analytics languages, like Python. This enables business professionals to analyze data, clean and organize it, build predictive models, and so much more with speed and efficiency not previously possible.
Meet Your Host
This week, let's welcome our 2 guest speakers - Mark Fritzen and Paul Yang - Data Science from Einblick.
MARK FRITZEN
Business Development Manager at Einblick                     Â
… accelerating Data Science
CLAIRE WORLEDGE
Ex-big 4 data analytics manager, Certified Fraud Examiner and IT auditor
… author of Data Analytics Secrets
PAUL YANG
Making Data Science Accessible at Einblick                   Â
… solving every data problem with just 1 sentence
Thanks For All The Amazing Content!
“Thanks for all the amazing content in the webclasses. We have learned quite a lot and this is helping the team to get going with SAP data analytics, as well as challenging our consulting vendors!”
Celia, Head of Internal Audit
What We Cover in Our Webclasses
During our Data Leaders In Internal Audit Tuesday Webclasses we are gaining insights on the following:
How do the Big 4 firms do data analytics?
What does the IIA, ISA, ACFE and ISACA say about data analytics?
What risks should be avoided when using data analytics in internal audit?
How can we train our auditors so that they can successfully use data analytics in their work?
What are the most obvious fraud schemes that data analysts need to be aware of?
What do “normal“Â auditors and data analysts need to understand to make an efficient team?
Which data do you need to extract from SAP and how should it be interpreted?
How can we leverage data to see risks in the entity and better prepare the audit?