logo for rishi lat one 21st.png


Rishi Sapra

Rishi is a Microsoft Data Platform Most Valuable Professional (MVP), being formally recognised by Microsoft for his community contributions. He is a Chartered Accountant (ACA) with a background in Financial Modelling and Consulting in Financial Services, having worked at Deloitte, HSBC, Barclays and KPMG prior to his current role as a Group Manager at Avanade. Rishi is a co-founder of Learn Data Insights (www.learndatainsights.com)

LinkedIn / Twitter

thumbnail_Francisco Gutierrez profile pic.jpeg

Francisco Gutierrez

A data lover with experience in Finance and as a Power BI contractor. Currently I’m in charge of the administration and deployment of Power BI in Entain giving support to multiple teams across the world.

LinkedIn / Twitter


Fernando Calero

Fernando is a data analytics enthusiast with experience in Business Process assessment and alignment with the strategy to improve performance and help achieve the Company’s goals and objectives, and in Controlling in the Automotive Manufacturing Industry where he spent more than 8 years in transnational companies like Robert Bosch in Mexico. Currently as an independent consultant he is applying his experience to help medium and small companies get insights from their data and take actions to better achieve their goals. Passionate about Business Intelligence and business process automation. Eager learner.​

LinkedIn / Twitter


 Mutala Baba

Mutala is a Chartered Accountant (ACCA) with Teim Accountants and a certified Microsoft Power BI professional. He specialised in using Power BI to give insights into an organisation performance and financial reporting for critical decision making. 

LinkedIn / Twitter


Triparna Ray

Triparna Ray is a BI Architect and MS Power BI consultant at IBM offering vast experience leveraging Microsoft Analytics and agile methodologies to deliver highly effective and creative solutions to business and technology challenges. Successfully delivered end to end BI solutions for clients across domains and geographies with special focus on Financial Reporting.​

LinkedIn / 

Gain hands-on experience with developing solutions in low-code/

no-code platforms that can deliver immediate business value within the finance function 

Network with peers and understand how the Microsoft technology

stack is being used in Finance

across different companies/industries ​ 

Keep up to date with the latest developments in these

technology platforms and

how new features can be applied within finance  

Young Business Colleagues
A space (virtual and physical) where finance professionals can come together to learn about modern approaches to financial reporting & analytics using the Microsoft Power Platform tool set

Follow us on LinkedIn and Twitter to be kept informed of upcoming events

Last Webinar - 10th December 2020 (6pm BST)

talk 21 copy.jpg

In this video, Imke takes us through carrying out advanced scenario modelling in Power BI, with a focus on Power Query. The scenario here is that we want to model Shipping/Marketing/Overhead costs as calculate sales revenue/net profit.

These depend on a number variables including the version of the product (Standard/Premium - each of them has a different set of fixed and variable costs) and the sensitivity to drivers such as price, quantity and exchange rates. Using a series of simple tables in excel as inputs, Imke shows how to produce:

• Sensitivity Analysis charts in Power BI showing how sensitive net profit is to a % change in Sales of the Premium/Standard product • Tornado charts showing the specific changes (in either direction) for a particular driver: e.g. showing how much net profit increases or decreases if price increases or decreases by 5%.

• Having different scenarios (with the excel input defining which drivers can be flexed and by how much under each scenario) selectable through a slicer to show the impact of each scenario on net profit.

• A monte carlo simulation with the number of iterations (e.g. 1000 or 10000) defined through a Power Query parameter, and the probability of the various driver values - in this case exchange rates - calculated using actual historical exchange rates from Yahoo Finance.

Join Our Mailing List 

  • LinkedIn
  • Twitter