Mastering Data Series

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Data Optimization for Finance 1: End to End Overview

To become better business partners, finance teams must deliver more relevant analyses and go beyond the siloed views of business. Finance teams must dive deeper in their searches for new signals in the enterprise data noise. They must carve out more time for innovation, engagement, and execution. A key to this evolution resides in the mastering of not only data but also technology, people dynamics and process optimization. In this seminar, learn how to architect simple and agile technology solutions that serve today’s data needs. The material will focus on the foundations of efficient data management; specifically on ways to master the capture, processing and delivery of the data that drives decisions.

Agenda Topics

  • The value of data for finance
  • Techniques to ask the right business questions and mitigate bias
  • How to secure fluid finance processes with the right technology pieces
  • The keys to optimal finance data preparation
  • Short, live case studies to illustrate practices on real financial data
  • Change management and proactive leadership in data projects

Course Length

Three 2-Hour Virtual/In-Person Sessions or One Full-Day Virtual/In-Person

Learning Objectives

  • Acquire an understanding of the complete skills required to design, run, and scale business analytics
  • Learn to optimize and leverage a combination of people, data technology, and processes to elevate your data capture process
  • Design efficient processes that empower more focus on collaboration and execution in your organization

Data Optimization for Finance 2: Accelerate the Master Data Process

Data insights lead to actionable intelligence. Finance teams have an increasingly complex task to ensure the right data is being collected, governed, and analyzed. In Data Optimization for Finance 1, we introduced the key concept of data evolution resides in mastering not only the data, but the technology, cultural dynamics, and process. In this course, participants will take a deeper dive into the data and technology to accelerate their ability to move from raw data to data that matters and on to actionable intelligence.

Agenda Topics

  • The foundation of data governance
  • Join data to build a holistic understanding of business challenges
  • Manage Master Data (customer, entity, product, etc. reference data)
  • Advanced data preparation techniques to accelerate analytics
  • Key Python commands to scale data preparation techniques to millions of rows

Course Length

Three 2-Hour Virtual/In-Person Sessions or One Full Day Virtual/In-Person

Learning Objectives

  • Master advanced data preparation techniques to boost insight
  • Understand the power and importance of data models
  • Introduction to Python commands to scale data techniques exponentially

 

Data Optimization for Finance 3: Advanced Techniques & AI

Data science is advancing at a furious pace. Yesterday’s pipe dream is today’s know-how to be a market leader. This course is designed to make some of those cutting-edge concepts attainable for your data-centric finance team. Concepts covered include advanced visualization techniques, artificial intelligence, and machine learning algorithms. Each of these topics will be covered with real-world application to finance and help your team think about data in new and impactful ways.

Agenda Topics

  • Presentation of the Machine Learning principles
  • The review of the key algorithm families and their applications
  • Profiling, preparation, and enriching of data for Machine Learning
  • Advanced visualization to support the interpretation of results
  • Understand the risks and opportunities of AI in business
  • Live case studies to illustrate AI applied to real financial data

Course Length

Three 2-Hour Virtual/In-Person Sessions or One Full-Day Virtual/In-Person

Learning Objectives

  • Garner an understanding of all the required expertise to be able to feed, run and interpret machine learning algorithms in a finance context
  • Ability to implement machine learning within your data process
  • To learn how to select KPIs and ensure their relevance and alignment to strategies and operating plans
  • Learn about advanced visualizations that support the interpretation of machine learning results
  • Understand the opportunities and risks that artificial intelligence provides to finance teams

Understanding the Case for Artificial Intelligence (AI) in Forecasting and Analytics

We are entering the era of digital FP&A where human and artificial intelligence (AI) work hand in hand to achieve better analytical results. The new world of FP&A requires on-demand continuous planning process and AI-driven forecasts where various business scenarios can be played almost in real-time. Both driver-based planning and FP&A predictive analytics are essential tools for implementing flexible dynamic planning and forecasting processes to achieve increased revenue growth, profits and improved operating performance.

Agenda Topics

  • Why AI-enabled analytics is the next competitive edge
  • The AI-enabled predictive analytics model
  • Define mindset stages
  • Implementing AI-enabled predictive analytics capabilities
  • Class use cases – (1) defining variables and (2) building analytical scorecard using KPIs

Course Length

3 2-hour Virtual Sessions or 1 Full-Day In-Person

Learning Objectives

  • Understand what AI-Enabled Analytics is and how it can help FP&A teams
  • Learn how to sharpen decision-making using sound judgement, critical thinking, and AIEnabled Analytics
  • Learn frameworks to implement powerful AIEnabled Analytics into action
  • Demonstration of a case study around implementation of AI-enabled budgeting, forecasting, and analytics
  • Learn how to sustain implemented AI-Enabled Analytics