Data Analytics training: How to challenge data

Prerequisites

No prior knowledge required

Objectives

◗ Identify the biases and limitations of a dataset.

◗ Evaluate the quality and reliability of the data used in the analyses.

◗ Interpret the key indicators and results from the analytical models.

◗ Assess the business relevance of an analysis or data model.

◗ Document an analysis requirement for the data teams.

Training program

◗ Interrogating and understanding data

– Define the different types of data (source, format, volume)
– Identify potential biases: collection, transformation, interpretation
– Understand the limitations of a dataset without business documentation
✔ UNDERSTAND | Illustration: mapping a financial data flow
✔ EVALUATE | Quiz: In your opinion… Is data always “objective”?

◗ Identifying the right questions to ask

– Link data to business questions: prediction, performance, alerts
– Avoid misleading correlations and apply the right filters
– Formulate explainable, verifiable, business-driven hypotheses
✔ UNDERSTAND | Brainstorming: What does “challenging data” mean?
✔ APPLY | Practical exercise: Reformulate a dashboard alert into a testable hypothesis
✔ EVALUATE | Quiz: In your opinion… Does a decline in margin always indicate a cost problem?

◗ Communicating effectively with Data teams

– Understanding the role of a Data Analyst/Data Scientist
– Knowing how to read an analysis report (KPIs, distributions, models, thresholds)
– Use common terminology to confidently challenge assumptions
✔ APPLY | Practical exercise: Critical analysis of an automated scoring report
✔ EXPERIMENT | Role-play: Responding to a data scientist regarding a model’s business relevance
✔ EVALUATE | Quiz: In your opinion… What does an R² of 0.92 mean?

◗ Structuring Your Own Data Requests

– Formulate a clear, prioritized requirement: decision, pilot, optimization
– Describe the expected inputs, outputs, and rules
– Create a clear, reusable brief for recurring projects
✔ APPLY | Practical exercise: Create a data brief to analyze customer churn
✔ EVALUATE | Quiz: In your opinion… What information is unnecessary in an analysis request?

Why choose this course?

According to all data analytics professionals, the ability to critically evaluate data is the key skill that organizations lack.

In just one day, this training course will provide you with the fundamentals of a skill set that will become crucial in the future, particularly for finance professionals.

Teaching and assessment methods

Before the training: Submit your expectations via your online portal 15 days before the training begins and complete a self-assessment of your skills.

Teaching Methods: A variety of teaching methods to cater to different learning styles, encourage active participation, and reinforce learning through experimentation and practice.

Educational materials: presentation materials, reference materials (summary sheets, tables, etc.), and other resources available in your account.

During the training: theoretical concepts are alternated with examples drawn from real-life cases. Participants are given the opportunity to engage in role-playing exercises. Numerous practical exercises allow participants to demonstrate their mastery of the skills as the training progresses.

Training monitoring and evaluation: attendance sheet and certificate of completion. Immediate and post-training evaluations conducted using the LearnEval platform.

Price

1 295 € EXCL. TAX

Testimonials

Data analytics training

Jonathan C.
Company
Training

Generalist trainings