- Data analytics, statistics, data analysis - Fundamental knowledge of statistics, data analysis (including correlation, regression and segmentation) and forecasting methods - Growth (decay), index calculations
Understanding and implementing
Target audience
- Internal auditors
- Bankers / Account managers
- Consolidation and accounting managers
- Financial managers and controllers
- Chartered accountants
- Accounting managers
- Treasurers
3 day
Data Analysis Training - Transforming and adding value to information
In today's data-driven world, knowing how to exploit data has become a strategic skill. This data analysis course enables you to transform raw data into useful information, directly in Excel. You'll learn how to structure, cross-reference and visualize data to extract meaning and guide your decisions.
Designed for operational or financial professionals, this course will give you the tools to automate analyses and develop your analytical autonomy, without depending on an IT department.
Prerequisites
This module requires a good knowledge of statistical analysis and Excel, acquired for example through the following training courses "Mastering fundamental data calculations" and and "Techniques for analyzing large volumes of data (Advanced Excel)". from our training catalog.
Objectives
◗ Integrate Data Science and Artificial Intelligence as aids to answering questions, making decisions and helping to improve performance.
◗ Transform raw data into actionable information
◗ Use the main analytical and predictive tools
◗ Model these tools for complete use cases in real-life situations
Training program
◗ Posing a data-oriented problem
- Differences between describing, understanding and forecasting
- Identify useful indicators for analysis (lagging, leading...)
- Translate a business question into a data issue
✔ UNDERSTAND | Illustration: typology of analysis purposes (retrospective vs. predictive)
✔ APPLY | Case study: transforming a management question into an analysis requirement
structured
✔ ASSESS | Quiz: in your opinion... What is a causal indicator?
◗ Structuring a modeling project
- CRISP-DM methodology: from question to model
- Choosing the right data and processing
- Introduction to deterministic and probabilistic models
✔ UNDERSTANDING | Guided study: breaking down a real case with CRISP steps
✔ APPLY | Case study: modeling a constrained delivery plan
(Excel Solver)
✔ ASSESS | Quiz: what do you think... What steps precede model selection?
◗ Applying predictive models to management
- Simple and logistic regression, decision trees
- Business cases: sales forecasting, erroneous OD, customer targeting
- Interpretation of results: reliability, thresholds, expected gains
✔ APPLY | Case study: predicting erroneous ODs with a decision tree
✔ EXPERIMENTATE | Workshop: critical reading of a simple scoring model
✔ ASSESS | Quiz: in your opinion... Which variable most influences prediction?
◗ Integrating Bayesian logic
- Conditional probabilities, belief, updating
- Apply Bayes' law to business reasoning
- Example: predicting a project delay from e-mail data
✔ UNDERSTAND | Illustration: diagram of Bayesian reasoning
✔ APPLY | Case study: updating a project delay probability based on new information
new information
✔ ASSESS | Quiz: what do you think... is Bayes just for statisticians?
◗ Use time series to forecast
- Moving averages, exponential smoothing, Holt-Winters
- Detection of trends, seasonality and anomalies
- Application to business forecasts: sales, expenses, volumes
✔ APPLY | Case study: forecast monthly sales using each method.
✔ EXPERIMENTATE | Workshop: test forecasting methods and compare errors
✔ EVALUATE | Quiz: what do you think... How do you know if a model is a good fit?
Why train in data analysis?
Would you like to initiate, develop or simply contribute to a Data-driven approach? Would you like to know which business questions can be answered using Data? Do your issues concern marketing, logistics, production management, human resources, quality, treasury or management control?
This affordable training course is at the heart of the Data Analytics competency.
Teaching and assessment methods
Before : self-assessment quiz
During the session: one complete business case per theme. Work in small groups and plenary discussions. Excel templates provided. Numerous practical exercises to validate the acquisition of skills at each stage.
After: the participant keeps all Excel templates.
The trainer is available to answer any questions relating to the training.
General training | FinHarmony Conseil & Formation
See our full training catalog.
Price
2,750 EXCL. TAX
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Jonathan C.
Company
Training