Vous travaillez en tant qu'ingénieur spécialisé dans les systèmes décisionnels au siège de l'entreprise française "Fantastic". L'entreprise "Fantastic" vend principalement des ouvrages de divertissement de type science fiction, thriller, policier... Elle dispose pour cela de plusieurs magasins de vente dans les centres des grandes villes en France. La direction de l'entreprise souhaite faire une étude large sur les ventes de l'année passée afin de prendre des orientations stratégiques nouvelles : ouverture de nouveaux magasins, fermeture ou transfert de magasins mal implantés, extension territoriale à de nouveaux départements français, réorganisation des directions, réorientation du marketing, élargissement ou réduction du catalogue, etc
1. Data Extraction and Transformation (SSIS):
- Identify data sources: Gather data from sales transactions, customer information, and product details across all stores. This may involve connecting to various databases or flat files.
- Develop SSIS packages:
- Extract data from each source using appropriate connectors (OLE DB, flat file, OData).
- Cleanse and transform data:
- Address missing values and inconsistencies.
- Standardize formats (dates, currencies).
- Derive new fields (e.g., purchase category, customer segments).
- Validate data integrity.
- Load the transformed data into a staging area or data warehouse.
2. Data Analysis and Modelling (SSMS):
- Connect to the data warehouse: Use SSMS to explore and query the transformed data.
- Dimensional modeling: Design a star schema or snowflake schema to efficiently represent sales data, products, customers, and stores.
- Create views and stored procedures: Build optimized data access points for specific analysis needs.
3. Data Visualization and Reporting (Power BI):
- Connect to the data warehouse: Import data from the chosen data model into Power BI.
- Develop interactive dashboards:
- Visualize key sales metrics (total sales, sales by genre, top-selling products, etc.).
- Analyze trends over time, compare stores, and segment customers.
- Use filters, slicers, and drill-down functionality for interactive exploration.
- Create informative and visually appealing reports with charts, maps, and tables.
4. Advanced Analysis and Insights:
- Utilize Power BI Desktop's DAX language: Create calculated columns and measures for deeper analysis (e.g., market share, customer lifetime value, campaign effectiveness).
- Consider advanced techniques:
- Explore machine learning to predict future sales or identify buying patterns.
- Implement R scripts for statistical analysis and custom visualizations.
5. Communication and Recommendations:
- Present findings to stakeholders: Translate data insights into actionable recommendations for the leadership team.
- Focus on strategic implications:
- Recommend new store locations based on sales potential and demographics.
- Identify and suggest adjustments to marketing campaigns for better reach and engagement.
- Propose product assortment changes based on popularity and profitability.
- Suggest organizational changes to optimize store operations or marketing efforts.
Additional Notes:
- Data security and governance: Ensure compliance with data privacy regulations and internal policies.
- Documentation and version control: Keep track of data sources, transformations, and analysis steps for future reference and reproducibility.
- Collaboration and feedback: Involve stakeholders throughout the process to ensure alignment with business needs and expectations.
By following these steps and leveraging the powerful tools of SSIS, SSMS, and Power BI, you can conduct a comprehensive BI analysis for Fantastic, providing valuable insights and recommendations to drive strategic decision-making and future growth.