Camille Salia

Project 1: Optimization and automation of reporting tools for Human Resources/Sales Administration/Commerce departments Needs gathering and analysis Implementation of Dataflow for storing and transforming large volumes of data using M and SQL languages. The goal was also to pool and standardize management rules reusable by all Data Product Managers. Importing encrypted or unencrypted data from SQL Server or SharePoint. Direct connection (DirectQuery) to a SQL Server Analysis Services (SSAS) database. Creation of Power BI reports for the group's management and HR, Sales Administration, and Commerce departments. Use of DAX language for KPI calculation such as FTE count, departure and arrival rates, salary increase tracking, salary cost... Implementation of Row Level Security (RLS) for data access restrictions. Publishing reports online via Power BI service. Integration of Power Apps forms to modify a table visual in Power BI. Creation of Power Automate flows for mass emailing of PDF files to clients. As well as for on-demand report updates. Project 2: Business Support, Power BI Administration, Report Maintenance, JIRA Support Tickets User rights management on different reports to secure data. Business support for the creation of their first Power BI reports. Change management and training for HR department users. Reference for Social dataflows, Access rights management. Gateway access rights management. Alerting on exceeding premium capacity threshold. Detection and analysis of reports contributing to the peak reached by the capacity. Proposal for report optimization. Support via Jira or GLPI for report maintenance. Technical environment: Microsoft Fabrics Admin, Jira, GLPI, dataflow

Gathering needs from departments for the deployment of performance indicators. Production and analysis of international dashboards. Advancement of cross-functional topics: data quality management, migration of reporting from Excel to Power BI. Issue with slow data import: exploration with Python in Jupyter Notebook using Numpy and Pandas packages.

Data extraction through SQL queries and data cleaning with R. Use of different segmentation methods (HAC, K-means). Use of forecasting techniques (Holt-Winters, GARCH, ARMA...)