Mohammad Hasan

• Leveraged SSIS, SSAS, SQL, Python, Power BI and data modeling techniques to analyze large, complex datasets, uncovering actionable insights that resulted in a 20% increase in business process efficiency. • Developed and implemented automated Power BI dashboards and reporting tools, improving the speed of data-driven decision-making by 30% and reducing manual reporting time by 25%. • Collaborated with cross-functional teams to define and test business hypotheses, applying statistical techniques to deliver data-driven insights that resulted in a 15% reduction in operational costs. • Designed and maintained ETL/ELT workflows in Azure Data Factory and Databricks, optimizing data retrieval processes and improving query efficiency by 30% across financial reporting dashboards. • Automated data pipelines using Databricks, eliminating manual processes and reducing reporting efforts by 40%, enabling real-time insights. • Translated business requirements into technical specifications, providing actionable insights through data visualizations to support finance, sales decisions and performance tracking. • Enhanced data flow efficiency, cutting data retrieval time by 35%, leading to faster and more reliable business analytics and data accuracy. Technologies and Tools Expertise: Business Intelligence & Analytics: • Power BI (Data modeling, DAX, M, Visualization) • Microsoft Power Platform (Power Automate, Power Apps) Data Management & Cloud Solutions: • Microsoft Fabric • Oracle PBCS & EMP Cloud • Azure Data Lake Storage • Azure SQL Database • Azure Data Factory (ADF) • SAP (Data Analytics & Integration) Database & ETL Development: • Microsoft SQL Server (On-premises & Cloud) • Data Modeling & Transformation • SQL Server Integration Services (SSIS) • SQL Server Analytical Services (SSAS) Programming & Version Control: • Python (Data Processing & Automation) • GitHub (Version Control & Collaboration)

• Developed and enhanced the product portfolio for BI reporting and self-service, working closely with B2C vertical teams to deliver impactful analytical tools. • Continuously improving and governing analytical products to support data discovery and interpretation, ensuring the right data is available for informed decision-making. • Contributed to the development and tracking of key performance indicators (KPIs) to support product development and strategic decisions. • Performed ETL data from multiple sources into Qlik Sense and Qlik Cloud applications and utilised the Qlik Deployment Framework (QDF) environment to manage and streamline data workflows, enhancing efficiency and consistency in data handling. • Thrived in agile cross-functional teams, collaborating with business analysts, domain data experts, solution engineers, BI architects, and business stakeholders to achieve common objectives. Tools: Qlik Sense, Power BI, Visual Basic Code, Jenkins, Bitbucket, SQL, TeraData Studio.

Responsible for BI dashboard development, Analytical reports and apps using Qlik Sense and Power BI tools for customer business needs and help understanding business Insights for decisions making process.

Worked with customer project in a team to analyse data to perform sales and profitability analysis and create insightful visualization using qlik sense in cloud.

• Worked on different internal and external Power BI projects performing ETL/ELT - SQL Server Integration Services, have built or maintained data pipelines and expand ETL/ELT processes to load more data to SQL DB. • Created Pipelines in ADF using Linked Services/Datasets/Pipeline/ to Extract, Transform and load data from different sources like Azure SQL, Blob storage, Azure SQL Data warehouse and processing the data in In Azure Databricks. • Hands -on experience in Azure Cloud Services (PaaS & IaaS), Azure Synapse Analytics, SQL Azure, Data Factory, Azure Analysis services, Application Insights, Azure Monitoring, Key Vault, Azure Data Lake. • Define, design, and develop interactive dashboards and reports in Power BI for Invoice Analysis, Sales opportunity Analysis, Financial Statement Analysis to identify trends, data predictions and recommend process improvements to reduce inefficiencies and improve accuracy and automation of workflow and data transfers.