Este é o meu perfilContato pela CazVidEste perfil está escrito em inglês
Dilpreet
Data Analyst
Contato
Competências
Demonstrated experience with Operational analysis.
Demonstrated experience with Exploratory data analysis.
Demonstrated experience with Descriptive statistics.
Demonstrated experience with Trend analysis.
Demonstrated experience with KPI development.
Formação acadêmica
Resumo
Data Analyst open to new opportunities
Experiência
Data Analytics and Business Intelligence Instructor
Lead applied training in SQL, Python, Power BI Desktop and Service, Tableau, Microsoft Excel, data modelling, data warehousing, and business intelligence through project-based instruction.. Train 25–35 students per term on data extraction, cleaning, transformation, validation, dashboard design, DAX calculations, KPI development, and business analysis.. Design approximately 8–10 case studies per term covering sales, revenue, customer behaviour, operational bottlenecks, data quality, logistics, and management reporting.. Evaluate 10+ portfolio projects and dashboards per term, reviewing dataset structure, calculation logic, data models, visual accuracy, business interpretation, and presentation quality.. Coach students on technical interviews, SQL exercises, project walkthroughs, analytics case studies, problem framing, and data-supported recommendations.
Business Data Analyst
Integrated and analyzed approximately 25,000–50,000 monthly records from ERP, logistics, finance, sales, and operations systems using SQL, Microsoft Excel, Power Query, and Python.. Developed SQL extraction, transformation, and reporting-automation workflows, reducing manual reporting effort by 6–8 hours weekly.. Built and maintained 12+ recurring operational, finance, and logistics reports using SQL views, stored procedures, Excel dashboards, reporting datasets, and dimensional models.. Analyzed fulfilment time, order accuracy, shipment costs, revenue, logistics efficiency, and customer-order trends.. Supported 5–7 stakeholders across operations, finance, logistics, and management through performance summaries, ad hoc analysis, KPI reporting, and business-review presentations.. Documented KPI definitions, SQL logic, data sources, business rules, and transformation steps.