DEVENDRA RANA

Design and build advanced data solutions using Azure PaaS services to enhance data visualization. Assess the current production state of the application and evaluate the effect of new implementations on existing business processes. Develop pipelines in ADF that extract, transform, and load data from sources such as Azure SQL, Blob storage, Azure SQL Data Warehouse, write-back tools, and others. Create Spark applications using PySpark and Spark-SQL for data extraction, transformation, and aggregation from multiple file formats to uncover customer usage patterns. Constructed supply chain pipeline using Talend and azure data factory and created relevant KPIs to visualize on Power BI, thereby improving the processing time by 85%.

Responsible for Visual Analytics, Reporting, and Data Engineering for one of the most highly focused projects, working directly with a Senior Vice President of UHG US. Developed SQL scripts for query automation to remove the need for human interaction when executing SQL queries, this increased the volume and accuracy of queries being run by 64%. Created a data pipeline to consume and store 500TB of raw data weekly in Azure. Created visualizations and reports to present data insights, enabling stakeholders to make informed business decisions. Worked on Tableau, Power BI, Big data environment (Hive, spark, Sqoop, Python, SAS, Shell script), SAP Crystal reports, Talend, automation of scripts, machine learning models for new eligible members and NLP for data cleaning, text Classification, missing values, data standardization (using record linkage, fuzzy matching) and prediction. Address parsing, distance calculation using latitude, longitude (Geopy library). Used Azure Data Factory, T-SQL, Spark SQL, and U-SQL Azure Data Lake Analytics to extract, transform, and load data from various sources into Azure data storage services. Ingest data into one or more Azure services, including Azure Data Lake, Azure Storage, Azure SQL, and Azure DW, and process the data in Azure Databricks.

A Banking Website using HTML, CSS, JavaScript, and using SQLite databases, NODE JS that stored the information about the users and the transactions such as credit, debit performed by the users.