Indu Priya Email and Phone Number

• Created and run jobs on AWS cloud to extract transform and load data into AWS Redshift using AWS Glue, S3 for data storage and AWS Lambda to trigger the jobs • Used AWS data pipeline for Data Extraction, Transformation and Loading from homogeneous or heterogeneous data sources and built various graphs for business decision-making using Python Matplot library. • Used clustering technique K-Means to identify outliers and to classify unlabeled data. • Worked on large SQL Datasets, to create new Power BI Reports and Dashboard• Created DAX functions using Filter, Mathematical, Logical, Statistical and Date Time functions to use in Power BI reports.• Performed ad-hoc reporting, creating multiple new reports in Power BI for the team based on understanding the requirement of the users.• Created a spatial database for the aforementioned GISs for use in ArcGIS Online.• Implemented using Machine Learning techniques with Python Pandas and Scikit-learn packages. • Contributed in building Machine Learning models with scikit-learn library in Python, like Logistic Regression model, SVMs model, Random Forest model, and Naive Bayes model.• Built on-demand Unit Price comparison data request and scheduled the report, for business analysis, management decision using Power BI.• Analyzed sales data using Transact SQL Scripting (T-SQL) Queries, Joins, Views, Stored Procedures and Common Table Expressions for the data available in SQL Server database.• Identified the dimension, fact tables and designed the Data Warehouse using Star schema.• Configured the SSIS Packages using Environment Variables for Dynamic Selection of Development and Production Environment.• Created and configured Dimensions, Attributes and Hierarchies using SQL Server Analysis Services (SSAS).• Created Business Power BI Reports using the Tabular SSAS models.• Designed and implemented Dashboards and Scorecards with business KPIs.

• Performed data analysis and data profiling using complex SQL Scripting and involved in Data mapping specifications to create and execute detailed system test plans. • Implemented machine learning model with Python Scikit- learn. • Superintended usage of Python NumPy, SciPy, Pandas, Panda SQL, Matplot, Stats packages to perform dataset manipulation, data mapping, data cleansing and feature engineering. Built and analysed datasets using R and Python.• Configured the SSIS Packages using Environment Variables for Dynamic Selection of Development and Production Environment. • Analysed existing internal data and external data, worked on entry errors, classification errors and defined criteria for missing values. • Performed data analysis and data profiling using complex SQL. • Performed network traffic data analysis, prevented any anomalies in enterprise’s network and provided recommendation.• Built forecasting and statistical models and integrated data from multiple sources to optimize efficiency and quality.• Enhanced productivity by 35% through problem-solving and debugging issues using Excel, Python, SQL queries, Tableau and Looker • Developed complex stored procedures, triggers, cursors, tables, indexes, constraints, views and other SQL joins for dashboard applications.• Adept at relational database structures, dimensional models, ETL, and data de-normalization• Created views in Tableau Desktop that were published to the internal team for review and further data • Performed analysis and customization using filters and actions • Analyzed large data using Excel (lookup, pivot tables, charts) • Analyzed the data using statistical features in Tableau to develop Trend Analysis reports. • Experienced in all project phases during Agile/SCRUM Methodologies• Performed analysis and presented results using SQL, Excel, and Visual Basic scripts. • Involved in testing the SQL Scripts for report development, Tableau reports, Dashboards, Scorecards.

• Analysed customer data (credit history and income statements) and created a new credit risk rating model which brought down the default rate by 50%. • Involved in building the ETL architecture and Source to Target mapping to load data into Data warehouse from multiple sources. • Interacted with other data scientists and architected custom solutions for data visualization using tools like tableau.• Performed statistical analysis of experimental design and analysis (DOE) using Python and data visualization using in-built Python functionalities such as Matplotlib. • Used scientific Python functionalities such as NumPy, Pandas, Seaborn, Plotly, Machine Learning, and Tensor flow for data structures, matrices and mathematical problems for and statistical modelling. • Collected, analysed, and interpreted raw data from various websites and utilized web scraping techniques to extract and organize general and competitor data. • Transformed raw data into SQL Developer database tables and created custom-made ETL jobs through Talend to prepare unruly data for machine learning and decision making.• Developed models in data and making predictive analysis through Regression analysis. • Used Power BI to collect and process data from internal and external systems to create reports and set access levels for individual users and specific dashboards for stakeholders based on information sensitivity. • Created and designed databases by identifying entities, attributes, relations, and data insertion using Microsoft SQL Server with SQL Server Management Studio to implement database system. • Provided software solutions for data preparation, data quality, data integration, application integration and data management through Extract, Transform and Load using Talend. • Participated in solutions design against business requirements and QA Verification phase to support the QA team. • Built data pipelines with ETL tools such as Talend and built business reports with Tableau.

• Worked with Data Modelling team to create Logical/Physical models for Enterprise Data Warehouse.• Prepared data quality criteria and governance for Data Warehousing Application.• Worked on data governance for improving data quality.• Developed and implemented BI solutions utilizing Tableau and SQL.• Assisted ETL team to define Source to Target Mappings.• Designed and developed complex active reports and dashboards with different data visualizations using Tableau desktop on customer data.• Used SAS for pre-processing data, SQL Scripting, and data analysis, generating reports, graphics and statistical analysis.• Developed Data Migration and Cleansing rules for the Integration Architecture (OLTP, ODS, DW).• Developed data mapping documents between Legacy, Production, and User Interface Systems.• Tested the source data for data completeness and data correctness.• Created various PL/SQL stored procedures for dropping and recreating indexes on target tables.• Created the ETL process that loaded the data into target database after performing all the transformations according to the business requirements.• Developed ETL packages with different data sources (SQL Server, Flat Files, Excel source files, XML files etc.) and loaded the data into target tables by performing different kinds of transformations using SQL Server Integration Services (SSIS) and T-SQL.• Developed different types of Tabular Reports, Matrix Reports (Cross Tab or Pivot), Chart and Graphs reports using the SSRS reporting as per the user's requirements and deployed in report server.• Used Unix Shell Scripting for automating logs, for user created table backups and for checking daily log.• Created filters and calculated sets for preparing dashboards and worksheets in Tableau.• Generated periodic reports based on the statistical analysis of the data from various time frame and division using SQL Server Reporting Services (SSRS).