Divya Gorantla

• Populating US healthcare data with financial resources, capital from the government, medical and academic capabilities, and characteristics of the patient population in SQL, constructing databases, and producing visuals with Python and Power BI.
• Evaluated large datasets, used data mining tools and statistical procedures.
• Collecting raw data from various sources, including databases, spreadsheets, and external APIs.
• Conducting exploratory data analysis (EDA) to identify patterns, trends, and outliers.
• Worked together with other departments to obtain the data needed, then analyzed the data to find trends, patterns, and abnormalities.
• Help with data transformation and purification to guarantee accuracy and data for reporting.
• Writing SQL queries to extract and manipulate data from relational databases.
• Working with databases like MySQL, PostgreSQL, or SQL Server.
• Coordinated a team of 30 students on a project to modify existing RDBMS, including coordinating the development of a framework to generate ad-hoc reports using enterprise data from Big Query.
• Created comprehensive reports based on MIS data to provide insights into process performance.
• Create, update, and expand standard operating procedures (SOPs) as well as BI tools.
• Preparing regular reports summarizing key performance indicators (KPIs) and data trends.
• Took part in conversations to get input and improve your data analysis.

<p>Populating US healthcare data with financial resources, capital from the government, medical and academic capabilities, and characteristics of the patient population in SQL<br>
Constructing databases<br>
Producing visuals with Python and Power BI<br>
Evaluated large datasets<br>
Used data mining tools and statistical procedures<br>
Collecting raw data from various sources, including databases, spreadsheets, and external APIs<br>
Conducting exploratory data analysis (EDA) to identify patterns, trends, and outliers<br>
Worked together with other departments to obtain the data needed, then analyzed the data to find trends, patterns, and abnormalities<br>
Help with data transformation and purification to guarantee accuracy and data for reporting<br>
Writing SQL queries to extract and manipulate data from relational databases<br>
Working with databases like MySQL, PostgreSQL, or SQL Server<br>
Coordinated a team of 30 students on a project to modify existing RDBMS, including coordinating the development of a framework to generate ad-hoc reports using enterprise data from Big Query<br>
Created comprehensive reports based on MIS data to provide insights into process performance<br>
Create, update, and expand standard operating procedures (SOPs) as well as BI tools<br>
Preparing regular reports summarizing key performance indicators (KPIs) and data trends<br>
Took part in conversations to get input and improve your data analysis</p>

<p>Designed ETL process using Pentaho Tool to load from Sources to Targets with Transformations<br>
Worked on Snowflake Schemas and Data Warehousing<br>
Worked within Agile methodologies using Jira Agile boards, managing sprints, and participating in ceremonies<br>
Developed Pentaho Big data jobs to load heavy volume of data into Amazon S3 data lake and then into Amazon Redshift data warehouse<br>
Actively participated in continuous improvement initiatives for data quality enhancement, providing valuable insights for process optimization<br>
Developed Ad-hoc reports and designed dashboard using splunk<br>
Managed and prioritized product backlogs, translating requirements into detailed user stories with acceptance criteria for development teams<br>
Migrated the data from Redshift data warehouse to Snowflake database<br>
Interpreting data and providing insights to support decision-making processes<br>
Collaborating with team members to understand business requirements<br>
Participating in team meetings and contributing to discussions<br>
Conducting ad hoc analysis as requested by team members or management<br>
Responding to specific data-related queries from stakeholders<br>
Created custom reports and dashboards within CRM platforms to track and visualize key metrics<br>
Used tools like Power BI or Tableau to enhance data visualization for stakeholders<br>
Build dimensional modelling, data vault architecture on Snowflake<br>
Loading the data from the different Data sources like (Teradata, DB2, Oracle and flat files) into HDFS using Sqoop and loading into Hive tables, which are partitioned<br>
Implemented data warehousing solutions using Snowflake, taking advantage of its cloud-based architecture<br>
Integrated Lambda functions with other AWS services, such as API Gateway and S3</p>

<p>Collecting and integrating data from various sources within the supply chain, including inventory systems, logistics databases, and procurement platforms<br>
Applying statistical models and machine learning algorithms for demand forecasting to improve inventory management and reduce stockouts<br>
Implementing algorithms and models to optimize transportation routes, reduce delivery times, and minimize transportation costs<br>
deploying code to leading cloud platforms, including Azure, GCP, and AWS, leveraging Docker/Kubernetes containers for efficient and scalable deployments<br>
Assessing the performance of machine learning models using appropriate metrics<br>
Validating models and adjusting parameters for optimal results<br>
Developing risk models to identify and mitigate potential risks in the supply chain, such as geopolitical events, natural disasters, or supplier financial instability<br>
Assessing the performance of machine learning models using appropriate metrics<br>
Validating models and adjusting parameters for optimal results<br>
Implemented Agile practices that are scalable to accommodate larger project teams and complex project landscapes<br>
deploying code to leading cloud platforms, including Azure, GCP, and AWS, leveraging Docker/Kubernetes containers for efficient and scalable deployments<br>
Applied sophisticated modeling methodologies such as VAR, Dynamic VAR, and Fourier Transformation for comprehensive data analysis<br>
Demonstrated expertise in containerization technologies, utilizing platforms like Docker to deploy and manage cloud services<br>
Successfully deployed code that scales to meet the demands of various cloud environments, accommodating dynamic workloads and user interactions</p>

<p>Developed Ad-hoc reports and designed dashboard using Splunk<br>
Worked with the management team and gathered the data from multiple data resources and then developed and designed ETL solutions as required<br>
Proficient in working with Customer Relationship Management (CRM) systems such as Salesforce, HubSpot, or other relevant platforms<br>
Conducted comprehensive data quality assessments, identifying discrepancies and implementing corrective measures to enhance the accuracy and reliability of datasets<br>
Developed reports and dashboards to visualize key performance indicators (KPIs) related to customer interactions and sales activities<br>
Writing ETL codes and SQL queries to check the desired results in the data-driven workflows and processing the transformation and loading<br>
Followed Waterfall methodology in the development process and participated in the daily Scrum meetings and carried sprints biweekly<br>
Developed automated test scripts using Selenium WebDriver with programming languages such as Python<br>
Developed reports and visualizations using BI reporting tools like Tableau and produced worksheets and dashboards<br>
implementation of data governance policies and frameworks to ensure standardized data management practices across the organization<br>
Performed the Data modeling to develop the mappings accordingly and involved with the Data Modelling team and provided suggestions in creating the data model<br>
Experience working with cloud-based data storage solutions, such as AWS S3, Azure Blob Storage, or Google Cloud Storage<br>
Utilized cloud services for data processing, transformation, and analysis<br>
Executed test cases directly within the qTest platform, recording test results and tracking test progress<br>
Designed and Developed Informatica Mappings from Scratch to Load the Data from Source System to Staging system and Warehouse System<br>
Writing ETL codes and SQL queries to check the desired results in the data-driven workflows and processing the transformation and loading<br>
Utilized Agile metrics (e.g., velocity, burn-down charts) to track team progress and provide insightful reporting to stakeholders<br>
Performed validation, quality checks, and audit count at various stages of the ETL process using data threshold validation check</p>