SAI KRISHNA

Project Overview: Data Modernization for Haldiram’s Supply Chain and Sales Analytics

Haldiram’s, a leading snack and sweets manufacturer, aimed to modernize its data infrastructure to support real-time analytics for supply chain optimization, sales trends analysis, and customer behavior insights. The project involved migrating on-premises legacy systems to Azure and implementing a robust data platform to enhance decision-making and operational efficiency.

Key Responsibilities:

• Designed and developed end-to-end data pipelines using Azure Data Factory (ADF) to extract, transform, and load (ETL) data from various sources into Azure Data Lake Storage (ADLS).
• Implemented data ingestion workflows to integrate structured and unstructured data from ERP, CRM, and POS systems.
• Set up and optimized Azure Synapse Analytics for data modelling and querying to support business intelligence reports.
• Defined schema and created Azure SQL tables in Azure using Sql queries.
• Deployed Azure Databricks to process large volumes of data for predictive analytics, including demand forecasting and customer segmentation.
• Ensured data security and compliance by implementing role-based access controls (RBAC), encryption, and Azure Key Vault for sensitive data.
• Collaborated with data scientists and analysts to develop machine learning models using Azure Machine Learning integrated with Databricks.
• Automated pipeline monitoring and failure notifications using Azure Monitor and Logic Apps.

Project Overview: Healthcare Data Integration and Analytics Platform
A leading healthcare provider sought to modernize its data infrastructure to improve patient care, streamline operations, and ensure compliance with healthcare regulations. The project involved creating a unified data platform to integrate patient records, clinical data, and operational metrics while enabling advanced analytics and real-time reporting.

Key Responsibilities:

• Designed and developed ETL pipelines using Azure Data Factory to ingest data from electronic health records (EHRs), IoT devices, and operational databases into Azure Data Lake.
• Built a healthcare data model in Azure Synapse Analytics to support queries for clinical insights and patient history analysis.
• Processed unstructured data, such as doctor’s notes and diagnostic images, using Azure Databricks and integrated them into the analytics pipeline.
• Ensured data security and compliance by implementing Azure Policy, data masking, and encryption in transit and at rest.
• Automated anomaly detection for patient vitals and operational data using machine learning workflows in Azure Machine Learning.
• Monitored data pipeline performance using Azure Monitor and set up alerts for failures or bottlenecks.

Project Overview: Azure-Based Application Support for a Python Web Application

A logistics company deployed a custom Python-based web application for real-time shipment tracking and order management. The application required ongoing support to ensure high availability, optimize performance, and resolve issues. The infrastructure was hosted on Azure, with integration for monitoring, scaling, and security.

Key Responsibilities:

• ● Monitored application health and performance using Azure Monitor and Application Insights, ensuring uptime and quick incident resolution.
• Automated log analysis and error detection using Python scripts integrated with Azure Log Analytics.
• Responded to user-reported issues, identified root causes, and implemented hotfixes in collaboration with the development team.
• Managed Azure App Service configurations, including scaling, SSL certificate updates, and custom domain settings.
• Set up and monitored Azure Functions for background tasks, such as periodic data syncing and email notifications.
• Wrote PowerShell and Python scripts to automate tasks like VM snapshots, resource tagging, and cost optimization.
• Ensured data security by managing Azure Key Vault for API keys and sensitive configurations.
• Documented troubleshooting guides, standard operating procedures (SOPs), and user guides for the application.