Murari Baikady

Project Description :

Creating data lake for the data from regional service centers involves collecting, storing, and organizing data from various spectrum ERP sources in a centralized repository. This specific requirement is to bring customer service program (CSP) data from 32 sites into data lake and made it available for business process leaders and data analyst for analysis and reporting needs.

• Designed the approach to get the data from spectrum in csv' files and loaded them into ADLSgen2. cleansed the data before moving to Dedicated SQL pool ( SQL server)
• Designed, developed and scheduled the data movement pipelines in azure synapse analytics, which includes data partitioning , removal of duplicates, data relationship check ( used synapse notebook for data cleaning work)
• The audit log tables are created to record the data quality issues along with iteration #, date and time stamp of the processing time and created the PowerBI reports.
• Developed a proof of concept in Azure stream analytics to consume fire alarm generated events in event hub , using tumbling window of 5 mins to load the records into bronze and Silver table.

Project Description :

The majority of deals go through the deal desk with various reasons for high price/discount variability. There are different attributes being considered for discounting and pricing across business units, as well as a lack of standardization in the discounting decisions. Price desk platforming is a data standardization and predicting the best discount % by customer and product/services. This initiative is yielding 10% increase in the win rate of the deal.

• Architected data model blueprints and integration pipelines, that underlays the end-to-end business processes as defined by the business and data domain owners. Used ADF , Azure Synapse analytics and stored data in dedicated SQL pool table.
• Created business data quality standards, validation rules in the staging area, data coverage check and reporting in Databricks, PySpark and PowerBI.
• Implemented the best practices in projects like partitioning, avoiding lazy evaluation, and proper use of delta caching for better performance.
• Implemented column-level security with grant-to-users, and row-level securities for persona-based access using predicate function and role-based access.
• Anchored the weekly business reviews with segment leaders to present the vision and value from the data. Visualization to depict the win-loss ratio of an opportunity and quotation.
• Designed internal process improvements to automate repetitive tasks, shortening data delivery times.
• Led the collaboration with various stakeholders like the finance team, Business leaders, and quotation managers to get the right quality of the master and transactional data and influenced them with quick proof of concepts (POCs).
• Led the team of data engineers and business analysts, whose primary role is creating data pipelines, maintaining data integrity, delineating the ERP data and business process.

Project Description :

The Existing data lake of Aviation is built on Greenplum , This project is to migrate data and business logic implemented in PostgreSQL to Azure cloud. The ETL jobs are to be migrated and scheduled in Azure ADF

• Formulated and piloted robust and scalable design for data warehouse model to incorporate slow-moving dimension and fact table tables for entire overhaul and component repair shops (6 overhaul shop and 10 component repair shops) – One stop shop place for all the repair data.
• The Consolidated data set optimized the cost of the data management by $1M per year by decommissioning the siloed data marts.
• Removed third party ETL tools, implemented the Azure data Factory integration with SAP HANA and OracleDB to move the data to into ZURE ADLS Gen1 and then to dedicated SQL(landing area , silver and gold area).
• Developed data model in dedicated SQL pool (MS SQL server) from all the engine service shops to support analytics initiatives and improve the delivery targets for Aviation customers, which includes stage, base and presentation data layer.
• Ingested data, Curated the data and developed published data set for supporting Labor Analytics to identify training opportunities, rework issues, shop KPI’s
• Ingested data, Curated the data and developed published data set for various scrap replacement scenarios (Used vs. New) to improve contract margins.
• Ingested data, Curated the data and developed a published data set to determine touch time and queue time for an equipment.
• Extensive data engineering to implement business logic and transformations into Postgres functions.
• Worked on Text mining on large unstructured data to derive reason and location of the defects in the high $ parts.
• Designed published data set for with all shops data – Single source of truth.

• Designed and implemented Purchased order and Advanced shipment notification related data integration between mainframe (sourcing application) to web-based supplier facing application using WebMethods and informatica.
• Designed the integration strategies, Created Technical, Functional and Mapping documents.
• Lead the User acceptance testing, where in I have given demo of full project to more than 50 outside suppliers of GE along with GE program Manager and functional leads.

• Enhanced and maintained 65 applications and more than 200 related integrations in informatica, WebMethods.
• Implemented innovative projects and saved more than $100K each year to customers in terms of efforts and time.
• Partnered with architecture & leadership team to drive strategy and standards