Project: Risk Reporting & Group Functions (CEDA)
Environments: Azure, Scala, Spark, Parquet, Apache Kylin, Databricks
Description: Client started building reporting layer over data lake. Complexity of the project involves any query need to be sub-second response, implement security and all need to be driven from cloud.
Project: FinRisk Ware House & Denali (CT)
Environment: JAVA, Hadoop, MapReduce, HBase, Hive, Sqoop, Avro, Spark, Oozie, Control M, Autosys
Description: Client started off loading DW by augmenting Hadoop Cluster. As part of this project they want to build reusable utilities to ingest and transform across multiple source systems. Complexity of the project involves discreet systems to standardize ingestion & support required transformations and provide data for Machine Learning purposes.
Project: Storage Re-Engineering
Environment: JAVA, Hadoop, MapReduce, HBase, Hive, Sqoop, Avro
Description: Client started off loading DW by augmenting Hadoop Cluster. As part of this project they want to reduce cost involved with data marts by reducing the number of instances & providing faster access to data using In-memory store.
Project: Audience Measurement
Environment: JAVA, Hadoop, MapReduce, HBase, Hive, Sqoop, Oozie
Description: Belgacom started implementing Hadoop Cluster to identify the viewership information for TV Subscribers. Media creators have questions about whether they are reaching the right audience on the right device at the right time. Second-by-second household viewing data, harvested from millions of TV households, has the potential to revolutionize the way TV stations sell advertising, schedule programming and place on-air promotions. This data is huge and ever increasing with each passing second, a Big Data system is needed to understand and derive insights from this enormous data.
Project: Data Fabric
Environment: JAVA, Hadoop, Sqoop, Avro, Map-Reduce
Description: UHG willing to implement data warehouse on BigData platform. In future once data is available at single place they will be running Analytics on the same. And also all provisioning of data to different data warehouses will be achieved by Data Fabric itself.
Project: Audience Measurement System
Environment: JAVA, Hadoop, Sqoop, HBase, Hive, Flume, PIG, Map-Reduce
Description: Telenet started implementing Hadoop Cluster to identify the viewership information for TV Subscribers. Media creators have questions about whether they are reaching the right audience on the right device at the right time. Second-by-second household viewing data, harvested from millions of TV households, has the potential to revolutionize the way TV stations sell advertising, schedule programming and place on-air promotions. This data is huge and ever increasing with each passing second, a Big Data system is needed to understand and derive insights from this enormous data.
Project: Master Use Royalty Upgrade
Client: Warner Music, London
Environments: Oracle 10g & 11g, ASP.net, Silver Light
Description: MUR, handles International Royalty between different affiliates of Warner Music or any 3rd Party companies. Existing Application is unable to process Royalty Statements for Sales reported from different distributional channels across world due to exponential increase in sales. During Process of Upgrade its planned to upgrade DB Character set. Using Agile Methodology this project is getting implemented to have smooth migration into new application.
Project: Data Warehouse – Migration of Distribution Channel to Arvato.
Environment: Oracle 10g
Client: Warner Music, London
Description: Warner Music UK, Physical Products distribution has been switched from Cinram to Arvato during 2011. During switch over different applications interfaces, which used to ensure supply chain management need to be re-written to support new distribution channel.
Project: DIP – Performance Improvement
Environment: Oracle 10g, ASP.NET, Power Builder
Client: Warner Music, London
Description: WMG planned to make all the sales processing in central DB and distributing the amount to the DSPs. With this centralization more burden will be on server to process more sales transaction files. Hence, planning to reduce the process file time to run more files in less time. Have done tuning work on the existing code.
Project: WARS – Warner Artist Royalty System & MUR – Master Use Royalty
Client: Warner Music, London
Environments: Oracle 11 & 10g, ASP.NET, Power Builder
Description: WARS, handles creation of statements & statement summaries for all artists who are in contract with WMG. Those statement or statement summary contains about the royalty earnings, recoupable costs, final amount payable to artist etc.. Royalty calculations are based on sales on catalogues created by the artists. Sales information comes to application from different systems. This application has got around 40 instances all around the globe.
MUR, handles International Royalty between different affiliates of Warner Music or any 3rd Party companies.
Project: TPFC (Third Party Fee Central)
Client: CFC International – India Services
Environments: ASP.NET, .NET, Java Script, MS SQL Server
Description: Countrywide Financials is US leading Mortgage Banking. Before Loan gets approval, applicants Credit History Report, Land appraisal Report will be created. For generating these reports there are many third party vendors. They charge money for the same. A web portal is created to keep track of all third party vendors payments, applicants applicable charges, etc.. for each & every loan application.
Project: ZSR
Environments: ASP.NET, .NET, Java Script & PDF (Acrobat), Adobe Document Server
Client: CCH (A WoltersKulwer Company)
Description: CCH is one of the leading website for the filling of sales & use tax returns in US (all states) for their clients.
Description: Developed software for in-house to streamline all departments’ (Marketing, Production, Inventory, Purchase & module for Salary generation) process flow & to improve productivity. In Marketing module, gives suggestions about prices to Quote. It automatically picks up Engineering Drawings related to that Particular offer & helps user to create offers with zero delay for collecting data. In Production Module, it gives suggestions for engineers regarding Production Planning and calculates time required for manufacturing product. It helps to create bill of material for products, which must to be manufactured. It keeps tracks of manufacturing of products. In Inventory module, it keeps track of raw material and gives value of stocks in stores at any instance. It generates automatic indent for shortage of materials. In Purchase module, it collects indents raised from stores and production departments and suggests best vendor. It prepares reports like Vendor Rating. In Salary module, it prepares monthly salary sheets & Pay slips and keep track of expenditures for statutory provisions. It keeps track of Attendance and OT’s.
Apache Kylin
Databricks
Core Java
Scala
Python
Micro Services
Oracle
MS SQL
Azure
Hadoop
Oozie
Sqoop
MapReduce
Hive
PIG
HBase
Cassandra
Kafka
Storm
Flume
Impala
Solr
Toad
Eclipse
IntelliJ
Shell Script
C#
ASP & ASPnet
Machine Learning
Cloudera Certified Developer for Apache Hadoop
Azure AI Fundamentals Certified
Certified Engineer by UBS
Azure Data Fundamentals Certified
Azure Architect Technologies
Azure Fundamental Certified
Expert Engineer by JP Morgan Chase
Datastax Certified Java Developer for Apache Cassandra
Cloudera Certified Developer for Apache Hadoop