Project 1 : Making sense of financial data
Industry : Financial Services
Problem Statement : Extract value from multiple sources & varieties of data in the financial domain
Description : In this project you will learn how to work with disparate data in the financial services domain and come up with valuable business insights. You will deploy IBM InfoSphere DataStage for the entire Extract, Transform, Load process to leverage it for a parallel framework either on-premise or on the cloud for high performance results. You will work on big data at rest and big data in motion as well.
- Creating DataStage jobs for ETL process
- Deploying DataStage Parallel Stage Editor
- Data Partitioning for getting consistent results
Project 2 : Enterprise IT data management
Industry : Information Technology
Problem Statement : Software enterprises have a lot of data and this needs to made sense of in order to derive valuable insights from it
Description : This project involves working with the data warehouse existing in a company deploying the IBM DataStage onto it for the various processes of extract, transform, and load. You will learn how DataStage manages high performance parallel computing. You will learn how it implements extended metadata management and enterprise connectivity. This also includes combining heterogeneous data.
- Enforce workload & business rules
- DataStage deployed on heterogeneous data
- Integrating real-time data at scale.
Project 3 : Medical drug discovery and development
Industry : Pharmaceutical
Problem Statement : A pharmaceutical company wants to speed the process of drug discovery and development through using ETL solutions.
Description : This project deals with the domain of drug molecule discovery and development. You will learn how DataStage helps to make sense of the huge data warehouse that resides within the pharmaceutical domain which includes data about patient history, existing molecules, and the effect of the existing drugs and so on. The ETL tool DataStage will help to make the process of drug discovery that much easier.
- Combining various types of data with ETL process
- Converting the data and transferring it for analysis
- Making the data ready for visualization & insights.
Project 4 : Finding the oil reserves in ocean
Industry : Oil and Gas
Problem Statement : Finding new oil reserves is a very herculean task. There are huge amounts of data that need to be parsed in order to find where oil exists in the ocean. This is where there is a need for an ETL tool like DataStage.
Description : This project deals with the process of deploying ETL tool like Datastage to parse petabytes of data for discovering new oil. This data could be in the form of geological data, sensor data, streaming data and so. You will learn how DataStage can make sense of all this data.
- Working with cloud or on-premise data
- Deploying DataStage for static or streaming data
- Converting data into the right format for analysis