Datastage general overview.
Use Cases and Deployment Scope
It handles large business scale data. Since this an example of ETL software, it can handle large amount of data records especially banking information to our clients, migrating and generating them into new sets of information that we can utilize into a better tangible data for processing. It can generate alot of information based on a lot data dump that we can utilize for more business refined approach.
Pros
- Executing batch jobs (datastage jobs).
- Compiles a lot of datasets into a new set of information.
- It creates more refined information based on what we create and define from the job logics created.
Cons
- Parameter refreshes the variables that need to be refreshed all the time when a new job is deployed.
- Defining variables one by one takes a lot of time especially those are hard coded.
- Jobs are sometimes get hung.
- Sessions locks up the jobs.
Return on Investment
- It’s hard to say at this point, it delivers, but not quite as I expected. It takes a lot of resources to manage and sort this out (manpower, financial).
- Definitely, I don’t have the exact numbers, but given the data it processes, it is A LOT. So props to the developer of this application.
- Again, based on my experience, I’d choose other ETL apps if there is one that's more user-friendly.
Usability
Other Software Used
ACE, IBM Instana



