IBM Db2
by IBM
Many core systems in banking, insurance and manufacturing still keep their transactional records in IBM Db2 tables and views. A Connect Anything connector reads those tables over SQL on a schedule, so policy, account or order history from the mainframe or distributed Db2 can sit in the Lake beside newer applications without exposing the production database to analysts.
- Category
- Cloud & Data Platforms
- Type
- Database
- Interface
- database interface
- Built with
- Connect Anything
- Credentials
- Username and password
- Docs
- IBM Db2 API docs
02Data
What you can sync.
- Sql query results
- Tables
- Views
Load IBM Db2 sql query results into your Lake and model it in the Warehouse with the rest of your stack.
Need more? Name any other IBM Db2 data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- A username and password
IBM Db2 uses a username and password. You add the credentials once, when the AI asks for them, and it tells you where to create them in IBM if you need help.
04Questions
Questions you can answer.
Once IBM Db2 data is in your Lake, ask an AI Mind in plain words or build the answer in DataPrism BI.
- Do monthly account balances in Db2 reconcile with the totals posted to the general ledger?
- Which customers appear in the Db2 policy tables but are missing from the CRM?
- How have order volumes recorded in the legacy Db2 system changed since the new platform went live?
- Which Db2 tables have stopped receiving new rows, suggesting a batch job has stopped?
05How it works
How it works in DataMind.
-
Pick IBM Db2.
Open Lake, pick IBM Db2 in the source picker and name the connection. Connect Anything opens with a ready prompt that points the AI at the IBM Db2 API docs.
-
Answer a few questions.
The AI reads the IBM Db2 documentation, then asks which credentials you will use, which data to sync (for example sql query results and tables), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
The connector agent writes a Python connector for IBM Db2, tests it against the live API and shows you sample rows. Then the data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
06Pairs
Works well with IBM Db2.
Sources teams join with IBM Db2 in the Warehouse, each one connected the same way.
-
SAP S/4HANA Reconcile transactions held in Db2 with financial postings in S/4HANA after period close. -
Salesforce Sales Cloud Match customer and contract records in Db2 with Salesforce accounts to find gaps between core systems and the front office. -
IBM MQ Compare messages waiting on MQ queues with transactions committed in Db2 to find where processing stalls.
