Abinitio Scenario Based Questions

Abinitio is a popular data integration and manipulation tool used in the IT industry. It is widely used for extracting, transforming, and loading (ETL) data from various sources into a data warehouse. As Abinitio is extensively used in data processing, it is crucial for professionals to be well-versed in handling different scenarios that may arise during the ETL process. To help you prepare for Abinitio interviews or enhance your knowledge in this area, we have compiled a list of scenario-based questions that commonly come up in interviews.

See these Abinitio scenario based questions

1. What is the difference between continuous and batch graph in Abinitio?
2. How can you handle duplicate records while loading data using Abinitio?
3. Explain the difference between “rollup” and “scan” in Abinitio.
4. What is the role of the “lookup” component in Abinitio?
5. How can you handle data partitioning in Abinitio?
6. What is the significance of a “join” component in Abinitio?
7. How can you handle exceptions in Abinitio?
8. Explain the concept of “reformat” in Abinitio.
9. What is the purpose of the “rollup” component in Abinitio?
10. How can you handle data validation in Abinitio?
11. What is the use of the “scan” component in Abinitio?
12. Explain the concept of “lookup” caching in Abinitio.
13. How can you handle data sorting in Abinitio?
14. What is the role of the “partition by key” component in Abinitio?
15. Explain the concept of “filter by expression” in Abinitio.
16. How can you handle data merging in Abinitio?
17. What is the significance of the “dedup sort” component in Abinitio?
18. How can you handle data aggregation in Abinitio?
19. Explain the concept of “replicate” in Abinitio.
20. What is the purpose of the “join with reformat” component in Abinitio?
21. How can you handle data cleansing in Abinitio?
22. What is the role of the “gather” component in Abinitio?
23. Explain the concept of “lookup match” in Abinitio.
24. How can you handle data enrichment in Abinitio?
25. What is the significance of the “normalize” component in Abinitio?
26. How can you handle data comparison in Abinitio?
27. Explain the concept of “rollup with merge” in Abinitio.
28. What is the purpose of the “unordered” component in Abinitio?
29. How can you handle data profiling in Abinitio?
30. What is the role of the “scan with rollup” component in Abinitio?
31. Explain the concept of “partition by expression” in Abinitio.
32. How can you handle data masking in Abinitio?
33. What is the significance of the “reformat with merge” component in Abinitio?
34. How can you handle data summarization in Abinitio?
35. Explain the concept of “lookup range” in Abinitio.
36. What is the purpose of the “replicate with merge” component in Abinitio?
37. How can you handle data profiling in Abinitio?
38. What is the role of the “unordered with rollup” component in Abinitio?
39. Explain the concept of “partition by range” in Abinitio.
40. How can you handle data validation in Abinitio?
41. What is the significance of the “reformat with merge” component in Abinitio?
42. How can you handle data summarization in Abinitio?
43. Explain the concept of “lookup range” in Abinitio.
44. What is the purpose of the “replicate with merge” component in Abinitio?

These scenario-based questions will help you gain a deeper understanding of Abinitio and its various components. Familiarizing yourself with these questions and their answers will not only prepare you for interviews but also enhance your expertise in using Abinitio for data integration and manipulation. Remember to practice these questions and customize your answers based on your experience and knowledge. Good luck!