Data Processing Cheat Sheet 2026

The 30 highest-yield Data Processing facts, distilled from real exam questions. Print it, save it as a PDF, or study it here — free, no sign-up.

1. What is a 'checksum' used for during data transfer and processing? → Verifying data integrity by detecting errors or corruption
2. What is horizontal scaling in the context of big data systems? → Adding more machines to a cluster to increase processing capacity
3. When a data processing cycle fails midway, a 'checkpoint' mechanism allows the job to: → Resume processing from the last successfully completed checkpoint rather than from scratch
4. Which technique replaces sensitive data with realistic but fictitious values to protect privacy? → Data masking
5. Which normal form eliminates transitive dependencies in a relational table? → Third Normal Form (3NF)
6. Which validation rule ensures a field contains only alphabetic characters? → Data type check
7. Which algorithm is commonly used to sort large datasets stored on disk (external sorting)? → Merge sort
8. What is data consistency in data processing? → Data is the same across all systems and does not contradict itself
9. Which of the following is an example of unstructured data? → A free-text email message
10. What is Apache Hive used for? → Querying and managing large datasets stored in Hadoop using a SQL-like interface
11. What is a stored procedure in a DBMS? → A precompiled set of SQL statements stored and executed on the database server
12. What does 'data accuracy' mean in data quality terms? → Data correctly represents the real-world values it is intended to model
13. What is the purpose of Apache NiFi in data pipelines? → Automating data flow between systems with a visual, drag-and-drop interface
14. What is a view in SQL? → A virtual table based on the result of a SELECT query
15. Inquiring about database-stored information is sometimes referred to as → Field
16. A hash table achieves average-case O(1) time complexity for lookups because: → It uses a hash function to map keys directly to storage locations
17. The 'medallion architecture' in data lakes uses three cycle stages. In order, these are: → Bronze → Silver → Gold
18. What is data aggregation in ETL transformation? → Combining multiple values into a single summary value such as a sum or average
19. Which processing model does Apache Kafka primarily support? → Real-time event streaming and message queuing
20. What is the purpose of a staging area in ETL processing? → A temporary storage location where data is held between extraction and loading
21. What is a data pipeline? → A series of automated steps that move and transform data from source to destination
22. What does HDFS stand for? → Hadoop Distributed File System
23. In a MapReduce cycle, the 'shuffle and sort' phase occurs between: → The Map phase and the Reduce phase
24. What is a transaction in database processing? → A unit of work that is executed completely or not at all
25. Which data format is most commonly used for exchanging data between web services today? → JSON
26. What is the primary disadvantage of real-time stream processing compared to batch? → Higher system complexity and infrastructure cost to achieve low-latency guarantees
27. What does the SQL JOIN clause do? → Combines rows from two or more tables based on a related column
28. What is batch processing in data systems? → Collecting and processing large volumes of data at scheduled intervals
29. Which transformation converts data from one format to another, such as date formats? → Data conversion
30. What is stream processing in big data? → Continuously processing data as it arrives in real time