DP-900 Describe core data concepts Practice Question
A retail company operates an e-commerce website that processes customer orders (insert, update, delete) throughout the day. The same company also runs reports on sales trends at the end of each quarter. Which type of data processing workload does the order processing represent?
⚠ Common exam trap
Test-takers frequently confuse 'analytical processing' (OLAP) with 'transactional processing' (OLTP) because both involve databases, but OLAP is for read-heavy, aggregated queries on historical data, not for the write-heavy, individual row operations of order management.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
B) Transactional processing (OLTP)
Order processing involves inserting, updating, and deleting individual customer orders in real time as they occur. This is the classic definition of an Online Transaction Processing (OLTP) workload, which is optimized for high-volume, low-latency transactions that maintain ACID (Atomicity, Consistency, Isolation, Durability) properties. The e-commerce website requires immediate data consistency for each order, which is the hallmark of transactional processing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A) Batch processing
Why it's wrong here
Batch processing does not fit this scenario because it groups data into finite, pre-scheduled chunks and processes them together, typically at off-peak times (e.g., nightly inventory reconciliation or payroll runs). In contrast, order processing on an e-commerce website must handle each transaction as it occurs, immediately updating stock levels, payment status, and order history. A delay caused by batch collection would create inconsistency, overselling, or poor user experience. The defining characteristic of this workload is real-time, event-driven, single-record updates — the antithesis of batch.
When this WOULD be correct
A question describing a scenario where a company processes end-of-month payroll for all employees by running a scheduled job that calculates salaries and generates pay slips in one go would make batch processing (option A) the correct answer.
- ✓
B) Transactional processing (OLTP)
Why this is correct
Order processing on an e-commerce site is the canonical example of OLTP: each click, cart update, and checkout triggers immediate INSERT, UPDATE, and DELETE operations against a normalized database. These transactions are short-lived, ACID-compliant, and require high concurrency and low latency to keep inventory and orders consistent. OLTP is optimized for fast, atomic writes and point lookups, not for scanning large historical datasets. Thus, the correct workload type for processing individual orders in real time is OLTP.
- ✗
C) Analytical processing (OLAP)
Why it's wrong here
OLAP is the wrong classification because it describes workloads built for complex analytical queries and aggregations over large volumes of historical data — for example, quarterly sales reports, product trend analysis, or star-schema cubes. While an e-commerce platform may feed operational data into an OLAP system, the act of processing an individual order is not analytical. OLAP queries are read-intensive, long-running, and typically use columnar storage and pre-aggregated measures, which would be wasteful and unsuitable for capturing each real-time transaction. The order processing pipeline itself is transactional, not analytical.
When this WOULD be correct
A question describing a workload that runs complex queries on large volumes of historical sales data to identify trends, such as 'Which processing type is used for quarterly sales trend analysis?' would make OLAP correct.
- ✗
D) Stream processing
Why it's wrong here
Stream processing is not the correct label here because it refers to continuous, non-blocking computation over unbounded data flows, such as clickstreams, IoT sensor readings, or live financial tickers, often using engines like Apache Kafka, Flink, or Spark Streaming. Although an e-commerce site might generate stream-like events, the actual order processing (validating payment, reducing inventory, creating the order record) is a discrete, transactional operation that must commit atomically to a database. Stream processing typically tolerates loose consistency or uses event-time windows, whereas OLTP demands strict ACID guarantees for each order. Therefore, order processing is best described as OLTP, not stream processing.
When this WOULD be correct
Stream processing would be correct if the question described a scenario where the company needs to analyze real-time clickstream data from the e-commerce website to detect fraud or personalize offers as users browse, without storing each event as a persistent record.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The DP-900 exam frequently reuses these exact scenarios with slightly different constraints.
✓B) Transactional processing (OLTP)Correct answer▾
Why this is correct
Order processing on an e-commerce site is the canonical example of OLTP: each click, cart update, and checkout triggers immediate INSERT, UPDATE, and DELETE operations against a normalized database. These transactions are short-lived, ACID-compliant, and require high concurrency and low latency to keep inventory and orders consistent. OLTP is optimized for fast, atomic writes and point lookups, not for scanning large historical datasets. Thus, the correct workload type for processing individual orders in real time is OLTP.
✗A) Batch processingWrong answer — click to see why▾
Why this is wrong here
Order processing involves individual insert, update, and delete operations on customer orders, which are typical of transactional processing (OLTP), not batch processing. Batch processing handles large volumes of data in scheduled, offline batches, not real-time transactions.
★ When this WOULD be the correct answer
A question describing a scenario where a company processes end-of-month payroll for all employees by running a scheduled job that calculates salaries and generates pay slips in one go would make batch processing (option A) the correct answer.
Why candidates choose this
Candidates may confuse batch processing with any data processing that occurs in groups, but the key distinction is that batch processing is scheduled and not real-time, whereas order processing here is continuous and interactive.
✗C) Analytical processing (OLAP)Wrong answer — click to see why▾
Why this is wrong here
Order processing involves frequent insert, update, and delete operations on individual records, which is characteristic of OLTP, not OLAP. OLAP is used for complex queries and aggregations on historical data, not for day-to-day transaction handling.
★ When this WOULD be the correct answer
A question describing a workload that runs complex queries on large volumes of historical sales data to identify trends, such as 'Which processing type is used for quarterly sales trend analysis?' would make OLAP correct.
Why candidates choose this
Candidates may confuse 'reports on sales trends' (which is OLAP) with the order processing itself, mistakenly thinking that because the company runs reports, the entire workload is analytical.
✗D) Stream processingWrong answer — click to see why▾
Why this is wrong here
Order processing involves individual insert, update, and delete operations on customer orders, which are typical of transactional processing (OLTP), not stream processing. Stream processing handles continuous, real-time data flows (e.g., sensor data, clickstreams) and is not designed for discrete record-level transactions.
★ When this WOULD be the correct answer
Stream processing would be correct if the question described a scenario where the company needs to analyze real-time clickstream data from the e-commerce website to detect fraud or personalize offers as users browse, without storing each event as a persistent record.
Why candidates choose this
Candidates may confuse 'real-time' order processing with stream processing, not realizing that OLTP handles real-time transactions on persistent data, while stream processing deals with transient event streams without persistent storage.
Analysis generated from the official DP-900blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
OLTP
OLTP (Online Transaction Processing) is a data processing system designed to manage and record high volumes of real-time transactions, such as bank deposits or online purchases, quickly and reliably.
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