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IBM 000-N32 Exam Overview:
| Certification Vendor: | IBM |
|---|---|
| Exam Name: | IBM Big Data Fundamentals Technical Mastery Test v1 |
| Exam Number: | 000-N32 |
| Certificate Validity Period: | 2 years |
| Related Certifications: | IBM Certified Specialist - Big Data P2090-032 IBM Big Data Fundamentals v2 |
| Exam Format: | Multiple Select, Multiple Choice |
| Available Languages: | Japanese, Simplified Chinese, English |
| Exam Price: | $200 USD |
| Exam Duration: | 75 minutes |
| Passing Score: | 65% |
| Real Exam Qty: | 34 |
| Recommended Training: | IBM BigInsights and Streams Courses IBM Big Data Fundamentals Training |
| Exam Registration: | Pearson VUE Registration IBM Certification Portal |
| Sample Questions: | ![]() |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers; Exam is retired, replaced by P2090-032 |
| Pre Condition: | No formal prerequisites; recommended basic knowledge of data processing and distributed systems |
| Official Syllabus URL: | https://www.ibm.com/certify/exams/000-N32 |
IBM 000-N32 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| IBM InfoSphere Streams | 20% | - Architecture and development tools - Stream computing concepts - Real-time data processing |
| Big Data Concepts & Architecture | 30% | - Big Data use cases and business value - Characteristics of Big Data (4 Vs) - Hadoop ecosystem fundamentals
|
| IBM InfoSphere BigInsights | 35% | - Architecture and components
- Security and authentication |
| IBM Big Data Portfolio & Solutions | 15% | - Integration and deployment scenarios - Comparison with competing solutions - Overview of IBM Big Data offerings |
IBM 000-N32: The Questions Everyone Asks
No formal prerequisites; recommended basic knowledge of data processing and distributed systems Eligibility details like these are worth double-checking before you register — vendors revise them periodically, and the official exam page (official 000-N32 exam page) always has the current version.
The official IBM Big Data Fundamentals Technical Mastery Test v1 outline has 4 domains — the biggest include Big Data Concepts & Architecture (30%), IBM InfoSphere BigInsights (35%), IBM Big Data Portfolio & Solutions (15%). Those weightings are your study compass: the largest domains hide the most points. See the full outline above for every subtopic.
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The exam is offered Online proctored or onsite at Pearson VUE test centers; Exam is retired, replaced by P2090-032, so decide which arrangement suits you before picking a date.
Delivery first: the moment you pay, we send the download link and access details to your email within a minute — even on holidays — and the files install on unlimited computers; contact support if 2 hours pass with nothing. For refunds, the terms are explicit: take the corresponding 000-N32 exam within 60 days of purchase, and if you fail, submit a scanned enrollment slip plus the official Score Report PDF within 2 days of the exam for a full refund, processed within 7 days. Excluded: exams taken within 3 days of purchase, name mismatches between candidate and payer, and free or expired products. The alternative to a refund: two equal-value exam products free, with your original updates intact.
The pass mark is 65%, and the official fee is $200 USD. That fee resets to full price on every retake, so the real money-saver is preparation — run the 34 practice questions from BraindumpsIT until passing becomes routine, then book your seat.
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Classroom hours alone won't tell you if you're ready — the 000-N32 practice questions from BraindumpsIT will. Use them after the coursework to convert knowledge into exam performance.
The IBM Big Data Fundamentals Technical Mastery Test v1 is IBM's official exam for the IBM Big Data Fundamentals Technical Mastery certification, a Mastery-level credential. Candidates take it to validate real skill — and employers read it exactly that way. It also connects to related credentials such as IBM Certified Specialist - Big Data, P2090-032 IBM Big Data Fundamentals v2.
The exam gives you 75 minutes for 34 questions. The candidates who struggle aren't usually short on knowledge — they're short on pacing. Fix that before test day: set a time budget per question, practice moving past hard items without stalling, and rehearse full timed sessions in the BraindumpsIT engine until the clock stops being a factor.
IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:
Which of the following options is NOT CORRECT?
- A. Big data solutions are ideal when all, or most, of the data needs to be analyzed versus a sample of the data; or a sampling of data isn?t nearly as effective as a larger set of data from which to derive analysis.
- B. Big data solutions are ideal for Online Transaction Analytical Process (OLTP) environments.
- C. Big data solutions are ideal for iterative and exploratory analysis when business measures on data are not predetermined.
- D. Big data solutions are ideal for analyzing not only raw structured data, but semi- structured and unstructured data from a wide variety of sources.
Correct Answer: B 🗳️
In regards of InfoSphere Streams, Which of the following options is CORRECT?
- A. InfoSphere Streams is a powerful analytic computing platform capable of gathering large quantities of data, manipulating the data, and storing it on disk.
- B. InfoSphere Streams is an extract, transform, and load (ETL) platform that is capable of integrating small volumes of data across a wide variety of data sources and target applications.
- C. InfoSphere Streams is web administration graphical user interface (GUI) capable of setting up a secure communication channel to stream post-processed data from a Hadoop cluster into a relational database, such as IBM DB2.
- D. InfoSphere Streams is a powerful analytic computing platform capable of analyzing data in real time with micro-latency.
Correct Answer: D 🗳️
What is good fit for Hadoop Distributed File System (HDFS)?
- A. Applications requiring high throughput of data.
- B. Lots of small files.
- C. Applications requiring low latency data access.
- D. Multiple writers accessing the same file.
Correct Answer: A 🗳️
What are the ?4 Vs? that characterize IBM?s Big Data initiative?
- A. Variety, Versions, Velocity, Volatility
- B. Velocity, Volatility, Variety, Veracity
- C. Volume, Volatility, Velocity, Variety
- D. Veracity, Variety, Volume, Velocity
Correct Answer: D 🗳️
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