Failed once? That's when direction matters most. The IBM Big Data Fundamentals Technical Mastery Test v1 study guide from ExamTorrent turns hard work into progress — 34 practice questions with mistake-pointing simulation.
IBM 000-N32 Exam Overview:
| Certification Vendor: | IBM |
|---|---|
| Exam Name: | IBM Big Data Fundamentals Technical Mastery Test v1 |
| Exam Number: | 000-N32 |
| Exam Price: | $200 USD |
| Exam Duration: | 75 minutes |
| Related Certifications: | P2090-032 IBM Big Data Fundamentals v2 IBM Certified Specialist - Big Data |
| Real Exam Qty: | 34 |
| Certificate Validity Period: | 2 years |
| Exam Format: | Multiple Choice, Multiple Select |
| Available Languages: | English, Simplified Chinese, Japanese |
| Passing Score: | 65% |
| 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% | - Stream computing concepts - Real-time data processing - Architecture and development tools |
| IBM InfoSphere BigInsights | 35% | - Data processing and storage - Security and authentication - Architecture and components
|
| IBM Big Data Portfolio & Solutions | 15% | - Overview of IBM Big Data offerings - Integration and deployment scenarios - Comparison with competing solutions |
| Big Data Concepts & Architecture | 30% | - Big Data use cases and business value - Characteristics of Big Data (4 Vs) - Hadoop ecosystem fundamentals
|
000-N32 FAQ — Efficient Preparation Starts Here
No formal prerequisites; recommended basic knowledge of data processing and distributed systems Eligibility rules do change, so confirm the current requirements on the official page (official 000-N32 exam page) before booking.
75 minutes for 34 questions. Efficiency beats exhaustion: the ExamTorrent software version simulates the real test scene and scores your performance, so every practice hour moves you forward.
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Yes:
Training gives knowledge direction; practice gives it proof. Follow courses with the 34 practice questions for the IBM Big Data Fundamentals Technical Mastery Test v1 to measure real progress.
Delivery and payment are both safe: we support credit card payment, your information is protected by a strict system, and the product emails automatically within a minute of purchase — unlimited devices, 7*24 support if nothing arrives within 2 hours. If you fail the corresponding 000-N32 exam within 60 days of purchase, we refund in full: provide a scanned enrollment slip plus the official Score Report PDF within 2 days of the exam, processed within 7 days. Excluded: exams within 3 days of purchase, candidate names that don't match the payer, and free or expired products. Or exchange for two equal-value products free.
$200 USD per attempt, 65% to pass. Since a retake costs the full fee, prepare with direction: the 34 practice questions from ExamTorrent focus your effort where the exam points are.
The IBM Big Data Fundamentals Technical Mastery Test v1 is IBM's certification exam for IBM Big Data Fundamentals Technical Mastery, at the Mastery level. It validates applied skills employers hire for — a credential worth the effort. Related credentials include IBM Certified Specialist - Big Data, P2090-032 IBM Big Data Fundamentals v2.
The IBM Big Data Fundamentals Technical Mastery Test v1 blueprint covers 4 domains — including IBM InfoSphere Streams (20%), IBM InfoSphere BigInsights (35%), Big Data Concepts & Architecture (30%). The weightings are your efficiency map: heavy domains first. Every subtopic appears in the outline above.
Through the vendor's official registration channels:
The IBM Big Data Fundamentals Technical Mastery Test v1 is delivered Online proctored or onsite at Pearson VUE test centers; Exam is retired, replaced by P2090-032, so pick the arrangement that suits you when booking.
Yes — download the free IBM Big Data Fundamentals Technical Mastery Test v1 demo and judge the question quality before paying. Every purchase stays valid for 365 days with free updates throughout, renewable afterward at 50% off.
IBM Big Data Fundamentals Technical Mastery Test v1 Sample Questions:
Which of the following tools can be used to configure the InfoSphere Data Explorer environment (choose two) ?
- A. Data Explorer Virtual Desktop
- B. InfoSphere Data Explorer?s web-based interface
- C. Data Studio Web Console
- D. REST/SOAP APIs
Correct Answer: B,D 🗳️
What is HADOOP?
- A. Hadoop is framework capable of transforming raw, unstructured data into plain, regular data readable by traditional data warehouses.
- B. Hadoop is a universal Big Data programming language used to query large datasets.
- C. Hadoop is a framework that allows for the distributed processing of large data sets across clusters of computers using a simple programming model.
- D. Hadoop is a single-node file system used as a base for storing traditional formatted data.
Correct Answer: C 🗳️
Which of the following options is CORRECT?
- A. InfoSphere Streams submits queries to structured dynamic data.
- B. InfoSphere Streams submits queries to unstructured dynamic data.
- C. InfoSphere Streams submits dynamic data to pre-existing queries.
- D. InfoSphere Streams submits queries to structured static data.
Correct Answer: C 🗳️
Which of the following options are CORRECT (Choose two)?
- A. The Stream Processing Language provides a language that works with the Streams run-time framework to support streaming applications.
- B. Users can develop Streams applications using Data Studio Web Console, an Eclipse-based Integrated Development Environment (IDE).
- C. InfoSphere Streams perform complex analytics on data at rest.
- D. Users can deploy existing data mining scoring models in Streams applications for real time insights as opposed to running those models on persistent, or stored data.
Correct Answer: A,D 🗳️
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