Exam Name: Foundations of IBM Big Data & Analytics Architecture V1
Certification Provider: IBM
Corresponding Certification: IBM Certified Solution Advisor
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IBM C2090-136 Exam Overview:
| Certification Vendor: | IBM |
|---|---|
| Exam Name: | Foundations of IBM Big Data & Analytics Architecture V1 |
| Exam Number: | C2090-136 |
| Related Certifications: | IBM Big Data Engineer certifications IBM Data Science certifications |
| Available Languages: | English |
| Exam Format: | Multiple choice, Scenario-based questions |
| Recommended Training: | IBM Big Data and Analytics training courses |
| Exam Registration: | IBM Certification Portal |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Computer-based exam (online proctored or test center depending on region and IBM testing partner) |
| Pre Condition: | No formal prerequisites, but familiarity with data management and analytics concepts is recommended. |
| Official Syllabus URL: | https://www.ibm.com/certify |
IBM C2090-136 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| IBM Big Data Ecosystem | - IBM InfoSphere components and data integration tools - IBM BigInsights overview and Hadoop ecosystem integration - IBM Streams for real-time analytics |
| Big Data Fundamentals | - Traditional data systems vs distributed data systems - Characteristics of big data (volume, velocity, variety, veracity) |
| Big Data Architecture | - Processing frameworks (batch and streaming paradigms) - Distributed storage concepts (HDFS and object storage principles) - Data ingestion pipelines and integration patterns |
| Data Governance and Security | - Data privacy, compliance, and access control principles - Data governance frameworks and metadata management |
| Analytics and Data Processing | - Data mining and statistical analysis concepts - Machine learning workflow basics - Descriptive, predictive, and prescriptive analytics |
C2090-136 Exam: Answers Before You Buy
Fees and scoring scales are set by IBM and published on its official pages; verify the current details before registering.
The written refund policy applies. Take the IBM Foundations of IBM Big Data & Analytics Architecture V1 exam within 60 days of purchase, and if you do not pass, Lead1Pass refunds you in full. The policy does not apply if the exam is taken within 3 days of purchase, if the exam was never actually taken, or to free materials or expired orders, and the candidate name must match the payer name. Submit a scan of your enrollment slip and the official Score Report PDF within 2 days of the exam; claims are processed within 7 days. Alternatively, exchange for two free exam products of equal value and keep your original update service. Orders arrive by email within 1 minute — contact support if nothing arrives within 2 hours.
Computer-based exam (online proctored or test center depending on region and IBM testing partner) Registration for the IBM Foundations of IBM Big Data & Analytics Architecture V1 exam is handled through these official channels:
After booking, your Lead1Pass practice questions arrive by email within 1 minute — preparation can begin the same day.
The C2090-136 exam is a IBM certification exam validating the skills in the IBM Foundations of IBM Big Data & Analytics Architecture V1 syllabus shown above. It counts toward these credential paths: IBM Data Science certifications, IBM Big Data Engineer certifications. Candidates at many career stages take it in 2026 to demonstrate verified capability. Lead1Pass prepares you with 60 practice questions in PDF, Desktop Test Engine, and Online Test Engine formats.
Everything, in one purchase: 60 practice questions for the IBM Foundations of IBM Big Data & Analytics Architecture V1 exam in three formats — a printable, expert-prepared PDF with instant download; a Desktop Test Engine for Windows that simulates the real exam with two practice modes and works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. You also receive a free demo, 365 days of free updates from a team that keeps innovating on the material, a 50% renewal discount afterward, unlimited installations, and considerate pre-sale and after-sale service.
Question counts and time limits are published by IBM; check the official exam page for current details.
No formal prerequisites, but familiarity with data management and analytics concepts is recommended. Since policies evolve, confirm the current requirements on the official IBM exam page before you schedule.
IBM recommends the following training for the IBM Foundations of IBM Big Data & Analytics Architecture V1 exam:
Supplement the training with the 60 practice questions from Lead1Pass — self-testing reveals what training alone cannot.
The official IBM Foundations of IBM Big Data & Analytics Architecture V1 outline defines 5 domains, the three largest being Data Governance and Security, Analytics and Data Processing, and IBM Big Data Ecosystem. The complete list is in the topics section above, and Lead1Pass's 60 practice questions address every domain.
IBM Foundations of IBM Big Data & Analytics Architecture V1 Sample Questions:
Data can come from a large number and variety of source systems. Based upon the IBM Big Data &
Analytics Reference Architecture which two statement are true when considering analytics on these data
sources?
- A. Activity data hubs manage consolidated information about past activity based on the decisions related
to entities in a master data hub. - B. MapReduce processing does not require a schema when loading the data but does require an
understanding of the data format prior to processing the data - C. Data marts contain a subset of data from various input sources across the enterprise that can be easily
updated in real time to provide faster analytics. - D. Data federation has the best performance and allows in place analytics directly at the source systems.
- E. Customer and account data is consolidated under a master data hub. Whereas product, supplier and
asset data are consolidated outside of a master data hub for better analytical efficiency.
Correct Answer: A,B 🗳️
What must occur before a bank's Chief Marketing Officer can understand the sentiments social media
users are expressing about the bank's credit cards?
- A. Buy a service offering from Twitter which provides insights into the behaviors of the bank's customers.
The bank will need to disclose the customer names. - B. Add sentiment metrics into the data warehouse. This trusted structured information source is
guaranteed to yield reproducible, high quality reports. - C. Get access to a social media analytics platform. Unstructured data extracted from many external
sources are analyzed in relevant context. - D. Monitor social media events in real time. Analyzing unstructured streaming data is necessary to
produce immediately actionable insights.
Correct Answer: B 🗳️
Using Brewer's CAP theorem as a guide for choosing between alternative data storage technologies,
which two distributed system properties does Apache HBase (part of Hadoop) guarantee?
- A. Consistency - all nodes see the same data at the same time.
- B. Concurrency control - correct results for concurrent operations.
- C. Atomicity - if one part of a transaction fails, the entire transaction fails.
- D. Availability - every request receives a response about whether it was successful or failed
- E. Partition tolerance - the system continues to operate despite arbitrary message loss.
Correct Answer: A,C 🗳️
Which IBM product uses the unique combination of UIMA pipeline for natural language processing and
machine learning?
- A. IBM Info Share BigInsights
- B. IBM Watson Content Analytics
- C. IBM Info Share streams
- D. IBM Watson Explorer
Correct Answer: A 🗳️
Which two statements are true when considering a solution for real-time data processing?
- A. Real-time data can be processed by IBM InfoSphere Streams and then optionally stored within IBM
InfoSphere Biglnsights as part of the IBM Big Data & Analytics platform. - B. Real-time analytics provided by IBM InfoSphere Streams can be used for fraud detection, health
monitoring, or machine data processing, whereas other products in IBM's Big Data & Analytics platform
are provided for sensor data and other real-time scenarios. - C. Real-time prediction and scoring can be performed by using the combination of IBM InfoSphere
Streams and SPSS products within the IBM Big Data & Analytics platform. - D. Real-time analytics can be performed within IBM InfoSphere Biglnsights by using the inmemoryquery
engine in IBM Biglnsights after data has first flowed through IBM InfoSphere Streams to capture data into
memory. - E. Real-time data processing within IBM InfoSphere Biglnsights can be performed with sub-second
response times using Apache Hadoop Streaming, and IBM InfoSphere Streams is included for processing
sensor-generated data.
Correct Answer: A,B 🗳️
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Viewing questions 1-5 out of 60 questions.
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