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 |
| Passing Score: | 70% |
| Related Certifications: | IBM Big Data & Analytics IBM Certified Solution Advisor |
| Available Languages: | English |
| Exam Format: | Multiple Choice |
| Exam Duration: | 90 minutes |
| Real Exam Qty: | 58 |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Delivered through Pearson VUE test centers or online proctored delivery.:contentReference[oaicite:0]{index=0} |
| Pre Condition: | No specific prerequisite exams required. |
| Official Syllabus URL: | https://www.ibm.com/training/certification |
IBM C2090-136 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Governance & Security | - Governance principles
|
| Big Data & Analytics Concepts | - Big Data fundamentals
|
| IBM Big Data Architecture | - IBM Products in Big Data
|
| Big Data Design Principles | - Design principles
|
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The IBM Foundations of IBM Big Data & Analytics Architecture V1 blueprint centers on these domains:
- Data Governance & Security
- Big Data & Analytics Concepts
- IBM Big Data Architecture
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IBM states the following prerequisites for the IBM Foundations of IBM Big Data & Analytics Architecture V1: No specific prerequisite exams required..
For the authoritative details, see the official certification page.
According to the latest exam information, the C2090-136 exam contains 58 questions and lasts 90 minutes minutes. Simulating those conditions at home with the PC test engine is excellent preparation for the real environment.
IBM Foundations of IBM Big Data & Analytics Architecture V1 Sample Questions:
A construction supply company has a lot of machine data ranging from sensors to GPS readings. They
want to integrate and analyze this data to help them optimize their resource allocation and gain real time
maintenance decision support while ensuring customer satisfaction. Which use case examples should the
Solution Advisor review to guide them on their Big Data & Analytics adoption planning?
- A. Operational Analysis
- B. Big Data Exploration
- C. Enhanced 360 View of the Customer
- D. Data Warehouse Modernization
Correct Answer: D 🗳️
Which statement best defines the Create New Business Models business imperative?
- A. Explore strategic options for business growth using new perspectives gained from exploiting Big Data
& Analytics. - B. Lead the creation of new value and agility for the business using Big Data & Analytics while reducing
cost. - C. Use Big Data & Analytics to drive enterprise agility, anticipate outcomes to make better decisions, and
drive business model innovation through a discipline of performance. - D. Plan, manage, and maximize operations, supply chains, and use of infrastructure assets to reduce
costs, increase efficiencies and productivity, and limit threats.
Correct Answer: B 🗳️
What are the names of the two zones represented by the question marks shown in this diagram?
- A. Information cleansing and preparation zone
- B. Exploration, landing, and archive zone
- C. Information audit and logging zone
- D. Extract, translate, and loading zone
- E. Real time analytics zone
Correct Answer: C,D 🗳️
Which statement is true when comparing SQL used in Relational Database Management Systems
(RDBMS) and SQL data on Hadoop type systems?
- A. When adding or updating information in Hadoop. HiveQL provides a flexible language construct for
MapReduce developers. - B. MapReduce developers and database specialist may both use their knowledge of SQL to add and
update information in a Hive database. - C. HiveQL is an ANSI SQL language that can be used by Oracle, IBM DB2. and other RDMS developers
to rapidly insert information into Hive. - D. Oracle and IBM DB2 are examples of SQL systems that are used to house business information and
well suited for CRUD and read-only operations.
Correct Answer: D 🗳️
Which in-memory database design point helps use main memory more efficiently?
- A. Organizing data according to columns rather than rows.
- B. Single Instruction Multiple Data processing.
- C. Automatic and always-on data compression.
- D. Processing data using multiple processor cores.
Correct Answer: B 🗳️
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