Foundations of IBM Big Data C2090-136 Exam Preparation Material
C2090-136: Foundations of IBM Big Data & Analytics Architecture V1 exam contains 58 multiple-choice questions (be obliged to attain score of 70% correct to clear this exam). The candidate will have 90 minutes to complete the exam. It is available in English language only.
This test consists of 6 sections.
Section 1: Big Data & Analytics Advantages and Concepts
Elucidate volume, velocity, diversity and veracity in relation to BD&A, classify analytics and the different types, explain the value of analytics to uphold business decisions, clarify how Big Data & Analytics are interlocked, enlighten the diverse data preparation processes, elucidate precise data preparation techniques meant for creating structured data and explain the general sources of data for BD&A.
Section 2: Big Data & Analytics Design Principles
Clarify when it is suitable to use Hadoop to support the BD&A use case, enlighten when it is correct to use data streaming to sustain the BD&A use case, give details when it is suitable to influence data streaming and Hadoop for data integration Extract, Transform, and Load (ETL), illustrate at what time to use analytics on data-in-motion vs analytics on data-at rest to support a corporate use case, utilize the CAP theorem to opt an optimal data storage technology and portray the considerations of security on BD&A. IBM Certified Solution Advisor
Section 3: IBM Big Data & Analytics Adoption
- Elucidate how to control maturity models intended for IBM Big Data & Analytics to recognize the customer’s current position and define the future development, give industry adoption examples for BD&A to direct a customer on their own use cases, depict the advantages of social media analytics to support BD& A use cases.
Section 4: IBM Big Data & Analytics Solutions
- Give details when it is suitable to use IBM BigInsights versus other hadoop distributions, explain how data can be provisioned designed for use with SPSS modeler to bring analytic outcomes, explain what solutions are desirable to manage and administer BD&A workloads, classify how to develop Risk Management with BD&A, explain the advantages of "in-database" analytics, illustrate the key BD&A units necessary to support a real-time operational analytics.
Section 5: IBM Big Data & Analytics Infrastructure Considerations
Clarify how infrastructure matters in facilitating Big Data & Analytics, portray the responsibility of storage and storage management software in Big Data and Analytics, illustrate how customers by means of data already managed by System z can broaden the platform to incorporate Analytics.
Section 6: IBM Big Data & Reference Architecture
Elucidate the advantages of IBM integrated BD&A platform, describe the Acquire, Grow, Retain customers vital and associated use cases, classify the Transform Financial Processes necessary and associated use cases.