C2090-102: IBM Certified Data Architect – Big Data

Exam Name: IBM Certified Data Architect – Big Data

Exam Code: C2090-102

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IBM C2090-102 Exam Summary:

Exam Name IBM Certified Data Architect – Big Data
Exam Code  C2090-102
Exam Duration  90 minutes
Exam Questions  55 
Passing Score  60% 
Exam Price   $200 (USD)
Training  Test Preparation Resource
Sample Questions   IBM Big Data Architect Certification Sample Question
Practice Exam   IBM Big Data Architect Certification Practice Exam

IBM C2090-102 Exam Topics:

Objective Details 
Requirements (16%)

– Define the input data structure
– Define the outputs
– Define the security requirements
– Define the requirements for replacing and/or merging with existing business solutions
– Define the solution to meet the customer’s SLA
– Define the network requirements based on the customer’s requirements

Use Cases (46%)

– Determine when a cloud based solution is more appropriate vs. in-house (and migration plans from one to the other)
– Demonstrate why Cloudant would be an applicable technology for a particular use case
– Demonstrate why SQL or NoSQL would be an applicable technology for a particular use case
– Demonstrate why Open Data Platform would be an applicable technology for a particular use case
– Demonstrate why BigInsights would be an applicable technology for a particular use case
– Demonstrate why BigSQL would be an applicable technology for a particular use case
– Demonstrate why Hadoop would be an applicable technology for a particular use case
– Demonstrate why BigR and SPSS would be an applicable technology for a particular use case
– Demonstrate why BigSheets would be an applicable technology for a particular use case
– Demonstrate why Streams would be an applicable technology for a particular use case
– Demonstrate why Netezza would be an applicable technology for a particular use case
– Demonstrate why DB2 BLU would be an applicable technology for a particular use case
– Demonstrate why GPFS/HPFS would be an applicable technology for a particular use case
– Demonstrate why Spark would be an applicable technology for a particular use case
– Demonstrate why YARN would be an applicable technology for a particular use case

Applying Technologies (16%)

– Define the necessary technology to ensure horizontal and vertical scalability
– Determine data storage requirements based on data volumes
– Design a data model and data flow model that will meet the business requirements
– Define the appropriate Big Data technology for a given customer requirement (e.g. Hive/HBase or Cloudant)
– Define appropriate storage format and compression for given customer requirement

Recoverability (11%)

– Define the potential need for high availability
– Define the potential disaster recovery requirements
– Define the technical requirements for data retention
– Define the technical requirements for data replication
– Define the technical requirements for preventing data loss

Infrastructure (11%)

– Define the hardware and software infrastructure requirements
– Design the integration of the required hardware and software components
– Design the connectors / interfaces / API’s between the Big Data solution and the existing systems