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C2030-102 - IBM Big Data Architect - Dump Information

Vendor : IBM
Exam Code : C2030-102
Exam Name : IBM Big Data Architect
Questions and Answers : 55 Q & A
Updated On : August 15, 2017
PDF Download Mirror : C2030-102 Brain Dump
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C2030-102 Questions and Answers

C2030-102

Reference:

www- 01.ibm.com/support/knowledgecenter/SSPT3X_4.1.0/com.ibm.swg.im.infosphere.biginsight s.analyze.doc/doc/bigsheets_con_workbooks.html


QUESTION: 50

Cloudant is defined by which of the following?


  1. A JSON document store

  2. A key/value store

  3. Agraph database

  4. A column/family store


Answer: C


Reference:

www.redbooks.ibm.com/redpapers/pdfs/redp5126.pdf


QUESTION: 51

Which of the following big data components makes all decisions regarding the replication of blocks?


  1. Job Tracker

  2. Edge Node

  3. Name Node

  4. Data Node


Answer: A


QUESTION: 52

Considering a service level requirement (SLR) of less than 3 milliseconds, what task must be performed to meet the SLR?


  1. Collect and analyze SNMP MIB data

  2. Survey a representative amount of end users

  3. Measure switch failure frequency

  4. Inquire when prime network hours occur


Answer: C

QUESTION: 53

Which of the following statements is true about DB2 BLU?


  1. To move a table from row based into a BLU columnar format you have to take a back upand restore it to a BLU table.

  2. To move a table from row based into a BLU columnar format you need to take it offline and do a one time convert into a BLU table.

  3. To support mixed workload it is necessary to create a shadow copy of the relevant tables.

  4. To support mixed workload it is necessary to create a shadow copy of the database populatedwith relevant BLU tables.


Answer: B


Reference:

www.ibm.com/developerworks/library/dm-1406convert-table-db2105/


QUESTION: 54

Data Architects assess data according to several common characteristics. One of these characteristics is the type of data. Which of the following are data types that fall into this ontology? (Choose two.)


  1. Master data

  2. Meta data

  3. Boolean

  4. Composite

  5. Integer


Answer: A, D


QUESTION: 55

In order to enable connectivity between Netezza and BigInsights, what must be enabled on the Netezza Performance Server?


  1. Java-based Netezza user-defined functions

  2. ODBC drivers from Netezza

  3. JDBC drivers from Netezza

  4. JAQL Netezza connectors


Answer: A


Reference:

www- 01.ibm.com/support/knowledgecenter/SSPT3X_4.1.0/com.ibm.swg.im.infosphere.biginsight s.import.doc/doc/data_warehouse_udf_netezza.html



IBM C2030-102 Exam (IBM Big Data Architect) Detailed Information

C2090-102 Test Information / Examination Information


Number of questions : 55
Time allowed in minutes: 90
Required passing score : 60%
Languages : English


C2090-102 Objectives


Test C2090-102: IBM Big Data Architect

Tab navigation

  • Overview- selected tab,
  • Objectives
  • Test preparation
  • Sample / Assessment Test
  • This test consists of 5  sections containing a total of 55 multiple-choice questions. The percentages after each section title reflect the approximate distribution of the total question set across the sections.

    Requirements (16%)

    1. Define the input data structure
    2. Define the outputs
    3. Define the security requirements
    4. Define the requirements for replacing and/or merging with existing business solutions
    5. Define the solution to meet the customer's SLA
    6. Define the network requirements based on the customer's requirements

    Use Cases (46%)

    1. Determine when a cloud based solution is more appropriate vs. in-house (and migration plans from one to the other)
    2. Demonstrate why Cloudant would be an applicable technology for a particular use case
    3. Demonstrate why SQL or NoSQL would be an applicable technology for a particular use case
    4. Demonstrate why Open Data Platform would be an applicable technology for a particular use case
    5. Demonstrate why BigInsights would be an applicable technology for a particular use case
    6. Demonstrate why BigSQL would be an applicable technology for a particular use case
    7. Demonstrate why Hadoop would be an applicable technology for a particular use case
    8. Demonstrate why BigR and SPSS would be an applicable technology for a particular use case
    9. Demonstrate why BigSheets would be an applicable technology for a particular use case
    10. Demonstrate why Streams would be an applicable technology for a particular use case
    11. Demonstrate why Netezza would be an applicable technology for a particular use case
    12. Demonstrate why DB2 BLU would be an applicable technology for a particular use case
    13. Demonstrate why GPFS/HPFS would be an applicable technology for a particular use case
    14. Demonstrate why Spark would be an applicable technology for a particular use case
    15. Demonstrate why YARN would be an applicable technology for a particular use case

    Applying Technologies (16%)

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

    Recoverability (11%)

    1. Define the potential need for high availability
    2. Define the potential disaster recovery requirements
    3. Define the technical requirements for data retention
    4. Define the technical requirements for data replication
    5. Define the technical requirements for preventing data loss

    Infrastructure (11%)

    1. Define the hardware and software infrastructure requirements
    2. Design the integration of the required hardware and software components
    3. Design the connectors / interfaces / API's between the Big Data solution and the existing systems

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