Test information:
Number of questions: 63
Time allowed in minutes: 90
Required passing score: 64%
Languages: English

This Database Associate certification is an entry level exam for a user of any of the DB2 for z/OS family of products. This individual is knowledgeable about the fundamental concepts of DB2 11 for z/OS through either hands on experience or formal and informal education. The database associate should have an in-depth knowledge of the basic to intermediate tasks required in day-to-day administration, basic SQL (Structured Query Language), understand which additional products are available with DB2 11, understand how to create databases and database objects, and have a basic knowledge of database security and transaction isolation.

Section 1 – Working with SQL and XML (14%)
Basic ability to write a DML SQL statement
Basic ability to access and process XML data (XQuery, Xpath)
Basic knowledge of most commonly used special registers
Basic knowledge of built-in functions

Section 2 – Security (8%)
Basic knowledge of restricting data access (authorities, privileges, views, profiles, roles, trusted contexts)
Basic ability to write a Data Control Language (DCL) SQL statement

Section 3 – Planning (17%)
Basic ability to connect to DB2 servers (demonstrate ability to use remote access)
Basic knowledge of different types of tables (Base, MQT, Auxiliary, Partitioned, Temporal � at a high level; when is it appropriate to use each type) and table spaces
Basic knowledge of subsystem parameters
Basic knowledge of DB2 architecture (address spaces, logs, IRLM)
Basic knowledge of data sharing concepts
Basic knowledge of database workloads (transactional processing vs. analytics)
Basic knowledge of encoding scheme concepts

Section 4 – Operations (14%)
Basic knowledge of DB2 commands and DSN commands
Basic knowledge of DB2 utilities
Basic knowledge of troubleshooting (Explain, SQL Codes)

Section 5 – Data Concurrency (10%)
Basic knowledge of transaction management (COMMIT, ROLLBACK, AUTOCOMMIT and SAVEPOINT)
Basic knowledge of locking
Given a situation, basic knowledge to identify the isolation levels that should be used

Section 6 – Application Design (19%)
Basic ability to create and call a stored procedure or a user defined function (understanding of passing parameters and obtaining results)
Basic knowledge of temporary tables (how they are created and when they should be used)
Basic knowledge of triggers (how they function; when they might be used)
Basic knowledge of program preparation and BIND options
Basic knowledge of referential integrity and constraints
Basic knowledge of non-relational data concepts (XML data, LOB data)
Basic knowledge of Temporal (Time Travel) Tables – System-period, Application-period, and Bi-temporal – ability to create and query

Section 7 – Working with Database Objects (17%)
Basic ability to demonstrate usage of IBM-supplied and user-defined data types
Basic ability to write a DDL SQL statement
Basic ability to identify characteristics and properties of DB2 objects (Tables, Indexes, Views,…)
Basic ability to look up information in the DB2 catalog

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Test information:
Number of questions: 60
Time allowed in minutes: 75
Required passing score: 63%
Languages: English

This test consists of 10 sections containing a total of 60 multiple-choice questions. The percentages after each section title reflect the approximate distribution of the total question set across the sections.

Database Objects (13%)
Create and alter database demonstrating knowledge of database attributes
Create and alter tables demonstrating knowledge of table attributes
Demonstrate knowledge of types, attributes, and purpose of indexes
Create table columns demonstrating knowledge and application of various data types
Apply constraints to database tables and columns
Correctly apply encoding schemes to tables
Manage sequences and identities on tables
Create views and understand the best practices for the use of those views

Data Retrieval & Manipulation (12%)
Create table joins using best practices
Merge / select from data change table reference
Demonstrate knowledege of when to use truncate versus delete
Create functions & expressions
Apply knowledge of best practices for grouping, aggregation, and uniqueness
Apply knowledge of best practices for inserts, updates & deletes
Apply knowledge of best practices for Predicates (BETWEEN, IN, LIKE)

Distributed Access to DB2 (8%)
Manage connections to optimize performance
Identify what makes a cursor ambiguous
Determine whether limited fetch or optimize clause should be used in a query
Use best practices to determine generic program options
Set up a data source (dot net, java, odbc)

Coding SQL in Application Programs (10%)
Manage the use of cursors within a program
Apply best practices for error handling
Demonstrate knowledge of when to use dynamic versus static SQL
Demonstrate knowledge of multi-row syntax
Understand when and how to use DCLGEN
Understand how to prepare the program for execution

Processing Options that affect program design (8%)
Understand when and how to use precompile options
Understand when and how to use Bind Options & Connection Settings
Understand when and how to use Special Registers & Built-in Global Variables
Understand when and how to use options at the statement level

Performance Considerations (7%)
Identify examples of accounting trace usage
Understand the use of explain data and IBM Data Studio
Identify differences in DB2 access paths
Identify Stage 1 versus Stage 2 Predicates

Units of work, concurrency, and checkpoint/restart (10%)
Ability to use Isolation Levels & bind release options
Identify the differences between COMMIT, ROLLBACK, and SAVEPOINTS
Ability to recognize and code basic Units of Work
Ability to recognize and code Data Currency options
Knowledge of best practices and restrictions for Autonomous Transactions
Applies Process control and Checkpoint / Restart processing

Application Design & Lifecycle (8%)
Ability to validate execution results are correct
Ability to test connections and stored procedures
Ability to work with DB2 LOAD and UNLOAD utilities
Ability to troubleshoot application performance
Ability to properly utilize DB2 Performance Features

Access to Non-Structured Data (8%)
Ability to work with native XML data
Ability to work with JSON data
Ability to perform schema Validation for XML
Ability to work with XML Built-In Functions
Ability to access Hadoop Data

Advanced Programming Topics (15%)
Ability to work with Stored Procedures
Ability to make use of UDF’s
Ability to use Triggers
Ability to manage relationships between tables using Referential Integrity
Ability to work with Temporal and Archive Tables
Ability to work with MQTs
Ability to work with Temporary Tables
Ability to work with Data Masking techniques

IBM Certified Application Developer – DB2 11 for z/OS

Job Role Description / Target Audience
This certification is intended for the IBM DB2 for z/OS application developers. This is a highly skilled individual responsible for the development of applications that utilize the DB2 product on the z/OS operating system. This individual has significant experience as a designer and developer and has extensive knowledge of DB2 application development constructs, including new features and functionality related to version 11.

This person is capable of performing intermediate to advanced tasks related to application design and implementation, SQL programming, multi-platform deployment (local and/or multi-tiered applications), performance, testing, troubleshooting, and programming specific to DB2 for z/OS. The IBM Certified DB2 for z/OS Application Developer should also, at a minimum, be aware of, and have some experience with, best practices for interfacing with DB2.

To attain the IBM DB2 for z/OS Application Developer certification, candidates must pass one test. To gain additional knowledge and skills, and prepare for the tests based on the job roles and test objectives, click on the link to the test below and refer to the Test Preparation tab.

Recommended Prerequisite Skills
Familiarity with: z/OS, TSO/ISPF, CICS, Application Server (e.g. WebSphere, etc.), IBM Data Studio, Visual Explain, Eclipse, RDz, z/OS Management Framework, SPUFI, DB2I, WLM, Performance Tuning, DB2 Objects. Proficient with: DB2 for z/OS, IBM Data Server Client, SQL & SQLPL, Stored Procedures

 

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Test information:
Number of questions: 30
Time allowed in minutes: 60
Required passing score: 60%
Languages: English, Japanese

If you are knowledgeable with DB2 10.5 and are capable of performing the intermediate to advanced skills required in the day-to-day administration of DB2 instances and databases, you may benefit from this certification role.

Section 1 – DB2 Server Management (17%)
Demonstrate the ability to configure DB2 workload for analytics system
DB2_WORKLOAD=ANALYTICS
DB CFG DFT_TABLE_ORG COLUMN
DB CFG DATABASE PAGE SIZE = 32K
DB CFG DFT_DEGREE=ANY
DB CFG DFT_EXTENT_SZ=4
Importance of UTIL_HEAP_SZ CFG for COLUMN ORGANIZED tables load
Demonstrate the ability to use autonomic features in DB2 10.5 BLU Acceleration
AUTO_RUNSTATS is not supported for COLUM ORGANIZED tables
Automatic Space Reclaims in BLU acceleration tables
Demonstrate knowledge of Data Studio 4.1
Demonstrate the ability to use Automated workload management when workload set to ANALYTICS

Section 2 – Physical Design (37%)
Demonstrate the ability to understand industry leading DB2 10.5 BLU Acceleration 7 big ideas
Simple to Impement and Use – No Indexes, No MDC, No MQT, No Partitioning, No Statistical Views
Friendly Huffman encoding – More frequent the values, the fewer bits in dictionary and packed registers. Performing most operations on encoded values.
Usage of SIMD Instruction Sets
Maximize CPU cache
Column Store – Minimal IO / Work performed directly on columns / Improved memory density / Cache efficiency
Memory Caching Facility – Leave the interesting data instead of traditional LRU or MRU algorithms
Data Skipping through SYNOPSIS Tables
Demonstrate the ability to understand and implement compression features
Table Compression – Data Compression / Value Compression / Adaptive Compression / COLUMN ORGANIZED table compression
Database backup compression
Demonstrate the ability to use expression based indexes and the statistics on those expression based indexes
Using RUNSTATS
Using Statistics Profiles
Automatic Statistics Collection
Knowledge of Oracle Migration and Compatibility Features in DB2 10.5
Demonstrate the ability to use Information Uniqueness Constraints
Knowledge of SQL compatibility enhancements
Extended row size support
Exclude null keys support

Section 3 – Monitoring DB2 Activity (17%)
Demonstrate the ability to use new monitor elements
Demonstrate the ability to use new monitor elements to monitor dynamic prefetch requests for data in column-oriented tables.
Demonstrate the ability to use new new monitor elements to measure column data size.
Demonstrate the ability to use new monitor elements to measure time spent in Columnar Data Engine (CDE)
Demonstrate knowledge of the new EXPLAIN enhancements Knowledge of SQL compatibility enhancements
Demonstrate the ability to understand new CTQ (Column Table Queue) Operator in the explain
Knowledge of new monitoring function – MON_GET_ROUTINE
Demonstrate knowledge of HADR monitoring enhancements
HEARTBEAT_MISSED
HEARTBEAT_EXPECTED
STANDBY_SPOOL_PERCENT
STANDBY_ERROR_TIME

Section 4 – High Availability (17%)
Knowledge of enhancements to pureScale
Understand the ability to use Online REORG in pureScale
Knowledge of replay member in pureScale standby cluster
Knowledge of HADR setup in a pureScale cluster environment
Demonstrate the ability to undestand Rolling Fix Pack Updates in pureScale
Demonstrate the ability to undestand STMM Multi-Tenancy Feature in pureScale
Demonstrate the ability to understand Explicit Hierarchical Locking Multi-Tenancy in pureScale system
Knowledge of DB2 Advanced Copy Services customized scripts

Section 5 – Utilities (13%)
Demonstrate the ability to use IBM Optim Query Workload Tuner
The Workload Table Organization Advisor
Support for comparing access plans before and after
Access Plan Explorer and in access plan graphs for the new CTQ operator
Demonstrate the ability to use DB2 10.5 Utilities
db2convert
LOAD Command – Additional ANALYZE phase for COLUMN ORGANIZED tables
Default AUTOMATIC STATISTICS COLLECTION in LOAD command for COLUMN ORGANIZED tables

IBM Certified Database Administrator – DB2 10.5 DBA for LUW Upgrade from DB2 10.1

Job Role Description / Target Audience
If you are knowledgeable with DB2 10.5 and are capable of performing the intermediate to advanced skills required in the day-to-day administration of DB2 instances and databases, you may benefit from this certification role.

This exam covers only the new features and functionality of DB2 10.5 for Linux, UNIX and Windows – you must possess the DB2 10.1 DBA for Linux, UNIX and Windows certification in order to qualify for the upgrade exam.

C2090-311 IBM DB2 10.5 DBA for LUW Upgrade from DB2 10.1

QUESTION 1
How is the Query Workload Tuner license installed and enabled?

A. With Data Studio, using the license activation kit.
B. By executing the db2licm command after data server installation.
C. With the Optim Performance Manager Server, using the license activation kit.
D. By running the Query Workload Tuner license activation command on the appropriate
WebSphere server.

Answer: A

Explanation:

---

QUESTION 2
If the DB2_WORKLOAD registry variable has not been set which database manager configuration
parameter must be modified, before a query that accesses a column-organized table can be
executed?

A. INTRA_PARALLEL
B. QUERY_HEAP_SZ
C. MAXIMUM DEGREE
D. SHEAPTHRES SHR

Answer: A

 

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Test information:
Number of questions: 64
Time allowed in minutes: 90
Required passing score: 64%
Languages: English

The IBM Certified Solution Developer – IBM InfoSphere Information Analyzer v9.1 exam certifies that the successful candidate has important knowledge, skills, and abilities necessary to conduct a baseline assessment of the data/information being analyzed. This included characterizing the data or information condition in terms of completeness, validity, structural integrity, relational integrity, technical standards, and business rule compliance including quality monitoring and information governance.

Section 1 – Environment (9%)
List key components and configuration steps
Given a scenario, describe how to plan for a large data environment
Identify the minimum requirements for installation

Section 2 – Data Setup (9%)
Identify steps necessary to make data sources available for analysis
Given a scenario, describe project activity security

Section 3 – Profiling Process (25%)
Identify the purposes of each analysis
Interpret system flag icons throughout the system
Identify the common steps that are needed to perform data profiling
Given a scenario, describe the process needed to assess and use data profiling results

Section 4 – Data Rules / Monitoring (36%)
Describe the purpose of data rule validation
Given a scenario, describe the process to implement and deploy the data rule
Identify the steps needed to implement data rule monitoring and baselining
Identify the steps needed to perform data rule execution
Describe the purpose and process of exception management (output tables, Data Quality Console)
Identify the steps necessary to deploy and execute a data rule in an external process

Section 5 – Populating / Reporting / Publishing (14%)
Demonstrate how to populate/report/publish
Demonstrate knowledge of content creation and scheduling
Given a scenario, describe the process to deliver outputs to a broad community

Section 6 – Troubleshooting / Tuning (6%)
Given a scenario, demonstrate troubleshooting techniques
Given a scenario, demonstrate system and process tuning techniques

IBM Certified Solution Developer – InfoSphere Information Analyzer v9.1

Job Role Description / Target Audience
The IBM Certified Solution Developer – InfoSphere Information Analyzer v9.1 is a Source System Analyst, Data Analyst, Business Analyst, Data Quality Analyst, Data Steward, Data Modeler, Data Architect, ETL Developer, and Data Scientist.

---

QUESTION 1
What feature permits the addition of data from one or more columns into one column allowing column analysis on this newly formed concatenated column?

A. Virtual table
B. Logical table
C. Virtual column
D. Logical column

Answer: C
Reference:https://www.scribd.com/doc/125259952/IBM-infoSphere-information-analyzer-v8-7-User-guide(page 70)

---

QUESTION 2
When importing published analysis results into a different Information Analyzer project which two contents are included?

A. Median value
B. Frequency values
C. Data Classification
D. Cardinality Percent
E. Uniqueness Code

Answer: C,D

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QUESTION 3
You are searching for an employee named Kristie Jones who has accounts on various applications, in which she has used the first names Kristie, Kristin, and Kristen as her first name.
Which is the correct rule logic for addressing this problem?

A. name like (‘KristieTKristinTKristen’)[ ]’Jones’
B. name matches (,KristieTKristinTKristen,)[]’Jones,
C. name contains (‘KristieTKristinTKristen’^rJones’
D. name matches_regex (‘Kristie’l’KristinTKristen^j’Jones’

Answer: D

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QUESTION 4
You are working with a System Administrator who must move an Information Analyzer project to a new Information Server environment using the command line tools. You need to ensure that the project is established with the same metadata and reports as in the original environment.
Which parameter must be included to successfully complete the export?

A. -includeCommonMetadata; -includeCommonReports; -includeAIIDataClasses
B. -includeAssignedAssets; -includeProjectReports; -includeAIIDataSources
C. -includeCommonMetadata; -includeReports; -includeAIIDataClasses
D. -includeProjectMetadata; -includelAReports; -includeDependentClasses

Answer: D

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Test information:
Number of questions: 66
Time allowed in minutes: 90
Required passing score: 71%
Languages: English

The Cognos BI Professional exam covers key concepts, technologies, and functionality of the Cognos products. In preparation for an exam, we recommend a combination of training and hands-on experience.

Iterative Development and CSIM (9%)
Identify different approaches for implementing BI projects
Identify the value of using a methodology
Distinguish between an approach and a methodology
Describe the iterative development process

Dimensional Design and Key Metrics (14%)
Describe the relationship between dimensions, facts, and granularity
Identify the differences between SQL and MDX
Define the Key Performance Indicators and identify their business purpose
Map Cognos components to KPI process flow
Describe the functional and organizational scope of Corporate Performance Management

Identify the Right Tool for the Business Need (16%)
Identify the differences between reporting, querying, and analysis
Map the Cognos products to reflect relationship between interactivity and formatting
Identify the need for scorecarding
Identify the need for planning
Identify the need for data manager
Identify the need for event management
Identify the need for analysis, reporting and querying
Identify different roles and categories of users

Determine User Requirements (15%)
Describe the importance of and the activities in the Analyze phase
Identify the elements of conducting a successful interview
Identify the dimensional elements of how users think about their business
Identify the metric elements and KPI of the dimensional design
Identify the business area to prototype with the highest return on investment
Identify methods of enriching the dimension map

Common Data Stores (14%)
Describe the data normalization process
Identify the difference between relational and OLAP data structures
Compare data store designs
Identify variations on data warehouse designs
Compare operational vs. reporting database designs
Identify considerations for modeling dimensionally (DMR) in Framework Manager

Cognos BI Architecture (12%)
Identify components and services of the Cognos Services Oriented Architecture
Describe benefits of the Cognos Application Firewall (CAF)
Describe the installation process
Identify considerations for installing to environments that include separate instances of a security provider
Identify considerations for addressing high availability and failover
Identify a properly designed installation map

Cognos BI Request Flows and Queues (8%)
Identify the correct flow of the request between architectural components and services for a given request
Identify the differences between high affinity and low affinity report execution requests and associated connections
Identify the relationship between scheduled jobs and batch reporting

Design, Build, and Deploy Considerations (8%)
Understand the use of the V-model testing
Considerations for moving between environments
Identify the important considerations for monitoring and tuning for performance
Identify application design and system considerations for performance

Maintain the BI Application (4%)
Identify the importance of ongoing monitoring the performance of the application
Describe the tracking and planning for enhancement requests and subsequent development phases
Identify integrating the new solution into regular backups and maintenance programs

IBM Certified Solution Expert – Cognos BI

Job Role Description / Target Audience
The BI Solution Expert (Professional) is responsible to analyze, plan, design, deploy, and operate Cognos applications using an appropriate methodology and development approach.

To achieve the IBM Certified Solution Expert – Cognos BI certification, candidates must possess the skills identified under Recommended Prerequisite Skills, if any, and pass four (4) exams.

Click the test link below to see the overview, objectives, and test preparation recommendations.

Recommended Prerequisite Skills
Prior to your preparation for this professional-level certification, the following knowledge and skills are recommended and assumed:
Knowledge of the Cognos Solutions Implementation Methodology
Technical proficiency in features of the Cognos Managers and Studios

 

---

QUESTION 1
A multi-server installation of Cognos BI must be performed. Which of the following is a valid strategy for installing across multiple servers?

A. Separate the gateway component from other server components to restrict report request processing to the Web server tier.
B. Enable dedicated request processing, by installing a dispatcher in the Web server tier to act as a primary dispatcher for routing requests to other dispatchers.
C. Scale the system vertically by installing one instance of all Cognos 8 services on a larger computer capable of managing more concurrent request threads.
D. Enable load balancing of requests for content management services by installing multiple instances of Content Manager.

Answer: B

---

QUESTION 2
Which of the following is a critical component in delivering Corporate Performance Management throughout an enterprise?

A. Drill down from summary to detailed information within individual subject areas.
B. Drill across from one subject area to another through conformed dimensions.
C. Star schema data marts designed to facilitate analysis and reporting.
D. Event management designed to monitor the status of Key Performance Indicators.

Answer: B

---

QUESTION 3
A company has several operational data stores. They wish to compare data from the various data stores against one another. The data in the various stores must be manipulated to match. Eventual report performance is more important than development time. Which of the following Cognos 8 components would BEST address their requirements?

A. Report Studio and Query Studio
B. Analysis Studio and Report Studio
C. Data Manager and Analysis Studio
D. Planning, Data Manager, and Report Studio

Answer: C

---

QUESTION 4
Why should an application’s performance be monitored on an ongoing basis after it goes into production?

A. Initial performance tests are usually too optimistic.
B. There is little value in performance tests before a system goes into production.
C. Usage patterns on applications tend to change over time.
D. New releases of system and application software usually degrade performance.

Answer: C

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QUESTION 5
Which of the following describes common methods for enriching an initial dimension map?

A. Add exception and range band dimensions and include additional metrics and calculations.
B. Merge dimensions and include additional metrics and calculations.
C. Include additional metrics and calculations and core metrics and dimensions from related business areas.
D. Include additional metrics, calculations, and hierarchy levels, and dimensions from related subject areas.

Answer: A

 

 

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Test information:
Number of questions: 60
Time allowed in minutes: 120
Required passing score: 65%
Languages: English

This test will certify that the successful candidate has the necessary skills to work with, transform, and act on data at a very large scale. The candidate will be able to build data pipelines and derive viable insights into the data using Apache Spark. The candidate is proficient in using streaming, machine learning, SQL and graph processing on Spark. This candidate may be a member of a Data Scientist team and/or Analytics team and has applied knowledge with deployment architectures and can assist in tuning, troubleshooting, and optimization.

Section 1 – Architecture (12%)
Compare and contrast Spark with Hadoop MapReduce
Explain memory management in Spark
Explain concepts such as master, drivers, executors, stages and tasks
Explain Spark transformations and actions with respect to lazy evaluation
Configure your application to run on a cluster

Section 2 – Performance and Troubleshooting (22%)
Manage partitions to improve RDD performance and apply different partition strategies
Identify what operations cause shuffling
Optimize memory usage with serialization options
Use caching, checkpoint, and persistence in appropriate situations
Debug Spark code
Monitor Spark applications
Manage runtime issues and performance bottlenecks in Spark

Section 3 – Core Skills (48%)
Read/writre data from multiple data sources and file types
Create and work with RDDs and related APIs
Create and work with DataFrames and related APIs
Create Spark config contexts for different requirements
Work with key value pairs and associated Spark APIs for key value pairs
Work with SparkSQL
Define and work with accumulators
Define and work with broadcast variables
Launch applications with spark-submit

Section 4 – Advanced Skills (18%)
Build a pipeline with Streaming, MLLib, SQL, and Graph on Spark
Work with Spark Streaming APIs
Work with SparkML and MLLib APIs
Work with GraphX

IBM Certified Developer – Apache Spark 1.6

Job Role Description / Target Audience
This test will certify that the successful candidate has the necessary skills to work with, transform, and act on data at a very large scale. The candidate will be able to build data pipelines and derive viable insights into the data using Apache Spark. The candidate is proficient in using streaming, machine learning, SQL and graph processing on Spark. This candidate may be a member of a Data Scientist team and/or Analytics team and has applied knowledge with deployment architectures and can assist in tuning, troubleshooting, and optimization.

Recommended Prerequisite Skills
Read and write Python code
Read and write Scala code
Create and work with RDDs and related APIs
Create and work with DataFrames and related APIs
Create and work with Dstreams and related APIs
Read/writre data from multiple data sources and file types
Read and write SQL statements
Compare and contrast Spark with Hadoop MapReduce
Manage partitions to improve RDD performance and apply different partition strategies
Identify what operations cause shuffling
Optimize memory usage with serialization options
Create Spark config contexts for different requirements
Use caching, checkpoint, and persistence in appropriate situations
Explain memory management in Spark
Work with key value pairs and associated Spark APIs for key value pairs
Define and work with accumulators
Configure your application to run on a cluster
Explain core concepts such as master, drivers, executors, stages and tasks
Debug your spark code
Define and work with broadcast variables
Explain Spark transformations and actions with respect to lazy evaluation
Monitor Spark applications
Launch applications with spark-submit
Manage runtime issues and performance bottlenecks in Spark
Build a pipeline with Streaming, MLLib, SQL, and Graph on Spark
Work with Spark Streaming APIs
Work with SparkML and MLLib APIs
Work with GraphX
Work with SparkSQL

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Test information:
Number of questions: 53
Time allowed in minutes: 75
Required passing score: 65%
Languages: English

This test consists of 5 sections containing a total of 53 multiple-choice questions. The percentages after each section title reflect the approximate distribution of the total question set across the sections.

Data Loading (34%)
Load unstructured data into InfoSphere BigInsights
Import streaming data into Hadoop using InfoSphere Streams
Create a BigSheets workbook
Import data into Hadoop and create Big SQL table definitions
Import data to HBase
Import data to Hive
Use Data Click to load from relational sources into InfoSphere BigInsights with a self-service process
Extract data from a relational source using Sqoop
Load log data into Hadoop using Flume
Insert data via IBM General Parallel File System (GPFS) Posix file system API
Load data with Hadoop command line utility

Data Security (8%)
Keep data secure within PCI standards
Uses masking (e.g. Optim, Big SQL), and redaction to protect sensitive data

Architecture and Integration (17%)
Implement MapReduce
Evaluate use cases for selecting Hive, Big SQL, or HBase
Create and/or query a Solr index
Evaluate use cases for selecting potential file formats (e.g. JSON, CSV, Parquet, Sequence, etc�)
Utilize Apache Hue for search visualization

Performance and Scalability (15%)
Use Resilient Distributed Dataset (RDD) to improve MapReduce performance
Choose file formats to optimize performance of Big SQL, JAQL, etc.
Make specific performance tuning decisions for Hive and HBase
Analyze performance considerations when using Apache Spark

Data Preparation, Transformation, and Export (26%)
Use Jaql query methods to transform data in InfoSphere BigInsights
Capture and prep social data for analytics
Integrating SPSS model scoring in InfoSphere Streams
Implement entity resolution within a Big Data platform (e.g. Big Match)
Utilize Pig for data transformation and data manipulation
Use Big SQL to transform data in InfoSphere BigInsights
Export processing results out of Hadoop (e.g. DataClick, DataStage, etc.)
Utilize consistent regions in InfoSphere Streams to ensure at least once processing

IBM Certified Data Engineer – Big Data

Job Role Description / Target Audience

This certification is intended for IBM Big Data Engineers. The Big Data Engineer works directly with the Data Architect and hands-on Developers to convert the architect’s Big Data vision and blueprint into a Big Data reality. The Data Engineer possesses a deep level of technical knowledge and experience across a wide array of products and technologies. A Data Engineer understands how to apply technologies to solve big data problems, and has the ability to build large-scale data processing systems for the enterprise. Data engineers develop, maintain, test and evaluate big data solutions within organizations. They provide input on the needed hardware and software to the architects.

Big Data Engineers focus on collecting, parsing, managing and analyzing large data sets, in order to provide the right data sets and visual tools for analysis to the data scientists. They understand the complexity of data and can handle different data variety (structured, semi-structured, unstructured), volume, velocity (including stream processing), and veracity. They also address the information governance and security challenges associated with the data. They have a good background in software engineering and extensive programming and scripting experience.

To attain the IBM Certified Big Data Engineer, candidates must pass one test. To gain additional knowledge and skills, and prepare for the test based on the job roles and test objectives, click on the link to the test below and refer to the Test Preparation tab.

Recommended Prerequisite Skills
Understand the data layer and particular areas of potential challenge/risk in the data layer
Ability to translate functional requirements into technical specifications.
Ability to take overall solution/logical architecture and provide physical architecture.
Understand Cluster Management
Understand Network Requirements
Understand Important interfaces
Understand Data Modeling
Ability to identify/support non-functional requirements for the solution
Understand Latency
Understand Scalability
Understand High Availability
Understand Data Replication and Synchronization
Understand Disaster Recovery
Understand Overall performance (Query Performance, Workload Management, Database Tuning)
Propose recommended and/or best practices regarding the movement, manipulation, and storage of data in a big data solution (including, but not limited to:
Understand Data ingestion technical options
Understand Data storage options and ramifications (for example , understand the additional requirements and challenges introduced by data in the cloud)
Understand Data querying techniques & availability to support analytics
Understand Data lineage and data governance
Understand Data variety (social, machine data) and data volume
Understand/Implement and provide guidance around data security to support implementation, including but not limited to:
Understand LDAP Security
Understand User Roles/Security
Understand Data Monitoring
Understand Personally Identifiable Information (PII) Data Security considerations

Software areas of central focus:
BigInsights
BigSQL
Hadoop
Cloudant (NoSQL)

Software areas of peripheral focus:
Information Server
Integration with BigInsights, Balanced Optimization for Hadoop, JAQL Push down capability, etc
Data Governance
Security features of BigInsights
Information Server (MetaData Workbench for Lineage)
Optim Integration with BigInsights (archival)
DataClick for BigInsights (Future: DataClick for Cloudant – to pull operation data into Hadoop for Analytics – scripts available today)
BigMatch (trying to get to a single view)
Guardium (monitoring)
Analytic Tools (SPSS)
BigSheets
Support in Hadoop/BigInsights
Data Availability and Querying Support
Streams
Interface/Integration with BigInsights
Streaming Data Concepts
In memory analytics
Netezza
DB2 BLU
Graph Databases
Machine Learning (System ML)

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