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How to Prepare For IBM InfoSphere QualityStage Fundamentals Technical Mastery Test v1
Preparation Guide for IBM InfoSphere QualityStage Fundamentals Technical Mastery Test v1
Introduction
This exam validates the technical knowledge required for the purpose of identifying, managing and closing sales opportunities.The test is applicable to sales representatives who demonstrate sales and technical knowledge of the software and targets the technical sales professional who can deliver a comprehensive business solution to customers through solution identification, product differentiation, and competitive positioning.
Passing this test counts towards PartnerWorld competency requirements and helps you attain higher membership levels. This test also entitles you to use the mastery qualification title on your business card. IBM P2090-95 practice exams and IBM P2090-95 practice test have all questions related to this.
Candidate should give this exam who want:
- Understand the algorithms used in QualityStage to improve data quality
- Understand general concept of data quality and QualityStage
- Understand QualityStage commonly used components and processes
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How much IBM InfoSphere QualityStage Fundamentals Technical Mastery Test v1 costs
- Examination Fees: $180 USD
- Examination Name: IBM InfoSphere QualityStage Fundamentals Technical Mastery Test v1
- No of Questions: 41 Questions
- Types of questions: Performance Based Questions
- Passing Score: 23 or higher
- Length of Exam: 90 min
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Sample Questions
Which of the following rules will retain FIELD1 with the longest last name and TITLE equals to “MR”?
- FIELD1: SIZEOF(TRIM(c.“LASTNAME”))>= SIZEOF(TRIM(b.“LASTNAME”)) AND c.TITLE=“MR”
- FIELD1: SIZEOF(TRIM(c.“LASTNAME”))>= SIZEOF(TRIM(b.“LASTNAME”)) AND b.TITLE=“MR”
- FIELD1: SIZEOF(TRIM(c.“LASTNAME”))>= SIZEOF(TRIM(c.“LASTNAME”)) AND c.TITLE=“MR”
- FIELD1: SIZEOF(TRIM(c.“LASTNAME”))<= SIZEOF(TRIM(b.“LASTNAME”)) AND c.TITLE=“MR”
Which of the following is TRUE regarding the use of Critical Fields?
- Critical Fields are fields with missing values.
- Only critical fields of a record are used to calculate the composite weights of the record.
- Critical Fields do not have to match exactly.
- Critical Fields are used to identify fields that must agree in order for records to be linked.
In Standardization Rule Sets, classification table contains what?
- Token, standard form, class, and override rules.
- Class, token, and standard form.
- Field name, data type, and position in record.
- Pattern of tokens, actions to execute, and the logic.
Investigation of data using QualityStage is for _____________________
- transforming the data from one data type to another.
- identifying all the data sources for data consolidation.
- discovering the actual values of missing data.
- verifying the reliability of the data in the fields to be used as matching criteria.
What is DataStage/Quality Stage Administrator client used for?
- Exporting log messages for a job.
- Scheduling jobs to execute.
- Setting up project properties.
- Compiling all the jobs at once.
What does character discrete investigation examine?
- None of the above.
- Multiple domain fields.
- Single domain fields.
- Both single domain and multiple domain fields.
What is DataStage/QualityStage Director client used for?
- Publishing and managing shared information services.
- Compiling and executing a job.
- Enabling run time column propagation for parallel jobs.
- Clearing log messages of a job.
Which one of the following is NOT a survive technique?
- Most Recent
- Probability based rule
- Longest Field
- Most Frequent
Which of the following should be avoided regarding the use of Match Improvement Strategy?
- Set critical values for important fields.
- Use only one Match Pass.
- Add additional passes.
- Adjust weights using weight overrides.
A QualityStage investigate job will NOT ________________
- group records together that are considered duplicates.
- examine single domain and free-form text fields.
- identify invalid and default values.
- discover trends and anomalies.
What does the informational content of a QualityStage Match phase measure?
- The degree of importance of a particular data field.
- The confidence of a match.
- The severity of false positives and false negatives.
- The significance of discriminating value and frequency.
What does the QualityStage Standardization Rule Set contain?
- Information on how to perform calculation with the data.
- Logic for parsing, classifying, and pattern processing the data.
- Rules for eliminating columns of data.
- Rules on which records to keep
Which one of the following is NOT a necessary step in QualityStage to address data quality issues?
- Survive
- Transform
- Standardize
- Investigate
If data value AEJPA 5342G is investigated using an all-C mask, what would the result look like?
- AEJPA 5342G
- AEJPA G
- CCCCBCCCCC
- AEJPA XXXXG
Which of the following is NOT true regarding the use of Match Type?
- Reference Match has one-to-one correspondence.
- Reference Match has many-to-one correspondence.
- Unduplicate Match requires two source files.
- All of the above.
What will a QualityStage match job do?
- Construct consolidated household views of individuals.
- Create cross reference keys.
- Gain complete understanding of data within context.
- Enforce business standards on data elements.
Which of the following is Weight Override used to add or replace?
- Agreement weight
- Disagreement weight
- Calculated weight
- All of the above.
Which of the following is NOT a Match Stage comparison method?
- NAME_UNCERT
- UNCERT
- FREQUENCY
- CNT_DIFF
Which of the following will be generated by a QualityStage Word Investigate job?
- Pattern report and output report.
- Sample report and detail report.
- Pattern report and token report.
- Sample report and token report.
What is Character Concatenate method used for?
- To generate reports for frequency and pattern references.
- To investigate one or more fields to uncover any relationship between the field values.
- To analyze data using one or more character masks.
- All of the above.
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IBM P2090-095 Exam Syllabus Topics:
| Section | Objectives |
| Data Quality Fundamentals | - Core concepts of data quality
- 1. Accuracy, completeness, consistency concepts
- 2. Data profiling fundamentals
|
| Standardization and Parsing | - Data standardization techniques
- 1. Parsing unstructured data
- 2. Rule sets and reference data usage
|
| Matching and Linking | - Match design principles
- 1. Match specifications and scoring
- 2. Deterministic vs probabilistic matching
|
| Data Cleansing and Survivorship | - Record consolidation concepts
- 1. Duplicate resolution strategies
- 2. Survivorship rules
|
| InfoSphere QualityStage Architecture | - Components and workflow
- 1. Parallel job design concepts
- 2. QualityStage stages overview
|