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Exam Objectives:
The IBM P2090-044 exam is designed to test a candidate's technical mastery in IBM InfoSphere Information Server for Data Quality Fundamentals. The exam objectives include:
- Understanding data quality concepts and the importance of data quality
- Understanding the architecture of IBM InfoSphere Information Server for Data Quality
- Installation and configuration of IBM InfoSphere Information Server for Data Quality
- Data profiling and analysis using IBM InfoSphere Information Server for Data Quality
- Data quality rule development and implementation
- Data quality exception handling and reporting
- Integration with other IBM InfoSphere Information Server components
These objectives are designed to test a candidate's knowledge of IBM InfoSphere Information Server for Data Quality and their ability to implement and use it effectively in a real-world scenario.
Exam Details:
The IBM P2090-044 exam is a technical mastery exam that is delivered in a proctored environment. The exam consists of 46 multiple choice questions and has a time limit of 90 minutes. The passing score for the exam is 63%.
The exam is delivered through the Pearson VUE testing system and can be taken at any Pearson VUE testing center. The cost of the exam varies by location and can be found on the Pearson VUE website.
The exam format is computer-based and candidates will need to have a basic understanding of IBM InfoSphere Information Server for Data Quality before attempting the exam. Candidates are not allowed to bring any materials into the testing center and will be monitored throughout the duration of the exam.
Related Books:
There are several books that can help a candidate prepare for the IBM P2090-044 exam:
- "IBM InfoSphere Information Server for Data Quality Fundamentals" by IBM Redbooks
- "Data Quality Assessment" by Arkady Maydanchik
- "Data Quality for Analytics Using SAS" by Gerhard Svolba
- "Data Quality: Concepts, Methodologies and Techniques" by Carlo Batini, Monica Scannapieco, and Chiara Francalanci
These books cover topics such as data quality concepts, data profiling, data quality rules, and exception handling. They can help a candidate gain a better understanding of IBM InfoSphere Information Server for Data Quality and prepare them for the exam.
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