Kursbeskrivning: Validating Data with Rules in Information Analyzer 8.1.1 - Web Based Training

Note: This is a self-paced online course in which the Guided Tour Product Simulation requires no installations: Everything is through your IE 5.0+ browser. Please DO NOT make travel arrangements for this course. After you receive confirmation that you are registered, just follow the instructions to access the course.

This browser-based product simulation let's you "learn-by-doing" in a case-study scenario in which you solve a 'real-life' business problem - no installations needed just a browser and a passion to learn.

By the end of this training you'll have a better understanding of this InfoSphere product's terminology, an overview of its architecture, and a better understanding of how it can be implemented.

You can learn more about the FlexLearning library:

http://www-304.ibm.com/jct03001c/services/learning/ites.wss/us/en?pageType=page&c=a0011797

USA IBM Training Registrar:

• Phone: (978) 899-2188
• Fax: (978) 899-2188
• e-mail: iiseduc@us.ibm.com

Before you enter the Guided Tour Product Simulation, we'll begin this tutorial by talking about the Rules' analysis capability. We'll discuss use cases in the field and see how Rules are applied in the 'real world'. We'll see how this ties in to the auditing of data and data quality in your organization. We'll see how the new functionality fits in with the existing Information Analyzer technology and extends it beyond initial data profiling and analysis functionality to Rules' monitoring capability. Here, we'll talk about how Rules will contribute to an ongoing process of managing and monitoring data quality over time and how they can help improve data quality.

Then we'll dive deeper into the core concepts, the architecture, and the both the extension of data quality assessment work as well as continual application of 8.1.1's data quality monitoring capabilities. We'll discuss basic practices of building Rules such as scoping, reusability, naming conventions, and association of Rules with business terms. We'll answer questions such as "What is a Rule?", "What are metrics?", and "How do I use benchmarks?".

Next, in a Guided Tour Product Simulation, you will build a simple Rule. You'll define it and apply it to a particular set of data. After executing that Rule and viewing its output, you will then use that same Rule definition to build a second Rule.

You will examine the pre-built functions and incorporate a function into a Rule Definition. You'll build a Rule Definition associated with reference information so that you can see how multiple pieces of data can be linked or associated together within a Rule Definition itself. We'll discuss different styles of Rules (Assessment style versus Monitoring styles) and the critical need to 'positively' frame Rules. You'll then organize Rules into folders. Next, you'll take multiple Rules and bring them together into a Rule Set. This way, you will achieve higher levels of evaluation and understanding around your data source. You will see how data is evaluated in a Rule Set. You will then see how graphs and trends are automatically generated for you and examine them. Then you will see how to use Metrics that allow you to identify trends in data quality.

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Roadmaps:

• Information Analysis – Business Analyst/Data Steward

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This basic course is for:

• Data Analysts
• Data Quality Specialists
• Business Analysts validating Data Rules
• People familiar with Information Analyzer V8.1 and 8.01
• People interesting in learning about the Data Rules functionality
• Data Stewards who monitor data quality
• Managers setting criteria about data quality
• ETL Developers

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You should have:

• Some understanding of data source, table, and column structures
• Rule developers will need to understand business definitions and terms at your company (For instance, criteria such as that for a SSN, it must not be null, it must be 9 numeric digits, etc.)
• Some programming experience is helpful but not required
• Some introductory training on Information Analyzer (Be able to navigate the UI and menu structure, understand how IA roles are defined, and know how to do an import and how to organize projects)

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• Build a Rule Definition and link it to the data
• Execute, test, and evaluate Rules
• Evaluate data results and adjust Rules as needed
• Navigate UI to build and apply Rules
• Understand styles of Rules and differing uses of Rules
• Build a Reference Rule, a Rule with a function, and a Rule Set

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• Confidence In Your Data
• Consequences of Poor Data Quality
• The Cause of Poor Data Quality
• What Constitutes Data Quality?
• Systematize Data Quality
• The Concept of Rule Definitions for Two Uses
• The Concept of Rule Sets
• Building Rule Definitions
• Evaluating (Executing) Rules
• Benchmarks, Baselines, and Metrics

Guided Tour Product Simulation:

• Build a Rule
• Re-use a Rule Definition
• Build a Reference Lookup Rule
• Create a Baseline
• Create a Rule with a Function
• Best Practices: Styles of Rules
• Organize Your Work
• Rule Sets: Validate an Entire Data Source
• Identify Patterns and Trends in Data
• Create a Metric

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Mandatory: Learners must have a screen resolution set to a minimum of 1024