Oversikt
| Kurskode | 1I017NO | Leveringsform | Web Based Training |
|---|---|---|---|
| Varighet | 7.0 timer | Kurstype | |
| Listepris |
NOK 1 400,00 u. moms
NOK 1 400,00 m. moms |
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'll use QualityStage to cleanse data and walk through the important steps in doing so - no installations needed just a browser and a passion to learn.
By the end of this training you'll have a better understanding navigation of QualityStage, its terminology, 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
You'll begin by learning about the concepts involved. We'll define QualityStage and talk about the types of problems that its solves. We'll dive deeper and discuss its architecture and take a closer look at how it works. Then, In a case study, you'll use QualityStage on a sample of data to ensure that an insurance company more effectively markets its products and services to its customers. You will:
- Solve Data Anomalies
- Parse Data Values and Standardize Them
- Match Customers Across Several Sources (Identify who has what policy)
- Create A Master Customer List to Present (to the Marketing Dept.)
- Identify Customers By Household
You will use QualityStage to cleanse the data and identify customers across domains and store it in a way that can be viewed by any number of reporting tools (Such as Business Objects)
Specifically, you will read up on the case-study, look at a data flow plan, and then use the product to go through the various phases. These include Investigation, Standardization, Matching, and Survivorship. Given some sample data in a file, you will configure QualityStage, run jobs, review data, and determine next steps.
Målgruppe
This basic course is for:
- Data Quality professionals
- Application Developers
- ETL Developers
- Database Administrators
- Business Analysts
- Data Architects
- Data Integration and/or Migration teams
Forkunnskaper
This course assumes that you have existing knowledge in the following areas:
- Some familiarity with databases is helpful although SQL knowledge is not needed
- Understanding of basic data structures including some knowledge of data classification and data types is needed
- Some experience with programming is helpful
- Basic understanding of Windows or OS's and a minimal understanding of Networking
- How to use an FTP tool
- Familiarity with data integration challenges is a plus
Mål
You'll understand what QualityStage is, its architecture, how it works, and gain a familiarity with its terminology and UI. You'll learn about business challenges that data quality presents and how QualityStage helps you understand data. You'll learn how to link records to identify a unique customer/material/vendor, choose the data that will go into your new database, clean up the data already in a database, configure QualityStage to standardize, match, and survive data
Nøkkelemner
- Data Integration Phases
- Discover
- Prepare
- Transform and Deliver
- What Is Data Quality
- Data Quality Challenges
- Inconsistent Standards
- How QualityStage Helps
- Architecture Client Server
- Investigate Phase
- Standardize Phase
- Match Phase
- Survive Phase
- Guided Tour Simulation:
- Configure Investigation Stage The Investigation Phase
- Character Discrete Type T Investigation
- Wrap Stage in a Job and Run It
- Look at Investigation Report
- Review of Investigations
- The Word Investigation
- Create and Run the Job
- Display Word Investigation Report
- Recap and Requirements
- Configure Standardization Stage You Must Define the Output File
- Choose the Rule-Set
- Choose Fields Rule-Set Will Affect
- Create, Deploy, and Run Job
- Configure Match Stage Define Input File for Stage
- Overlay Definitions
- Define the Output File
- Add Fields to Beginning
- Configure the Match Stage
- Choose Blocking Criteria
- Choose Match Criteria
- Define the Extract
- Look at Match Results
- Build a Second Pass
- Perform Weight Override
- Data Flow Summary
- Configure Survive Stage Survive Stage
- Define Input File
- Define Output File
- Configure Survive Stage
- Choose Field to Define Group
- Create, Deploy, and Run Job
- Look At Output File
- Additional Survive Rules
- Most Frequent Non-Missing Technique
- Most Recent Data
- Second Match Stage: Householding Define the Output File
- Create a TEMP Field
- Redefine the 22 Bytes
- Configure Second Match
- Create First Pass
- Select Blocking Criteria
- Select Field to Match On
- Define How Data Moved to Buckets
- Create, Deploy, and Run Job
- Iterate a Pass
- Perform a Weight Override