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Migrating to Production - Data Warehouse ETL Toolkit
Interview Questions
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Job SearchThe migration process can vary depending on many variables, including politics, technical infrastructure, and the ETL toolset. In general, the ETL team is usually part of the development side of things and should avoid the distractions associated with providing first-level production support for the data warehouse, unless your organization is large enough to warrant a dedicated production-support ETL team.
For the purpose, assume that the ETL team exists only in development and hands its work over to a production-support team when the jobs are ready for production. Again, these processes can vary depending on your organizational structure and the tools employed in your environment. This section should be used as a guide to the finishing touches of the ETL lifecycle.
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Data Warehouse ETL Toolkit Related Tutorials |
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| Informatica Tutorial | Data Warehousing Tutorial |
| Networking Tutorial | Hadoop Tutorial |
| Apache Flume Tutorial |
Data Warehouse ETL Toolkit Related Interview Questions |
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| Informatica Interview Questions | Data Warehousing Interview Questions |
| Networking Interview Questions | System Administration Interview Questions |
| Hadoop Interview Questions | MYSQL DBA Interview Questions |
| Data modeling Interview Questions | Hadoop Administration Interview Questions |
| Apache Flume Interview Questions | Informatica Admin Interview Questions |
Data Warehouse ETL Toolkit Related Practice Tests |
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| Informatica Practice Tests | Data Warehousing Practice Tests |
| Networking Practice Tests | System Administration Practice Tests |
| Hadoop Practice Tests | MYSQL DBA Practice Tests |
| Hadoop Administration Practice Tests |
Data Warehouse Etl Toolkit Tutorial
- Requirements
- Etl Tool Architecture
- What The Data Warehouse Is
- The Mission Of The Etl Team
- To Stage Or Not To Stage
- Designing The Staging Area
- Data Structures In The Etl System
- Planning And Design Standards
- The Logical Data Map
- Inside The Logical Data Map
- Building The Logical Data Map
- Integrating Heterogeneous Data Sources
- Mainframe Sources
- Flat Files
- Xml Sources
- Web Log Sources
- W3c Common And Extended Formats
- Name Value Pairs In Web Logs
- Erp System Sources
- Extracting Changed Data
- Defining Data Quality
- Assumptions About The Environment In Which Cleaning And Conforming
- Design Objectives
- Cleaning Deliverables
- Screens And Their Measurements
- Conforming Deliverables
- The Basic Structure Of A Dimension
- The Grain Of A Dimension
- The Basic Load Plan For A Dimension
- Flat Dimensions And Snowflaked Dimensions
- Date And Time Dimensions
- Big Dimensions
- Small Dimensions
- One Dimension Or Two
- Dimensional Roles
- Dimensions As Subdimensions Of Another Dimension
- Degenerate Dimensions
- Slowly Changing Dimensions
- Late-arriving Dimension Records And Correcting Bad Data
- Multivalued Dimensions And Bridge Tables
- Ragged Hierarchies And Bridge Tables
- Technical Note:populatinghierarchybridge Tables
- Using Positional Attributes In A Dimension To Represent Text Facts
- The Basic Structure Of A Fact Table
- Guaranteeing Referential Integrity
- Surrogate Key Pipeline
- Fundamental Grains
- Preparing For Loading Fact Tables
- Factless Fact Tables
- Augmenting A Type 1 Fact Table With Type 2 History
- Graceful Modifications
- Multiple Units Of Measure In A Fact Table
- Collecting Revenue In Multiple Currencies
- Late Arriving Facts
- Aggregations
- Delivering Dimensional Data To Olap Cubes
- Current Marketplace Etl Tool Suite Offerings
- Current Scripting Languages
- Time Is Of The Essence
- Using Database Bulk Loader Utilities To Speed Inserts
- Managing Database Features To Improve Performance
- Troubleshooting Performance Problems
- Increasing Etl Throughput
- Scheduling And Support
- Reliability, Availability, Manageability Analysis For Etl
- Etl Scheduling 101
- Scheduling Tools
- Load Dependencies
- Data-availability Metadata
- Migrating to Production
- Operational Support For The Datawarehouse
- Bundling Version Releases
- Supporting The Etl System In Production
- Achieving Optimal Etl Performance
- Estimating Load Time
- Vulnerabilities Of Long-running Etl Processes
- Minimizing The Risk Of Load Failures
- Purging Historic Data
- Monitoring The Etl System
- Measuring Etl Specific Performance Indicators
- Measuring Infrastructure Performance Indicators
- Measuring Datawarehouse Usage To Help Manage Etl Processes
- Tuning Etl Processes
- Explaining Database Overhead
- Etl System Security
- Securing The Development Environment
- Short-term Archiving And Recovery
- Media, Formats, Software, And Hardware
- Hard Copy, Standards, And Museums
- List Of Topics -metadata
- Planning And Leadership-list Of Topics
- Index Of Topics In Data Warehouse
- Deepening The Definition Of Etl
- The Future Of Data Warehousing And Etl In Particular
Surrounding The Requirements
Etl Data Structures
Extracting
Cleaning And Conforming
Delivering Dimension Tables
Delivering Fact Tables
Development
Operations
Metadata
Responsibilities
Real-time Etl Systems
Conclusions
