Tag Archives: ETL

Data Warehousing and ETL for Microsoft Dynamics CRM Online With timeXtender

Find out how timeXtender solves the issue of extracting data from CRM Online into an on-premise data warehouse. See how the timeXtender CRM adapter, enables you to pull data from all standard entities such as accounts, contacts, leads, opportunities, etc. as well as from any custom entities and fields. Date, time and registration At present

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Documentation – Full Printable

- Fully automated generation of Documentation, including full version control to ensure that the generated documentation corresponds to the deployed version of the project. Comments can be added to all elements in the project. The template can be modified and the documentation comes as a hyperlinked PDF document. The documentation is valid for IT Audit

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Multiple Environment Deployment

Before I started using Multiple Environment Deployment, I had to build cubes outside of office hours, so that I didn’t disturb users in their work if I made mistakes or had to deploy new cubes.” Flemming Andersen, IT Manager, JP Group   As the BI backend has become a mission critical asset, it is often

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Trace

Complete trace of a single entity within the Meta model. Trace between the cube and data source(s). See [Data Lineage Diagrams]

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Version Control

Version control, also known as revision control, manages the changes done to a project in TX2014. A project is defined as the collection of objects such as tables, dimensions and cubes but also includes settings for source and destination connections. Version control has two major benefits, serving the purposes of documentation as well as the

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Data Quality

- Enforcement of implicit and explicit primary- and foreign key constraints. – Enforcement of threshold values. – Row or value based checkpoints and notifications.

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Reverse Engineer Data Warehouse

If you have an existing SQL Server data warehouse, the reverse engineering feature allows you to import tables, views, primary key and foreign key constraints, stored procedures and user-defined functions into the TX2014 meta model. This is especially useful when converting your hand coded data warehouses into timeXtender, and means that you do not have

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Automated Performance Optimization

- Hash-bytes – Compressions: supports row-and table based compression on both staging and data warehouse. Implemented automatically based on table classification. Can be manually configured in advance mode.

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Data Warehouse Hierarchy Builder

- Visual builder for GL acccounts dimension (balance sheet, income statement). – Include custom rollup formulas (dimension calculations). – Generic usage for mapping any structure into reporting format.

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Indexes

TX2014 supports both automatic created indexes as well as rich capabilities to add your own non clustered indexes to fine tune the load performance of your data warehouse platform. Automatic indexes are added based on table classification such as dimension/fact/large/normal and transformations done on a table, to ensure well performing code out of the box.

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Lookups

One of the most commonly features of TX2014 is the ability to look up a value across tables using a simple drag and drop interface. Lookups can be used to perform both simple tasks as fetching a single value from a related table based on one or more joined fields, but also in more complex

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Move Projects As XML Between Installations

- Move or copy an entire solution between installations, customers, or environments. – Works across different SQL Server versions and editions.

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Multithreading

As part of getting the best load performance, it is possible to design execution packages for multi-threaded execution – or parallel execution, using a user-defined number of threads per package. The flexible design capabilities allow configurations such as a single threaded master package that controls multi-threaded sub packages. Another common configuration is a “string of

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Table Partitions

Table partitioning offers the ability to separate the contents of a logical table into separate physical storage units. This can greatly improve performance as only the partition(s) affected by a query, an insert or update operation will be touched. TX2014 manages partitions with a template based approach, which allows easy reuse of partition patterns across

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Time Dimensions

The most common of all dimensions is time, since there is virtually no reporting or analysis done without the context of when. A time or calendar dimension can always be derived of source data, as any other dimension. Additionally you can also take advantage of the time table and time dimension features in TX2014 to

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Incremental Load

To improve load performance for very large tables, a feature called Target-based Incremental Load was introduced with timeXtender version 4.5. This feature controls how data is inserted, updated, and deleted between the raw and valid table instances. The Target-based Incremental Load feature is especially useful in scenarios where the source system cannot reliably identify new

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