Tag Archives: General Features

Data Compressions

Data compression is to your database what zip files are to the file system. It significantly reduces data storage and disk operations, both leading to improved performance. Storage is commonly reduced by 40-90%, depending of the compression type used: Row or page on staging areas and data warehouse respectively. Performance can often be improved by

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Multithreaded Execution

By default, execution of SSIS packages, data cleansing, dimension and cube processing etc. is performed single threaded. This means that TX2014 will only initialize calls towards SQL Server from a single thread (single process). With multithreaded execution it is possible to configure execution packages with a user-defined number of concurrent threads, which will execute against

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Team Development

TX2014 supports multiple concurrent developers, effectively allowing true team development. In timeXtender products previous to tX2012, objects were locked at project level and although there are ways to use multiple projects to support multiple concurrent developers, a project is normally considered as the smallest amount of work for a single developer. In TX2014, it is

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Template Data Sources

When you need to extract data from multiple data sources of nearly identical structure, template data sources is there to help. In logical terms it is based on a single data source (the template) that is used to extract the source Meta data such as tables, views, fields, data types. An unlimited number of additional

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Multiple timeXtender Projects

In TX2014 you design and build your data warehouse solution within the context of a project. A project can be considered as a container that holds all the objects such as data sources, staging databases, tables, views, stored procedures, dimensions, cubes etc. TX2014 comes with one project out of the box, but you can add

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Export / Import Projects

The Meta data of a TX2014 project is persisted in the repository, using a SQL Server database for storage. This optionally also include version control and multiple environments transfer for automated promoting Meta data from development to test, QA, production environments. In addition it is also possible to export and import the Meta data in

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Data Warehouse

The overall purpose of a data warehouse is to integrate corporate data from various internal- and external data sources. Data is collected over time and stores historical events that are often not persisted in the source systems and is also commonly referred to as the single version of the truth, making the data warehouse an

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Data Staging

The data staging area is a temporary location for data between the source systems and the data warehouse. This is where source data is copied to in the extract phase of ETL and is the first integration point for data coming from multiple source systems. This is also where the majority of data cleansing and

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Data Lineage Diagrams

Most data warehouse developers have experienced the challenge of answering a common question like “what data source fields are we using for this measure?” and sometimes you can even add “and what are we doing to it in the ETL process?” If you are one of the many, that either do not have complete end

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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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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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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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SQL Snippets

This new feature is the SQL counterpart to Business Functions. It is parameterized and reusable SQL. When you use SQL Snippets your SQL transformations will be strongly typed. This means that when a table or fieldname is changed, the transformations that use them are also changed. To add a snippet From the Tools menu, in

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QlikView modeler & script generator

QlikView® is a very popular presentation tool, which allows business users to rapidly build views and dashboards. The back end implementation however very easily gets quite complex and time consuming, due to the need for scripting. Using the TX2014 drag and drop interface, you create QlikView® models ready for import into your QVW documents, thus

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