Windows-based server software installed on a centrally located physical or virtual machine. This software orchestrates the ingestion of data from various sources. This separates data movement from the desktop software, while ensuring data never leaves a users environment.
2. The ODX Storage
A SQL database or Azure Data Lake where raw data is stored after ingestion from sources. By storing data in it's raw form, it can be used for later analysis, or retrieval.
3. The MDW Storage
A SQL Database or Synapse Dedicated SQL Pool where data from multiple sources is cleansed, transformed, and consolidated into a single version of truth.
4. SSL Endpoints
A subset of related data combined into a single model or "mart". This model can be exported to multiple endpoints such as Power BI, Qlik, Tableau, Analysis Services, or CSV.
5. TimeXtender Portal
A web portal handling the administration of your TimeXtender Data Estate. Instances hold the storage connection details as well as maintain the configuration information implemented in TimeXtender Desktop.
6. TimeXtender Desktop
Windows-based Desktop-client software where each instance can be configured & implemented through a single, integrated user-interface.
When working in a sandbox environment, the Desktop and Server software can be installed, run, and controlled all from the same machine.
However, in production-ready setups, multiple concurrent users are necessary. Ideally, each client runs their own local instance of TimeXtender Desktop and connect remotely to the ODX Server.
Please note: With a client-server setup, the ODX Server IP Address or Hostname must be "reachable" by each client machine. More Info.
Server software should be installed on a centrally located server so it can be controlled by multiple clients.
Each TimeXtender user should install and use TimeXtender Desktop on their own "client" machine
AdventureWorks is a commonly used sample dataset that closely represents common online transactional processing (OLTP) systems. It is based on a fictitious manufacturer and distributor of bicycles, outdoor equipment, and apparel. In this training we will perform common extract, transform, and load (ETL) techniques on this data. To become more familiar with the dataset, click to expand and explore the AdventureWorks entity relationship diagram.
MAP Data Source
By Mapping a Data Source to an ODX instance you are specifying which ODX should be allowed to connect and transfer this source data. This will be useful later when you have multiple ODX instances.