Analytics anyone can use.
Data prep anyone can use.
Analytics for organizations.
Cloud analytics for organizations
Tableau Server has many built in features to promote data exploration, collaboration, and security. The Data Server is arguably the most powerful of these tools but is commonly overlooked and underutilized. Answer these questions to see how the Data Server can save you time and increase productivity.
• Are you struggling to manage and update many large extracts while removing duplicates?
• Do you want to refresh your extracts once and automatically update your workbooks?
• Do you want to provide centralized management of your metadata? The ability to author a calculation once and share it with everyone, creating a standardized definition for each field?
• Are you tired of having to deploy database drivers on each users local machines?
• Do you want to simplify how your users access data stored in your databases?
If you found yourself replying 'yes' to any of these questions, then it’s time to unleash the Data Server.
Tableau Data Server allows you to upload and share data extracts, preserve database connections, as well as reuse calculations and field metadata. This means any changes you make to the dataset; calculated fields, parameters, aliases, or definitions, can be saved and shared with others, allowing for a secure, centrally managed and standardized dataset. Additionally, you can leverage your server's resources to run queries on extracts without having to first transfer them to your local machine.
Publishing your data is as simple as choosing "Publish to Server..." from the context menu of the data source you are connected to, entering your credentials and specifying permissions. Connecting to the data server is like connecting to any other database, choose "Tableau Server" from the connection list, authenticate, and select the data source. Data connections can be administered, modified or deleted by accessing 'Data Sources' on Tableau Server.
The Data Server creates a single repository for data and data connections, preventing duplication and confusion. All workbooks connecting through the Data Server automatically update when the original data source updates. Scheduling automatic refreshes of extracts allows everyone to have the most up to date dataset and saves space by eliminating the need for duplicate extracts. By having users connect to a single shared extract you reduce the number of queries made to the original database, resulting in fewer API calls and lower service costs, particularly when connecting to Salesforce.
Queries against large data extracts are run directly by the Data Server hardware resulting in shorter processing times and without needing to transfer the extract to the local machine. Imagine million row extracts, several gigabytes in size that no longer need to be copied to the local machine. Instead all processing is completed by the server's dedicated multi-core hardware.
Credentials for live database connections can be embedded into the published data sources, thereby allowing the Data Server to act as a proxy and not requiring each user to authenticate to the original database.
Additionally, a single set of database drivers installed on the server can handle all database connections for all users, eliminating the need for each user to install and update drivers on their local machines. This is an enormous administrative time saving in large desktop deployments.
Data source level calculations, aggregations, parameters, sets, groups, joins between tables, and measures and dimensions, now become metadata that is standardized for all users and no longer needs to be recreated for each workbook. A single database administrator (DBA), who best understands the data can create hierarchies and rename or hide fields to simplify a business user's choices. If any changes are made to the data's structure the DBA can make those modifications and they will propagate to all workbooks using that data source.
In addition to maintaining the metadata for a data source, a data source admin can create permissions and user level filters to control each user's access to portions of the dataset. This means storing a single data connection or extract without the need to create duplicate data sets for each user. Permissions for editing data source metadata can be limited to a few named users responsible for data integrity and administration. This way the business user can focus on deriving insights from the data and not the underlying database structure, proper field definitions or data integrity.
Explore how data server can help automate and standardize your workgroups data sources by acting as a fast and secure proxy and extract repository. View our Data Server video for more information.