Tableau helps people see and understand their data. Gone are the days when insight from data was restricted to a few erudite analysts and IT.
The era of data discovery presents a new set of challenges for IT. There is still the necessity for metadata management, and securing sensitive information. Ability to scale becomes of greater importance than ever—because the value of your data increases and correlates with the number of people who are able to make use of it.
This paper will address all of the these issues and more, so you can ensure you have a solution that can respond to this new, rapidly advancing concept of data discovery and self-service analytics.
We've also pulled out the first several pages of the whitepaper for you to read. Download the PDF on the right to read the rest.
A new generation of business intelligence and visual analysis software puts data into the hands of the people who need it. Slow, rigid systems are no longer good enough for business users or the IT teams that support them. Competitive pressures and new sources of data are creating new requirements. Users are demanding the ability to answer their questions quickly and easily. And that’s a good thing.
Tableau Software was founded on the idea that data analysis and subsequent reports should not be isolated activities but should be integrated into a single visual analysis process—one that lets users quickly see patterns in their data and shift views on the fly to follow their train of thought. Tableau combines data exploration and data visualization in an easy-to-use application that anyone can learn quickly. Anyone comfortable with Excel can create rich, interactive analyses and powerful dashboards and then share them securely across the enterprise. IT teams can manage data and metadata centrally, control permissions and scale up to enterprise-wide deployments.
This overview is designed to answer questions common to IT managers and administrators and help them support visual analysis software deployments of any size. In this document we cover:
- Tableau Architecture
- Deployment Models
- System Administration
- Data Strategy
- Metadata Management
- Mobile Deployment
Tableau has a highly scalable, n-tier client-server architecture that serves mobile clients, web clients and desktop-installed software. Tableau Desktop is the authoring and publishing tool that is used to create shared views on Tableau Server.
Tableau Server is an enterprise-class business analytics platform that can scale up to hundreds of thousands of users. It offers powerful mobile and browser-based analytics and works with a company’s existing data strategy and security protocols. Tableau Server:
- Scales up: Is multi-threaded
- Scales out: Is multi-process enabled
- Provides integrated clustering
- Supports High Availability
- Is secure
- Runs on both physical and Virtual Machines
One of the fundamental characteristics of Tableau is that it supports your choice of data architecture. Tableau does not require your data to be stored in any single system, proprietary or otherwise. Most organizations have a heterogeneous data environment: data warehouses live alongside databases and Cubes, and flat files like Excel are still very much in use. Tableau can work with all of these simultaneously. You do not need to bring all your data in-memory unless you choose to. If your existing data platforms are fast and scalable, Tableau allows you to directly leverage your investment by utilizing the power of the database to answer questions. If this is not the case, Tableau provides easy options to upgrade your data to be fast and responsive with our fast in-memory Data Engine.
Tableau includes a number of optimized data connectors for databases such as Microsoft Excel, SQL Server, Oracle, Teradata, Vertica, Cloudera Hadoop, and many more. There is also a generic ODBC connector for any systems without a native connector. Tableau provides two modes for interacting with data: Live connection or In-memory. Users can switch between a live and in-memory connection as they choose.
Live connection: Tableau’s data connectors leverage your existing data infrastructure by sending dynamic SQL or MDX statements directly to the source database rather than importing all the data. This means that if you’ve invested in a fast, analytics-optimized database like Vertica, you can gain the benefits of that investment by connecting live to your data. This leaves the detail data in the source system and send the aggregate results of queries to Tableau. Additionally, this means that Tableau can effectively utilize unlimited amounts of data – in fact Tableau is the front-end analytics client to many of the largest databases in the world. Tableau has optimized each connector to take advantage of the unique characteristics of each data source.
In-memory: Tableau offers a fast, in-memory Data Engine that is optimized for analytics. You can connect to your data and then, with one click, extract your data to bring it in-memory in Tableau. Tableau’s Data Engine fully utilizes your entire system to achieve fast query response on hundreds of millions of rows of data on commodity hardware. Because the Data Engine can access disk storage as well as RAM and cache memory, it is not limited by the amount of memory on a system. There is no requirement that an entire data set be loaded into memory to achieve its performance goals.
Tableau Server Components
The work of Tableau Server is handled with the following four server processes:
Application Server: Application Server processes (wgserver.exe) handle browsing and permissions for the Tableau Server web and mobile interfaces. When a user opens a view in a client device, that user starts a session on Tableau Server. This means that an Application Server thread starts and checks the permissions for that user and that view.
VizQL Server: Once a view is opened, the client sends a request to the VizQL process (vizqlserver.exe). The VizQL process then sends queries directly to the data source, returning a result set that is rendered as images and presented to the user. Each VizQL Server has its own cache that can be shared across multiple users.
Data Server: The Tableau Data Server lets you centrally manage and store Tableau data sources. It also maintains metadata from Tableau Desktop, such as calculations, definitions, and groups. The published data source can be based on:
- A Tableau Data Engine extract
- A live connection to a relational database (cubes are not supported)
Read more about the Data Server in the section Data Strategy below.
Backgrounder: The backgrounder refreshes scheduled extracts and manages other background tasks.
Gateway/ Load Balancer
The Gateway is the primary Tableau Server that routes requests to other components. Requests that come in from the client first hit the gateway server and are routed to the appropriate process. If multiple processes are configured for any component, the Gateway will act as a load balancer and distribute the requests to the processes. In a single-server configuration, all
processes sit on the Gateway, or primary server. When running in a distributed environment, one physical machine is designated the primary server and the others are designated as worker servers which can run any number of other processes. Tableau Server always uses only one machine as the primary server.
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