Tableau is a powerful data visualization tool widely used in the industry to turn raw data into insightful visualizations. It supports a variety of data connection types and file formats, making it versatile for different data scenarios. Understanding its architecture—from desktop to server—is crucial for effectively utilizing its capabilities.
Tableau Components and Capabilities
1. Data Source Connect Type: Live & Extract
Tableau allows connections to data sources in two main modes: live and extract.
Live Connection: Directly queries the data source in real-time, suitable for situations where data freshness is critical.
Extract Connection: Extracts a snapshot of data into Tableau's proprietary format (Hyper), offering faster performance and offline access.
2. File Types in Tableau
Tableau uses several file types to manage and store its data and visualizations:
Hyper (.hyper): Tableau's high-performance data engine file format for extracts.
TDS (.tds) and TDSX (.tdsx): XML-based formats that store metadata and data source connection information.
TWB (.twb) and TWBX (.twbx): XML-based workbook files (TWB) and packaged workbook files (TWBX) that contain visualization definitions and data sources.
3. Types of Data in Tableau
Tableau manages two main types of data:
Data: Raw data from connected sources used to create visualizations.
Metadata: Information about the data structure, relationships, and characteristics that Tableau uses for visualization and querying.
Tableau Architecture
a) Desktop Architecture
Tableau Desktop, where users create visualizations, consists of four primary components:
Data Source: Where raw data originates, whether live or extracted.
Desktop Application: Interface where users design and create visualizations.
Consumer: End-users who interact with published visualizations.
Server: Centralized repository for publishing and managing workbooks.
Authentication, publishing, and access control are managed through gateways and an application server. Metadata is stored in repositories, while Hyper files store extract data.
b) Server Architecture
Tableau Server extends the capabilities of Tableau Desktop with additional components:
Data Connectors: Facilitate connectivity to various data sources.
Gateways: Manage routing and load balancing across servers.
Application Server: Handles authentication, user interface rendering, and application operations.
VizQL Server: Converts raw data queries into visualizations.
Data Server: Manages data connections and queries.
Data Engine: Processes extract data stored in file storage, facilitating data manipulation operations.
Repository: Stores security information, usage data, and workbook configurations.
Cache Server and Backgrounder: Support caching and background tasks, respectively.
Search & Browse: Enable users to find and explore published content effectively.
Conclusion
Understanding Tableau's architecture—from its desktop components where visualizations are created to the server infrastructure for deployment and management—is essential for leveraging its full potential in data visualization and analytics. By comprehending its data connection types, file formats, and underlying architecture, users can effectively harness Tableau to derive insights and make data-driven decisions.