Tableau Server is designed in a way to connect many data tiers. It can connect clients from desktop, mobile, and web. Tableau Desktop is a robust data visualization tool. It is highly available and secure.

It can run on both virtual and physical machines. It is a multi-user, multi-process and multi-threaded system.

Providing such powerful features requires a robust architecture. Let's study the Tableau Server Architecture in this tutorial.

In this tutorial, you will learn

• Tableau Server Architecture
• Data Server
• Data Connectors
• Components of Tableau Server
• Gateway
• Clients

Tableau Server Architecture

The various layers used in the Tableau server are given in the following architecture diagram

Figure 1 Tableau Architecture Diagram

Let's study the different components of Tableau Architecture

1. Data Server

The primary component of Tableau Architecture is the Data sources it can connect to it.

Tableau can connect to multiple data sources. These data sources can be on-premise or remotely located. It can connect to a database, excel file, and a web application all at the same time. Tableau can connect data from heterogeneous environments. It can blend the data from multiple data sources. It can also make the relationship between various types of data sources.

2. Data Connectors

The Data Connectors provide an interface to connect external data sources to Tableau Data Server.

Tableau has in-built ODBC/SQL connector. This ODBC Connector can connect to any databases without using their native connector. Tableau has an option to select both live and extract data. Based on the usage, one can be easily switched between extracted and live data.

• Live Connection or Real time data: Tableau can connect to real time data by linking to the external database directly. It uses the infrastructure of existing database system by sending dynamic MDX (Multidimensional Expressions) and SQL statements. This feature can link to the live data with Tableau rather than importing the data. It makes good the investment done by an organization on a fast and optimized database system. In many enterprises, the size of the database is huge and is updated periodically. In those cases, Tableau works as a front-end visualization tool by connecting to the live data.
• Extracted or In-memory data: Tableau has an option to extract the data from external data sources. We can make a local copy in the form of tableau extract file. It can extract millions of records in Tableau data engine with a single click. Tableau's data engine uses storage such as RAM, ROM and cache memory to store and process data. Using filters, Tableau can extract few records from a huge dataset. This improves the performance, especially while working on massive datasets. Extracted or in-memory data allows the users to visualize the data offline, without connecting to the data source.

3. Components of Tableau Server

The different components present in a Tableau server are:

• Application Server
• VizQL Server
• Data Server

A) Application Server:

The application server is used to provide the authentications and authorizations. It handles the administration and permission for web and mobile interfaces. It assures security by recording each session id on Tableau Server. The administrator can configure the default timeout of the session in the server.

B) VizQL Server:

VizQL server is used to convert the queries from the data source into visualizations. Once the client request is forwarded to VizQL process, it sends the query directly to data source and retrieves information in the form of images. This image or visualization is presented to the user. Tableau server creates a cache of visualization to reduce the load time. The cache can be shared across many users who have the permission to view the visualization.

C) Data Server:

Data server is used to manage and store the data from external data sources. It is a central data management system. It provides metadata management, data security, data storage, data connection and driver requirements. It stores the relevant details of data set such as metadata, calculated fields, sets, groups, and parameters. The data source could extract data as well make live connections to external data sources.

4. Gateway

The gateway channelizes the requests from users to Tableau components. When the client makes a request, it is forwarded to external load balancer for processing. The gateway works as a distributor of processes to various components. In case of absence of external load balancer, gateway also works as a load balancer. For single server configuration, one primary server or gateway manages all the processes. For multiple server configurations, one physical system works as primary server while others are used as worker servers. Only one machine can be used as a primary server in Tableau Server environment.

5. Clients

The dashboards and visualizations in Tableau server can be viewed and edited using different clients. The Clients are Tableau Desktop, web browser and mobile applications.

Clients	Environment
Tableau Desktop	Tableau Desktop is a business analytics tool. It helps to create, view and publish dashboards in Tableau Server. Users can access various data sources and build visualizations in Tableau Desktop.
Mobile	The dashboards from the server can be interactively visualized using mobile browsers and applications. The browser and application can be used to view and edit the contents in the workbook.
Web	Web browsers such as Google Chrome, Safari, Firefox and internet explorer support the Tableau server. The contents and visualizations in the dashboard can be edited through these web browsers.

Summary:

• The architecture of Tableau Server is designed to connect different data sources securely.
• Data Server is the first layer in the architecture. It helps Tableau to connect data in various heterogeneous environments.
• Data connector is the second layer. It helps to connect to various databases using its ODBC connector.
• Tableau can connect the real time live data by connecting the database directly. It can also extract a local copy of data through its in-memory data store for faster processing.
• The components such as Application Server, VizQL Server, and data server act as the third layer.
• The application server is used for authentications and authorizations.
• VizQL is used to convert the SQL query into visualizations.
• Data Server is a centralized data management system used in the architecture.
• A gateway is used to distribute the processes into different components.
• The fourth layer of the architecture are the clients such as Tableau Desktop, web and Mobile.

What is Tableau

What is Tableau?

Tableau is a powerful and fastest growing data visualization tool used in the Business Intelligence Industry. It helps in simplifying raw data into the very easily understandable format.

Data analysis is very fast with Tableau and the visualizations created are in the form of dashboards and worksheets. The data that is created using Tableau can be understood by professional at any level in an organization. It even allows a non-technical user to create a customized dashboard.

The best feature Tableau are

• Data Blending
• Real time analysis
• Collaboration of data

The great thing about Tableau software is that it doesn't require any technical or any kind of programming skills to operate. The tool has garnered interest among the people from all sectors such as business, researchers, different industries, etc.

In this tutorial, you will learn-

• What is Tableau?
• Tableau product suite
• Tableau Desktop
• Tableau Public
• Tableau Server
• Tableau Online
• Tableau Reader
• How does Tableau work?
• Excel Vs. Tableau

Tableau Product Suite

The Tableau Product Suite consists of

• Tableau Desktop
• Tableau Public
• Tableau Online
• Tableau Server
• Tableau Reader

For clear understanding, data analytics in tableau can be classified into two section

1. Developer Tools: The Tableau tools that are used for development such as the creation of dashboards, charts, report generation, visualization fall into this category. The Tableau products, under this category, are the Tableau Desktop and the Tableau Public.
2. Sharing Tools: As the name suggests, the purpose of the tool is sharing the visualizations, reports, dashboards that were created using the developer tools. Products that fall into this category are Tableau Online, Server, and Reader.

Let's study all the products one by one.

Tableau Desktop

Tableau Desktop has a rich feature set and allows you to code and customize reports. Right from creating the charts, reports, to blending them all together to form a dashboard, all the necessary work is created in Tableau Desktop.

For live data analysis, Tableau Desktop provides connectivity to Data Warehouse, as well as other various types of files. The workbooks and the dashboards created here can be either shared locally or publicly.

Based on the connectivity to the data sources and publishing option, Tableau Desktop is classified into

• Tableau Desktop Personal: The development features are similar to Tableau Desktop. Personal version keeps the workbook private, and the access is limited. The workbooks cannot be published online. Therefore, it should be distributed either Offline or in Tableau Public.
• Tableau Desktop Professional: It is pretty much similar to Tableau Desktop. The difference is that the work created in the Tableau Desktop can be published online or in Tableau Server. Also, in Professional version, there is full access to all sorts of the datatype. It is best suitable for those who wish to publish their work in Tableau Server.

Tableau Public

It is Tableau version specially build for the cost-effective users. By the word "Public," it means that the workbooks created cannot be saved locally, in turn, it should be saved to the Tableau's public cloud which can be viewed and accessed by anyone.

There is no privacy to the files saved to the cloud since anyone can download and access the same. This version is the best for the individuals who want to learn Tableau and for the ones who want to share their data with the general public.

Tableau Server

The software is specifically used to share the workbooks, visualizations that are created in the Tableau Desktop application across the organization. To share dashboards in the Tableau Server, you must first publish your work in the Tableau Desktop. Once the work has been uploaded to the server, it will be accessible only to the licensed users.

However, It's not necessary that the licensed users need to have the Tableau Server installed on their machine. They just require the login credentials with which they can check reports via a web browser. The security is high in Tableau server, and it is much suited for quick and effective sharing of data in an organization.

The admin of the organization will always have full control over the server. The hardware and the software are maintained by the organization.

Tableau Online

As the name suggests, it is an online sharing tool of Tableau. Its functionalities are similar to Tableau Server, but the data is stored on servers hosted in the cloud which are maintained by the Tableau group.

There is no storage limit on the data that can be published in the Tableau Online. Tableau Online creates a direct link to over 40 data sources that are hosted in the cloud such as the MySQL, Hive, Amazon Aurora, Spark SQL and many more.

To publish, both Tableau Online and Server require the workbooks created by Tableau Desktop. Data that is streamed from the web applications say Google Analytics, Salesforce.com are also supported by Tableau Server and Tableau Online.

Tableau Reader

Tableau Reader is a free tool which allows you to view the workbooks and visualizations created using Tableau Desktop or Tableau Public. The data can be filtered but editing and modifications are restricted. The security level is zero in Tableau Reader as anyone who gets the workbook can view it using Tableau Reader.

If you want to share the dashboards that you have created, the receiver should have Tableau Reader to view the document.

How does Tableau work?

Tableau connects and extracts the data stored in various places. It can pull data from any platform imaginable. A simple database such as an excel, pdf, to a complex database like Oracle, a database in the cloud such as Amazon webs services, Microsoft Azure SQL database, Google Cloud SQL and various other data sources can be extracted by Tableau.

When Tableau is launched, ready data connectors are available which allows you to connect to any database. Depending on the version of Tableau that you have purchased the number of data connectors supported by Tableau will vary.

The pulled data can be either connected live or extracted to the Tableau's data engine, Tableau Desktop. This is where the Data analyst, data engineer work with the data that was pulled up and develop visualizations. The created dashboards are shared with the users as a static file. The users who receive the dashboards views the file using Tableau Reader.

The data from the Tableau Desktop can be published to the Tableau server. This is an enterprise platform where collaboration, distribution, governance, security model, automation features are supported. With the Tableau server, the end users have a better experience in accessing the files from all locations be it a desktop, mobile or email.

Excel Vs. Tableau

Both Excel and Tableau are data analysis tools, but each tool has its unique approach to data exploration. However, the analysis in Tableau is more potent than excel.

Excel works with rows and columns in spreadsheets whereas Tableau enables in exploring excel data using its drag and drop feature. Tableau formats the data in Graphs, pictures that are easily understandable.

Parameters	Excel	Tableau
Purpose	Spreadsheet application used for manipulating the data.	Perfect visualization tool used for analysis.
Usage	Most suitable for statistical analysis of structured data.	Most suitable for quick and easy representation of big data which helps in resolving the big data issues.
Performance	Moderate speed with no option to quicken.	Moderate speed with options to optimize and enhance the progress of an operation.
Security	The inbuilt security feature is weak when compared to Tableau. The security update needs to be installed on a regular basis.	Extensive options to secure data without scripting. Security features like row level security and permission are inbuilt.
User Interface	To utilize excel to full potential, macro and visual basic scripting knowledge is required	The tool can be used without any coding knowledge.
Business need	Best for preparing on-off reports with small data	Best while working with big data.
Products	Bundled with MS Office tools	Comes with different versions such as the Tableau server, cloud, and desktop.
Integration	Excel integrates with around 60 applications	Tableaus integrated with over 250 applications
Real time data exploration	When you are working in excel, you need have an idea of where your data takes you to get to know the insights	In Tableaus, you are free to explore data without even knowing the answer that you want. With the in-built features like data blending and drill-down, you will be able to determine the variations and data patterns.
Easy Visualizations	When working in excel, we first manipulate the data that is present and then the visualization such as the different charts, graphs are created manually. To make the visualizations easily understandable, you should understand the features of excel well.	Whereas in Tableau, the data is visualized from the beginning.

To conclude, Tableau beats Excel in major areas like the interactive dashboards, visualizations, capabilities to work with large-scale data and many more.

Summary

• Tableau is a powerful and fastest growing data visualization tool used in the Business Intelligence Industry
• The Tableau Product Suite consists of 1) Tableau Desktop 2) Tableau Public 3) Tableau Online 4) Tableau Server and Tableau Reader
• Tableau Desktop has a rich feature set and allows you to code and customize reports
• In Tableau public, workbooks created cannot be saved locally, in turn, it should be saved to the Tableau's public cloud which can be viewed and accessed by anyone
• Tableau server is specifically used to share the workbooks, visualizations that are created in the Tableau Desktop application across the organization
• Tableau online has all the similar functionalities of the Tableau Server, but the data is stored on servers hosted in the cloud which are maintained by the Tableau group.
• Tableau Reader is a free tool which allows you to view the workbooks and visualizations created using Tableau Desktop or Tableau Public.
• Tableau connects and extracts the data stored in various places. It can pull data from any platform imaginable.
• The spreadsheet application used for manipulating the data while Tableau is a perfect visualization tool used for analysis

How to Use JMeter for Performance & Load Testing-Chapter 5

Performance Testing is crucial to determine that the web application under test will satisfy high load requirements. It can be used to analyze overall server performance under heavy load.

Apache JMeter testing tool offers following benefit in Performance Testing

• JMeter can be used to test the performance of both static resources such as JavaScript and HTML, as well as dynamic resources, such as JSP, Servlets, and AJAX.
• JMeter can discover maximum number of concurrent users that your website can handle
• JMeter provides a variety of graphical analyses of performance reports.

JMeter Performance Testing includes:

• Load Testing: Modeling the expected usage by simulating multiple user access the Web services concurrently.
• Stress Testing: Every web server has a maximum load capacity. When the load goes beyond the limit, the web server starts responding slowly and produce errors. The purpose of the Stress Testing is to find the maximum load the web server can handle.

The figure below shows how JMeter load Testing simulates the heavy load:

Create a Performance Test Plan in JMeter

In this tutorial, we are doing a performance analysis of Google.com for 1000 users

Before testing the performance of target web application, we should determine-

• Normal Load: Average number of users visit your website
• Heavy Load: The maximum number of users visit your website
• What is your target in this test?

Here is the roadmap of this practical example

Step 1) Add Thread Group

1. Start JMeter
2. Select Test Plan on the tree
3. Add Thread Group

Right click on the "Test Plan" and add a new thread group: Add -> Threads (Users) -> Thread Group

In the Thread Group control panel, enter Thread Properties as follows:

• Number of Threads: 100 (Number of users connects to the target website: 100)
• Loop Count: 10 (Number of time to execute testing)
• Ramp-Up Period: 100

The Thread Count and The Loop Counts are different.

Ramp-Up Period tells JMeter how long to delay before starting the next user. For example, if we have 100 users and a 100-second Ramp-Up period, then the delay between starting users would be 1 second (100 seconds /100 users)

Step 2) Adding JMeter elements

Now we determine what JMeter elements in this test. The elements are

• HTTP request Default

This element can be added by right-clicking on the Thread Group and selecting: Add -> Config Element -> HTTP Request Defaults.

In the HTTP Request Defaults control panel, enter the Website name under test (http://www.google.com)

• HTTP Request

Right-click on Thread Group and select: Add -> Sampler -> HTTP Request.

In HTTP Request Control Panel, the Path field indicates which URL request you want to send to Google server.

For example, if you enter "calendar" in Path field. JMeter will create the URL request http://www.google.com/calendar  to Google server

If you keep the Path field blank  JMeter will create the URL request http://www.google.com to Google server.

In this test, you keep the Path field blank to make JMeter create the URL request http://www.google.com to Google server.

Step 3) Adding Graph result

JMeter can show the test result in Graph format.

Right click Test Plan, Add -> Listener -> Graph Results

Step 4) Run Test and get the test result

Press the Run button (Ctrl + R) on the Toolbar to start the software testing process. You will see the test result display on Graph in the real time.

The picture below presents a graph of a test plan, where we simulated 100 users who accessed on website www.google.com.

At the bottom of the picture, there are the following statistics, represented in colors:

• Black: The total number of current samples sent.
• Blue: The current average of all samples sent.
• Red: The current standard deviation.
• Green: Throughput rate that represents the number of requests per minute the server handled

Let analyze the performance of Google server in below figure.

To analyze the performance of the web server under test, you should focus on 2 parameters

• Throughput
• Deviation

The Throughput is the most important parameter. It represents the ability of the server to handle a heavy load.  The higher the Throughput is, the better is the server performance.

In this test, the throughput of Google server is 1,491.193/minute. It means Google server can handle 1,491.193 requests per minute. This value is quite high so we can conclude that Google server has good performance

The deviation is shown in red - it indicates the deviation from the average. The smaller the better.

Let compare the performance of Google server to other web servers. This is the performance test result of website http://www.yahoo.com/ (You can choose other websites)

The throughput of a website under test http://www.yahoo.com is 867.326/minutes. It means this server handle 867.326 requests per minute, lower than Google.

The deviation is 2689, much higher than Google (577). So we can determine the performance of this website is less than a Google server.

NOTE: The above values depend on several factors like current server load at Google, your internet speed, your CPU power etc. Hence, it's very unlikely that you will get the same results as above.