By Hari Poluru
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History
Heritage
 Company traces its roots to academic research in Stanford University’s Department of Computer
Science between 1997 and 2002
 Founded in Seatle 2003
 Patended technology named VizQL
 Growing revenue ~$72M 2011
 Started at Seattle
Organization
 Management Team consists of Former Prof and PHD scholars from Stanford and Leaders from
Ventures caps
 ~around 600 employees
 Incorporated in the US
 HQ in the US
 8 offices in 5 countries
 Customers and partners in all continents
 Tableau's products have been incorporated into product suites of multiple independent software
vendors, including Oracle for its Oracle Essbase Visual Explorer product
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All About
Fast Time-to-Value
 With traditional OLAP, constructing cubes is time consuming and requires
expert skills. This process can take months, and sometimes over a year
 In addition, the cube must be constructed before it can be calculated, a
process which itself can take hours. And, all this must occur before analysis
or reporting can be performed before the user even sees answers to his
questions
 Because the data could be loaded in memory, creating analysis in Tableau
takes seconds. There is no pre-definition of what is a dimension – any data
is available as a dimension and any data is available as a measure
 The time implementing Tableau is spent locating data, and deciding what
analysis is interesting or relevant to solving the business question.
Typically, this process takes lesser time
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Why ?
Easy to Use
 The entire end user experience in Tableau is driven by the “click.” End users enjoy using Tableau
because it works the way their mind does
 Each time they want to review the data sliced a new way, they simply click on the data they want to
evaluate. Because Tableau could operate in memory, with each click all data and measures are
recalculated to reflect the selection
 Users can go from high level aggregates (e.g., roll up of margin on all products in a specific line) to
individual records (e.g., which order was that?) in a click – without pre-defining the path to the
individual record
Powerful
 Because queries and calculations could be performed in memory, they are extremely quick. In
addition, if in memory feature is in use, the performance of Tableau is not constrained by the speed
of the underlying source
 Even if the underlying data is stored in a system which has poor query performance (for instance, a
text file), the performance is always optimal because the data could be loaded in memory. Tableau
also compresses data as it is stored in memory, allowing large amounts of data to be stored
 Patented VizQL technology makes Tableau acts more faster
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What data can I analyze with Tableau?
• Your data needs to be in a database, spreadsheet or structured text format
before you can analyze it with Tableau. Databases include relational
databases and multidimensional OLAP databases. The specific databases
your copy of Tableau can connect to depends on your purchase options.
• To see which data sources your copy of Tableau can connect to, select Data
> Connect to Data. Any data source that is not supported by your version of
Tableau is grayed out. Contact Tableau to upgrade your database
accessibility options.
• Tableau can connect to many relational data sources, and two OLAP/cube
data sources: Oracle Essbase and Microsoft Analysis Services. Tableau
queries the data using standard drivers and query languages (like SQL and
MDX) and presents a visual analysis of the data.
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Types
•
Tableau Server provides browser-based visual analytics tool and just a few clicks, users can publish
dashboards and reports with current data automatically customized to the needs of everyone across
your organization. It deploys in minutes and users can produce thousands of reports without the need
of IT services.
•
Tableau worker is a additional Tableau tool to use in distributed environment to support more
browsing & searching activities to handles a large number of tasks and refresh extracts. Workder will
be a dedicated machine to run several background task processes.
•
Tableau Desktop is a desktop data visualization application(report development tool) that analyze
virtually any type of structured data and produce highly interactive, beautiful graphs, dashboards,
and reports in just minutes. After a quick installation, developers can connect to virtually any data
source from spreadsheets to data warehouses and display information in multiple graphic
perspectives.
•
Tableau Reader is a free viewing application that lets anyone read and interact with packaged
workbooks created by Tableau Desktop.
•
Tableau Public is a free service that will create and share data visualizations on the web. Thousands
of users can use to share data on websites, blogs and through social media like Facebook and Twitter.
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n-Tier Client-Server Architecture
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Data Layer and Data Connectors
Data Layer
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.
Data Connectors
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
 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.
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Server
Tableau server have its own Apache web server and it will configure automatically when the installation is
processing.
Tableau authorization is handled by the following:
 Roles and permissions: Define specific capabilities that users can or cannot perform
on certain objects in Tableau. A role is a set of permissions that administrators can use
as-is or customize.
 Licensing and user rights: Control the maximum set of permissions that a user can have.
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Server Components
Tableau Server Components
The work of Tableau Server is handled with the following server processes:
 Application Server
Application Server processes (wgserver.exe) handle browsing and permissions for the Tableau Server web and
mobile interfaces
 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
 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.
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How it Works?
The diagram describes how tableau works
between the client's web browser, web
server(s) and Tableau Server.
1. When a user visits the webpage and it
sends a request to web server.
2. The web server sends a request to
Tableau Server.
3. Tableau server creates a request and
check the authentication and reply to
web server.
4. Web server process the request &
construct the view’s URL & passes to
web browser.
5. Browser sends a request to Tableau
Server for the continues request.
6. Tableau Server checks the web browser
request and it must be redeemed within
three minutes after they are processed
and sends back the final URL for the
embedded view.
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Tableau Desktop
Can create graphs, report, dashboard using Tableau Desktop and publish reports & dashboards to Tableau portal
for business use. separated into three tiers:
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•
•
Visually Analyze Data
Build Interactive Dashboards
Share and Interact
Tableau workspace:
Tableau desktop contains Data window, view cards, toolbar, worksheet, workspace controls, dimensions area,
measures area, set, parameter, status bar, worksheet bar.
Workbooks and Sheets:
Worksheets - can contain worksheets and dashboards. A worksheet is where you build views of data by
dragging and dropping fields onto shelves.
Workbooks – It contain one or more worksheets or dashboards and hold all of your work. It allow to organize,
save, and share results.
Dashboard is a combination of several worksheets that can arrange for presentation or to monitor the data.
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Connect to Data
To start analyzing your data, connect Tableau desktop to data sources and data source can be as an Excel
workbook, Teradata table, Oracle data warehouse. After connecting, the data fields become available
in the Data window to create your reports. You can perform many actions with your data as below,
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Support multiple data source
Connecting to a Custom SQL Query
Editing the Connection
Renaming the Connection
Duplicating the Connection
Replace Data Source
Exporting the Connection
Refreshing the Data
Closing the Connection
Connecting to Multiple Tables
Creat table joins
Adding Tables to the Data window
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Connect to Data

Once the server information / credentials are provided, the user can select a schema to connect to
and pick a table.

Through the multiple tables options, it is possible to create a join between two tables and use them
both in a single report.
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Tableau also provides a custom SQL option for freeform queries to retrieve data exactly as the user
wants it. This is useful in cases that require operations to be done on the data before importing the
dataset for reporting.
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Tableau also allows connection to pre-existing OLAP cubes created by a variety of tools.
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Tableau connections to the native .tde extract canisters can be set up. TDE extracts are Tableau’s
method of caching data locally, so as to reduce database hits for frequently accessed reports. They
also allow tableau workbooks to be packaged, standalone reports that can be distributed for
viewing without having to connect to the data source.TDE extracts can be refreshed manually
through tableau desktop or be scheduled for periodic refresh through the enterprise edition.
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Data sources supported by Tableau
Actian Vectorwise 1.5 and later
MySQL 4.0 or later
Aster Data nCluster 4.5 and later
Netezza release 4.6 or later
Cloudera Hadoop Distribution via Hive (CDH3u1,
which includes Hive .71, or later)
OData
Firebird 2.0 or later
Greenplum 4.x and later
IBM DB2 (9.1 or later) for Linux, UNIX, and
Windows
MapR Distribution for Apache Hadoop
Microsoft Access 2003 or later
Microsoft SQL Server Analysis Services 2000,
2005, 2008,2008R2, 2012 (Multi-dimensional
mode only)
Microsoft PowerPivot 2008 (whether or not
published in Sharepoint)
Microsoft Excel 2003 or later
Microsoft SQL Server 2000, 2005, 2008, 2008R2,
or 2012
Microsoft Windows Azure Marketplace
DataMarket
Oracle Hyperion Essbase 11.1.1
Oracle Database 10.x or later
ParAccel Analytic Database (PADB)
version 3 and later
PostgreSQL 7.0 or later
Progress OpenEdge 10.2B patch 4 or later
SAP NetWeaver Business Warehouse 7.00
with SP20+ recommended. Also requires
SAP GUI for Windows 7.20 Client
Sybase IQ 15 and later
Teradata 6 or later
Text files, comma delimited format
Vertica 4.x or later
Also, many databases that are ODBC
Version 3.0 compliant
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Data Source Relationships
Select Data  Connect to
Data to connect to at least
two data sources. The data
sources are shown in a
drop-down list at the of
the Data window.
The Data window color
codes the primary and
secondary data sources
with a colored bar down
the left side.
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Data Source Relationships
Relationships are automatically created based on field names, however, you can
define custom relationships by selecting Data > Relationships. In the
Relationships dialog box, select the primary data source in the drop-down at the
top of the dialog box. Then select the secondary data source. Any automatic
relationships are shown or you can select Custom and then click Add to relate
fields from each data source.
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Dimensions
Tableau treats any field
containing qualitative,
categorical information as a
dimension.
For example, text / date
fields would classify as
dimensions.
In simplest terms, a
dimension can be thought
of as a column header in a
relational table. A context
provider for data.
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Measures
Tableau treats any field
containing quantitative,
countable values as
measures
For example, revenue or
number of units sold.
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Calculated Fields
Calculated fields are custom dimensions or measures created
by the user. These fields are typically derived from existing
fields imported from the source data.
For example, tableau imports two dimensions named City and
Country. A user can create a dimension that displays both in a
single column by creating a calculated field to concatenate the
two dimensions.
It is also possible to create compound measures using
calculated fields.
Total revenue = no. of units sold x price per unit
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Calculated Fields (contd.)
Right click on the dimension / measure pane and select
calculated field. Tableau validates expressions automatically.
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Report Area
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Report Area (contd.)
 The Tableau report area consists of several “shelves” where the
data elements (dimensions, measures, sets, etc) can be dragged
and dropped.
 Dragging and dropping dimensions into the column or row shelf will
create a basic table.
 Dropping a measure into the text shelf will display the fact data
grouped by the context of the dimension in the row or column
shelf.
 Dropping dimensions in both row and column shelves will generate
a crosstab.
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Report Area (contd.)
Basic Crosstab layout
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Sets
Tableau sets are used to work with specific elements of data
sets.
The three main uses of a set are:
Create a subset of the data – Select one or more dimension members that are of interest to you. For
example, sort a field and select only cities on the west coast with populations greater than 500,000, or
manually select outliers that appear in a scatter plot. Refer to Example – A Set Containing a Subset for
more information.
Create unique encodings – Combine dimension members to create unique encodings. For example,
create a set that combines market and product, and then color-encode a data view using the combined
members. Refer to Example – A Set Containing Unique Encodings for more information.
Save filters for later use – once you have created a filter, you can save the filter as a set and use it in
all of the worksheets in a workbook. This saves you from having to recreate the filter every time you
want to use it.
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Filters
Filters are used to restrict datasets at the query level.
They affect the elements of the “where” predicate clause in an
SQL query against the data source.
Filters in Tableau are of three types:- Static filters on a report
- Dynamic / View filters or prompts
- Relative filters
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Filters
Static filters affect the where
clause of the query
They are used to restrict the
elements retrieved in the report.
Filters can be made global, that
is affect the entire report instead
of a single worksheet.
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Hierarchies
Tableau supports hierarchies for drilling analysis.
To create a hierarchy, simply drag a dimension over another
dimension, and a popup to create a hierarchy will appear.
While this can be achieved with any two or more arbitrary
dimensions, it is generally good practice to restrict hierarchies to
elements that will allow simplification and clarity in report
presentation.
For example, date / time dimensions form natural hierarchies with
Year / Quarter / Month / Day / Time
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Hierarchies
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Groups
Tableau allows the creation of groups of consolidations of elements
of a dimension.
For example, Jan – Mar can be grouped as “Winter” seasons.
Measures and calculations will rollup according to the consolidated
group rather than the individual dimensional elements.
Groups are often used to create parents for hierarchical relationships
within the same dimension.
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Groups
Right click a dimension and select “Create Group”.
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Aggregations
The “Customize” option opens the formula window for the user to
enter a custom calculation.
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