This document provides an overview of data visualization and Tableau features. It discusses the shortcomings of traditional business intelligence tools, the business case for visual analytics, and Tableau's software ecosystem. The document also describes Tableau's desktop workspace, including the start page, data connections, worksheets, and features like dashboards, collaboration, data sources, visualizations, and security options. Tableau is presented as a tool that improves decision-making by enabling interactive data exploration and visualization.

1. DATA VISUALIZATION FOR MANAGERES
MBA III SEM
SPECIALIZATION
BUSINESS ANALYTICS
As per RTMNU,Nagpur

2. MODULE -1
 Creating Visual Analytics with Interactive data visualization
software Desktop –Shortcomings of Traditional Information
Analysis, Business Case for visual analysis, The Interactive data
visualization software Software Ecosystem, Introducing Interactive
data visualization software Desktop Workspace

3. DATA VISUALIZATION

 Decision Making
 Finding solution to problems
 For understanding the data clearly
 To find Relationship among the data
 Comparative Analysis
Data Visualization
Data Visualization

4. PROCESS OF DATA VISUALIZATION
Integrate
Different Data
Set
Analyze Visualize

5. TABLEAU FEATURE
 Tableau Dashboard
 Tableau Dashboards provide a wholesome view of
your data by the means of visualizations, visual
objects, text, etc.
 Dashboards are very informative as they can
present data in the form of stories, enable the
addition of multiple views and objects, provide a
variety of layouts and formats, enable the users to
deploy suitable filters.
 You even have the option to copy a dashboard or
its specific elements from one workbook to another
easily.

6.  Collaboration and Sharing
 Tableau provides convenient options to collaborate with
other users and instantly share data in the form of
visualizations, sheets, dashboards, etc. in real-time.
 It allows you to securely share data from various data
sources such as on-premise, on-cloud, hybrid, etc.
 Instant and easy collaboration and data sharing help in
getting quick reviews or feedback on the data leading to
a better overall analysis of it.

7.  Live and In-memory Data
 Tableau ensures connectivity to both live data
sources or data extraction from external data sources
as in-memory data.
 This gives the user the flexibility to use data from more
than one type of data source without any restrictions.
 You can use data directly from the data source by
establishing live data connections or keep that data in-
memory by extracting data from a data source as per
their requirement.
 Tableau provides additional features to support data
connectivity such as automatic extract refreshes,
notifying the user upon a live connection fail, etc.

8.  Data Sources in Tableau
 Tableau offers a myriad of data source options you can
connect to and fetch data from.
 Data sources ranging from on-premise files, spreadsheets,
relational databases, non-relational databases, data
warehouses, big data, to on-cloud data are all available on
Tableau.
 One can easily establish a secure connection to any of
the data sources.
 Data connectors such as Presto, MemSQL, Google
Analytics, Google Sheets, Cloudera, Hadoop, Amazon
Athena, Salesforce, SQL Server, Dropbox and many more.

9.  Advanced Visualizations (Chart Types)
 One of the key features of Tableau and the one that got
its popularity is its wide range of visualizations.
 Bar chart
 Pie chart
 and as advanced as a:
 Histogram
 Gantt chart
 Bullet chart
 Motion chart
 Treemap
 Boxplot

10.  Maps
 Tableau has a lot of pre-installed information on maps
such as cities, postal codes, administrative boundaries,
etc. This makes the maps created on Tableau very
detailed and informative.
 You can add different layers of geology on the map as
per your requirements and create informative maps in
Tableau with your data.
 The different kinds of maps available in Tableau
are Heat map, Flow map, Choropleth maps, Point
distribution map, etc.

11.  Robust Security
 Tableau takes special care of data and user security.
 It has a fool-proof security system based on authentication
and permission systems for data connections and user
access.
 Tableau also gives you the freedom to integrate with other
security protocols such as Active Directory, Kerberos, etc.
 Mobile View
 Tableau acknowledges the importance of mobile phones in
today’s world and provides a mobile version of the Tableau
app.
 One can create their dashboards and reports in such a
manner that it is also compatible with mobile.
 Tableau has the option of creating customized mobile
layouts for your dashboard specific to your mobile device.
The customization option gives the option for adding new
phone layouts, interactive offline previews, etc.

12.  Ask Data
 The Ask data feature of Tableau makes it even more favored
by the users globally.
 This feature makes playing with data just a matter of simple
searches as we do on Google.
 You just need to type a query about your data in natural
language and Tableau will present you with the most relevant
answers. The answers are not only in the form of text but also
as visuals.
 Trend Lines and Predictive Analysis
 Another extremely useful feature of Tableau is the use of time
series and forecasting.
 Easy creation of trend lines and forecasting is possible due to
Tableau’s powerful backend and dynamic front end.
 You can easily get data predictions such as a forecast or a
trend line by simply selecting some options and drag-and-
drop operations using your concerned fields.

13.  Data graphics should draw the viewer’s attention to the
sense and substance of the data, not to something else.
Edward R. Tufte
 The seeds for Tableau were planted in the early 1970s
when IBM invented Structured Query Language (SQL)
and later in 1981 when the spreadsheet became the killer
application of the personal computer.
 The business information (BI) industry was created with
this wave; each vendor providing a product “stack” based
on some variant of SQL

14.  The pioneering companies invented foundational
technologies and developed sound methods for collecting
and storing data
 A new generation of NOSQL2 (Not Only SQL) databases
are enabling web properties like Facebook to mine
massive, multi-petabyte3 data streams.
 Data today resides in many different proprietary
databases and may also need to be collected from
external sources.
 The traditional leaders in the BI industry have created
reporting tools that focus on rendering data from their
proprietary products.
 Performing analysis and building reports with these tools
requires technical expertise and time
 The people with the technical chops to master them are
product specialists that don’t always know the best way
to present the information.

15.  The scale, velocity, and scope of data today demands
reporting tools that deploy quickly.
 The tools need to guide us to use the best techniques
known for rendering the data into information.

16. SHORTCOMINGS OF TRADITIONAL INFORMATION
ANALYSIS
 In any given BI using organization just over 8 percent of employees
are actually using BI tools. Even in industries that have aggressively
adopted BI tools (e.g., wholesales,banking, and retail), usage barely
exceeds 11 percent. Nigel Pendse, BARC(Business Application
Research Center).
 The BARC Survey noted these causes
1.The tools are too difficult to learn and use.
2.Technical experts were needed to create reports.
3.The turnaround time for reports is too long.
 When BI system reports are received,traditional tools often employ
inappropriate visualization methods.
 People want to make informed decisions with reliable information.
 They need timely reports that present the evidence to support their
decisions. They want to connect with a variety of datasources, and
they don’t know the best ways to visualize data

17. BUSINESS CASE FOR VISUAL ANALYSIS
 The entity seeks profits or engages in non-profit
activities, all enterprises use data to monitor
operations and perform analysis.
 Three Kinds of Data that Exist in Every Entity
 Reports, analysis, and ad hoc discovery are used to
express three basics kinds of data.
 Known Data (type 1)
 Data You Know You Need to Know (type 2)
 Data You Don’t Know You Need to Know (type 3)

18.  Known Data :-Encompassed in daily, weekly, and
monthly reports that are used for monitoring activity,
these reports provide the basic context used to inform
discussion and frame questions.
 Type 1 reports aren’t intended to answer questions.
 Their purpose is to provide visibility of operations.

19.  Data You Know You Need to Know (type 2)
 Once patterns and outliers emerge in type 1 data the
question that naturally follows is: why is this happening?
 People need to understand the cause of the
 outliers so that action can be taken.
 Traditional reporting tools provide a good framework to
answer this type of query as long as the question is
anticipated in the design of the report.

20.  Data You Don’t Know You Need to Know (type 3)- By
interacting with data in real-time while using appropriate
visual analytics, Tableau provides the possibility of seeing
patterns and outliers that are not visible in type 1 and
type 2 reports.
 The process of interacting with granular data yields
different questions that can lead to new actionable
insights.
 Software that enables quick-iterative analysis and
reporting is becoming a necessary element of effective
business information systems.

21. HOW VISUAL ANALYTICS IMPROVED DECISION
MAKING

24. TURNING DATA INTO INFORMATION WITH VISUAL
ANALYTICS
 Data that is overly summarized loses its ability to inform.
When it’s too detailed, rapid interpretation of the data is
compromised.
 Visual analytics bridges this gap by providing the right style of
data visualization and detail for the situational need.
 Simplicity—Be easy for non-technical users to master.
 Connectivity—Seamlessly connect to a large variety of
datasources.
 Visual Competence—Provide appropriate graphics by
default.
 Sharing—Facilitate sharing of insight.
 Scale—Handle large data sets.

25. SOFTWARE ECOSYSTEM
 Tableau’s product line includes desktop design and
analysis tools for creating and consuming data.
 For larger deployments, Tableau Server permits
information consumers to access reports in a secure
environment without the need to load software.
 Reports are consumed in Tableau Server via a web-
browser.
 Tableau Server also enables reports to be consumed on
iOS or Android tablet computers.

26.  Tableau Public is a free tool that facilitates sharing public
data on the web via blogs or webpages.
 For those that want a hosted solution, Tableau
Public Premium is a fee-based service that
uses the same technology as Tableau Public in
private consumption environment.

27. TABLEAU DESKTOP

28. TABLEAU READER

29. INTRODUCING THE TABLEAU DESKTOP
WORKSPACE
 Start page and Data Connection

31.  Mutliple Worksheet Page

32.  Tableau Workspace

33. REFERENCE
 Tableau your Data, Daniel G Murray, 2nd Edition,
Wiley Publishing, ISBN-13: 978- 8126573448.
 www.wikipedia.com
 www.google.com
 https://data-flair.training/blogs/tableau-data-
sources/