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Tableau file types- purpose, features and limitations


TWB - Tableau WorkBook file

1) A text file, to be more specific, an XML file, which is a highly structured text file that contains

a) Data connection information

b) View layout definitions

c) And thumbnails or snapshots of each view

 

TWBX Tableau packaged WorkBook file

1) Everything contained in a Tableau WorkBook file

+PLUS+

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MIT Sloan Review, don’t allow pies to obscure the “New Intelligence” you hope to share

MIT Sloan Review, don't allow pies to obscure the New Intelligence you hope to share

I was very interested to read the survey results from MIT about data access challenges facing business analysts. The article states that "The New Intelligent Enterprise... will allow you to do some immediate benchmarking — and see how your organization is doing in relation to your peers." While I am certain the data from this survey can indeed be useful in meeting their objective, I am also certain that their initial chart selection makes this difficult to easily see and understand.

 

In an effort to demonstrate how they can make their upcoming report much more informative

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TCC EU 2011- Premier of Tableau 6.1- Developers on Stage

Chris Stolte, Chief Development Officer, Tableau (co-founder, Tableau Software)- on-stage
Dan Jewett, VP of Product Management
Francoise Ajenstat, Director of Product Management

Some comments are the opinion of Freakalytics and not necessarily those of Tableau

This content is live blogged; there may be occasional errors or omissions.
 
 
Overview

Mission of dev team- “Help people see and understand their data.”
Make data fun
, anathema too many, but key to using data throughout the organization and entire decision-making process
 
 
Four key areas of investment for 6.1

Data performance
Sharing via mobile optimization with iPad
Localizing and globalizing the products- French and German
User experience- make every step easy, fast and fun!

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A response to the TDWI article, “An Imperative to Build, Not Buy, Agile BI”

As TDWI and vendors catch on to the success of “Agile BI” being created with products like Tableau, I find the need to reply to the idea that the same old technology will work in this new world.  This article from TDWI energized me to write a response to this frequently cited idea.  In case you aren’t familiar with the acronmym “BI”, it simply means business intelligence, typically referring to traditional tools like Cognos, Business Objects, Excel, Microstrategy, SAS and many other products. 

What is Agile BI? 
“Agile BI” is new-found jargon that describes what

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Tableau Tips: Synchronizing Multiple Data Sources in a Tableau Dashboard

The setup
You have connected to more than one data source in your Tableau workbook, for example, your sales database in Oracle and a customer call database in SQL Server.  Tableau seamlessly allows you to connect to multiple data sources in one workbook.  Views developed from both data sources can be placed in a single dashboard.

However, if you try to use global filters or quick filters to synchronize the two data sources, you will find that it isn’t possible; only one data source can be linked to either.  In fact, the term “Global” filter in Tableau can be confounding, since it is only global to views using the current data source.  Global filters will not work with other data sources even if the data items have the same name!

The solution
As of Tableau 5.0 (released in 2009), a new feature

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Rapid Graphs- Tableau for Customer Segmentation and Lifetime Value Analysis

This was presented at the Tableau Conference 2009. It is about the tremendous opportunities to leverage customer segmentation and lifetime value data at the individual customer level. Click here for the presentation.

Identifying segments for every customer can unlock long-hidden value for your marketing team. Combining this information with Tableau creates a simple means for marketing owners to evaluate and improve their decisions.

A second opportunity is adding lifetime value estimates to each customer as you acquire them and as their behavior adds additional information to inform their value. With lifetime value estimates, you will gain a huge competitive advantage in evaluating your the long-term value of your marketing investments and product decisions. Are your most expensive programs just impacting short-term outcomes and only reaching lower value customers? How are your customers being affected by a blend of marketing programs over time?

Click here to see a summary view on Tableau Public which was constructed from part of the Tableau workbook used in this presentation. Many thanks to Ellie Fields at Tableau for selecting the views and publishing this summary!

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Data warehousing success- 100% Vision / 80% Tactical / 20% of the Work

My Background in Data Warehousing

I have been involved in the creation, development, and maintenance of seven data warehouses through the years- one of them before I even knew about the term “data warehousing”!  I have built them with SAS and Oracle, SAS alone, Informatica and Oracle, Oracle alone, and SQL Server.

I have also visited many companies as an adviser, consultant and user of their data warehouse. In these many visits, I have seen some successes and many failures. Often, the failures could have been prevented with some key guiding principles.

Data Warehousing or Enterprise Data Integration?

Data warehousing is now known by a new buzz word, Enterprise Data Integration. In fact, SAS recently renamed SAS ETL Studio as SAS Data Integration Studio (they also added some new features around the EDI area, one new feature was around continual data acquisition so that near real time data feeds are available in the data warehouse.) Another great part of SAS EDI is SAS Data Quality, this should be a consideration throughout the entire process, but I won’t directly comment about data quality in this post. Since most people still use the term data warehousing, so I will keep the popular terminology over the analysts and even SAS.

What Does it Take to Build a Successful Data Warehouse?

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