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Self-Service BI

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on 4 July 2013

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Transcript of Self-Service BI

So far, business intelligence vendors have focused too much on putting spreadsheets on steroids and not enough on closing the loop between visual displays and analysis.

The point is that if you are still running your business on questions you planned on answering last year or last month, you are probably going to quickly fall behind companies that are able to poke, probe and explore their options based on more visual and interactive forms of analysis.
~~ Dan Woods
Self Service BI
... When Thornton May was interviewing people for his book “The New Know”, he asked a prominent venture capitalist known for his 360-degree view of the technology industry what he thought of when he heard the phrase business intelligence. His response was
“big software, little analysis.”
Sadly, his response rings true.

In the 1990s, the data warehousing industry, which had become lackluster due to its many failures and the inability of thought leaders and vendors to tell us anything new and worthwhile, promoted the term business intelligence (BI) as its new rallying cry. It was used as a marketing campaign to rekindle interest in old technologies, but did little to change the course of events. The industry continued to focus on building the infrastructure of data rather than the tools and methods that are needed to actually use data.
Self-service BI is defined as the facilities within the BI environment that enable BI users to become more self-reliant and less dependent on the IT organization. These facilities focus on four main objectives:

easy access to source data for reporting and analysis;
easy-to-use BI tools and improved support for data analysis;
fast-to-deploy and easy-to-manage data warehouse options such as appliances and cloud computing;
and simpler and customizable end-user interfaces.
Claudia Imhoff & Colin White. 2011.
Self-Service Business Intelligence: Empowering Users to Generate Insights. TDWI Best Practices Report, Third Quarter.
why self service bi?
BI Has Hit the Wall
Stephen Few.
2011. BI Has Hit the Wall. Perceptual Edge. http://www.perceptualedge.com/blog/?p=820
~~ Stephen Few
New Analytics
Technical people are also responsible for maintenance and change. Lots of change. Change that they are not able to respond to in a timely manner. Nor are they able to anticipate all of the potential needs of the Business.

As a result, they have little time for documentation and are not available to support analysts in a DBA capacity:
complex queries
data quality
investigating new connections/source systems
BIG STACK solution
Traditional Tech-Centric BI
Data preparation and Governance
Build BI Stack
Build all Analysis
Managed Reporting
While Tech is doing this...
Even with access to Data Warehouses, Data Marts and Data Sources, analysts are spending approximately
75% of their time wrangling the data into an analysis ready state.
Analysts are being asked to RAPIDLY provide insight into ever changing Business challenges
all this
to get this
Enable Analysts to conduct analysis
Data preparation and governance
Respond to business
Explore, analyze
Report, monitor
Predict, investigate
Instead, Self-Service BI could look like this
Data Warehouse solutions need to be fast to deploy, flexible, and easy to use. In many organizations new data source systems are being added faster than legacy systems are retired and IT has struggled to keep the pace. Data warehouses can also become too complex or the information may become out of date. This leads to lowered use by analysts who will always find a way to get the data they need.

E-Bay has been dealing with this challenge on a large scale since 2001. In 2010, they adopted a Self-Service BI model by creating a Data Hub, using HADOOP to query their big data and Tableau to analyze it.
General Motors recently announced their plans to in-source 10,000 IT jobs, to build world class data centers utilizing Tableau as their self-service bi analytics tool
Why Tableau Server for Self-Serve BI?
columns, rows and filters - similar to Excel pivot tables
drag and drop easy user interface
switches between chart types instantly
letting the data tell us the story
drag and drop dashboarding
Based on principles of perception, Tableau keeps it clean and simple using best practices. Interactivity helps tell the story.
Tableau Desktop is a tool for all analyst skill levels. Connecting to data, analyzing data and building interactive dashboard reports does not require an IT analyst or developer.
Tableau is one of the new In-Memory tools that enable self-service BI. And it's catching on.
Tableau Desktop is used to connect to data, conduct analysis and build interactive dashboards.

Tableau Reader is like Adobe Reader - it's free and let's users filter and interact with reports if you don't have Server.

Tableau Server manages user access, data sources and connections, and serves up the reports.
In-Memory visual analytic tools crunch the data right on your computer - using your RAM rather than on the disk where the data resides. This means SPEED. Instant Insight.

Data is imported into the workbook and compressed by Tableau's Data Engine at a ratio of 10 to 1. Tableau can handle BIG DATA.
Proxy Data Connections
analyst connects to data source(s) through server
creates extract
conducts analysis
builds report workbook
another analyst uses that data extract
conducts analysis
builds report workbook
and so on and so on....
Rapid Insight
Rapid insight is not only achieved through Tableau's speed of analysis and visual display. With Server, rapid insight is achieved through the sharing of data sources.
Tableau Server enables the creation of a data center or hub where analyst can access multitudes of data sources and each others reports. This transparency puts an end to data and reporting silo's that cause much confusion and wasted time.
think of all the data sources that analysts of different departments connect to
with server those connections are only set up once and available to any or all analysts
That means an exponential reduction in
Time To Insight!
it gets considerably cheaper with more users
at least 50% of analysts time spent getting data ready to analyze would not be replicated by another analyst
Instead of 75 power point slides, management can interact with reports during meetings
You can save a view of the interactive report and send the link to team members advising them of meeting decisions
You can add comments to reports that others will see - like Facebook
... AND this is a no brainer for IT
Server can be implemented in 1/2 a day
that would be installing, set-up, creating user groups, assigning user access and adding some data connections
IT claims Server requires about 1 hour per month for maintenance
By the time the information gets to management they already have dozens of new questions.
Recommendations for Self-Service BI
to Tableau or not to Tableau?
Claudia Imhoff & Colin White.
2011. Self-Service Business Intelligence: Empowering Users to Generate Insights. TDWI Best Practices Report, Third Quarter.
for the report users...
but we need the right tools to do the job right
Considerations in Selecting a Self-Service BI Tool
(or DIY - do it yourself BI)
Claudia Imhoff & Colin White. 2011.
Self-Service Business Intelligence: Empowering Users to Generate Insights. TDWI Best Practices Report, Third Quarter.
Show Me
wrangle the data
tell the story
change with business on the fly
In-Memory means you don't need to build the whole STACK
That means more time spent investigating and getting to the story
or being able to respond to more requests
or connecting to data they could never get before
and they wouldn't be spending all that time reconciling results with other departments - that's almost a 'single version of the truth'
share your insight!
127 % ROI
These are Implementation Costs - annual fees are approximately 20%.
Cheap - on average under $200 per user
Easy to migrate current data - just connect to it
The easiest program for developing reports
High Quality
EDW Tableau Platform Engineer Job
Date: Sep 21, 2012
Location: Austin, TX, US

EDW Tableau Platform Engineer-INF0002525

About the General Motors Enterprise Data Warehouse (EDW) team:

GM has recently announced numerous steps to strengthen its position as a global automotive leader. GM is constructing an Enterprise Data Warehouse (EDW) as one of the cornerstones to achieve this objective. As a member of the EDW team you will play a significant role in helping GM implement one of the largest data warehouses in the world. GM is seeking dynamic individuals who will leverage their industry knowledge and experiences to design, architect, deploy, and manage this data warehouse.

About the role:

The Tableau Platform Engineer is responsible and accountable for defining, configuring, maintaining, monitoring and troubleshooting GM’s next generation, cross company Tableau business intelligence platform, including server and desktop products.
SEE your data
let the data tell the story
rapid insight
1 million records in 6 seconds
save time = save $$$
interactivity = real time story
sharing = transparency
industry leading
127% ROI
respond to business now = respond to customers sooner
no more big builds = $$$
Its a revolution
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