Intellectual Property - DAMA New York
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Transcript Intellectual Property - DAMA New York
Putting It All Together:
Trends in Business Intelligence
Claudia Imhoff, PhD
Intelligent Solutions, Inc.
[email protected]
www.intelsols.com
Blog: http://www.b-eye-network.com/blogs/imhoff/
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
Claudia Imhoff
President and Founder
Intelligent Solutions, Inc.
A thought leader, visionary, and practitioner in the
rapidly growing fields of business intelligence and
customer focused-strategy – Claudia Imhoff, Ph.D., is
an internationally recognized expert on analytical CRM,
business intelligence, and the infrastructure to support
these initiatives – the Corporate Information Factory
(CIF). Dr. Imhoff has co-authored five highly-regarded
and popular books on these subjects and writes
monthly columns (totaling more than 100) for technical
and business magazines.
Email: [email protected]
Phone: 303-444-6650
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
2
Putting It All Together
Going Beyond Traditional BI – Operational BI Takes
the Stage
Data Warehouse Appliances and Analytic
Databases – Making Life Simpler
BI Software as a Service – Feeling SaaS-y?
Open Source BI – Free Software Anyone?
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
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The Three Levels of Business
Intelligence
Strategic BI
timeframe ~ months
Tactical BI
timeframe ~ days or weeks
Operational BI
timeframe is intra-day
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The Three Levels of Business
Intelligence
Strategic BI
Tactical BI
Operational BI
Business
focus
Achieve long-term
business goals
Manage tactical initiatives
to
achieve strategic goals
Monitor & optimize
operational business
processes
Primary
users
Executives &
business analysts
Business analysts,
& LOB managers
LOB managers, operational
users &
operational processes
Timeframe
Months
to years
Days to weeks
to months
Intra-day
to daily
Data
Historical
data
Historical
data
Real-time, low-latency,
& historical data
Paradigm Shift
Mode of
operation
User driven
Data centric
User driven
Data centric
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Event driven
Process centric
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What is Operational BI*
A set of services, applications and technologies
for monitoring, reporting on, analyzing and
managing the business performance of an
organization’s daily business operations
*From research study. “Embedded BI”, written by Colin White and Judy Davis, www.B-EYE-Research.com
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
6
Operational BI – Answers to Day-toDay Business Questions
picked
packed
What is my customer’s order status? What can
I offer based on customer’s life-time value?
shipped
invoiced
What is my current inventory level world wide?
Is it sufficient to meet demands?
Yield
What is my production yield right now?
Am I at par with acceptable standards?
Can I afford to make this move
at current margin rates?
Operational BI
Helps front-line workers
make immediate business decisions
to squeeze out inefficiencies.
New Data Needs
Information on demand
Real-time + historical data
Access to SAP, Siebel, Oracle and
BI results
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Real Time Decision-Making*
Operational BI optimizes time latency between
when a business event occurs and when an
appropriate action is taken
The goal – to “right-size” the decision-making cycle
Compressing time lag between knowing what is
happening and taking action based on that knowledge
Real-time must consider potential trade-off between timeto-action and business value of actions
* From “Right-Time Business Intelligence: Optimizing the Business Decision Cycle” By Judy Davis, www. BEYE-Network.com Research paper
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
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Impact on BI Environment
History of BI
Extract usable information from operational systems
Users, technologies, processes, procedures – all
independent of operations
Now what?
Impact on BI environment is significant
Increase in number of users, volume of data, and faster
performance
Operational BI – MUST be integrated into the operational
environment
Requires understanding of operational systems, processes,
procedures, workflows, personnel
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Impact on BI Environment
Numbers of users increase significantly
Traditional BI rarely supported a few hundred, maybe a
thousand or so users
Opening BI up to operational personnel means ramping
up into tens of thousands of users
These users have very different interface requirements
Means BI implementers must rethink how BI is delivered to
business users
Means tighter and faster connectivity of enterprise
decision support environment to rest of the company.
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Impact on BI Environment
Volumes of data increase substantially
Detailed intraday snapshots of data are loaded or tricklefed into data warehouses
Tens of terabytes to hundreds of terabytes are not
unusual storage requirements for operational BI
Scalability now a mandatory requirement in any BI
technology
Whether in processing and integration of data, storage of massive
volumes, or retrieval of query responses
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Impact on BI Environment
Faster performance
Query performance must mimic or emulate response
times in operational systems
Sub-second to just a few seconds to return data from a query.
Ability to prioritize queries not only according to their
importance but also their response requirements is
mandatory success criterion
This last feature has stumped many BI implementers and BI
vendors
Must have ability to handle mixed work load gracefully
and simultaneously
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Getting Started – Assess
Reality
First step – perform honest assessment of existing
data delivery capabilities – available technologies,
maturity of the BI architecture, existing personnel,
etc.
Combine these with solid understanding of business
requirements for operational BI data
Important to understand which weaknesses
discovered in assessment will be exaggerated as
you speed up the enterprise
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Operational BI Requirements
Continuous availability of operational data and BI
results
Current information from operational systems
Integrated with BI data on demand
Minimal impact on operational systems performance
Presented in a proactive manner
Make decisions – act on information presented
Easy to understand and use
Dynamic modeling
Ability to change business rules on the fly
Show different set of metrics depending on situation
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Picking a Project
Look for workflow activities that have significant
impact on costs or revenues
Bottlenecks today that can be made more efficient
through use of operational BI
Don’t make big changes to operational processes
Just speed up or make more efficient processes you
already have in place
You will have to retrain personnel and retool SOPs
Project managers may not realize operational BI
application has ramifications beyond project’s
immediate boundaries
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
15
Putting It All Together
Going Beyond Traditional BI – Operational BI Takes
the Stage
Data Warehouse Appliances and Analytic
Databases – Making Life Simpler
BI Software as a Service – Feeling SaaS-y?
Open Source BI – Free Software Anyone?
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
16
Data Warehouse Appliances
BI and data warehousing technologies continue to
evolve and innovate
Produce more efficient & cost effective ways to deliver BI
Latest innovations are DW and BI appliances
Definition of an appliance*
One purpose
One package
One installation
One vendor
* From the B–EYE-Research.com paper titled “Data Warehouse Appliances: Evolution or Revolution?”
by Colin White, and Richard Hackathorn
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Data Warehouse Appliances
All-in-one box that provides a hardware server
preconfigured with all software components
Designed for a specific purpose – supporting data
warehouse processing
Offers ease of use, simplicity, and compatibility – tested,
ordered and delivered as a single system
Simple to understand even though mechanism may be
complex
Low cost in terms of TCO
High performance in achieving its purpose
Single point of service provided by single vendor
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Data Warehouse Appliances
Cost effective solution
TCO of a data warehouse appliance is lower because
cost of hardware and software is cheaper
Also because simplicity and ease of reduces installation,
administration and support cots
Improved usability of a data warehouse appliance means
projects can be developed and deployed faster
Includes popular BI capabilities
Interactive dashboards, analysis, reports, alerting, and
data integration
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Sweet Spot for Data Warehouse
Appliances
Size of Data
Multiple
Terabytes
Data Warehouse
Appliances
Mega- to
Gigabytes
Focused Purpose
Specialized
Databases
(e.g., Teradata,
IBM)
Any database
vendor
Complexity of Workload
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Mixed Purpose
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Data Warehouse Appliances
Pros
Cons
Immediate visibility &
interaction into
business performance
Non-disruptive to
existing infrastructure
Faster deployment
Low maintenance –
black box
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
Still some opposition to
use of appliances by IT
departments
Loss of “control” over
moving parts
DW and BI appliance
scalability
Customization to fit
each company’s needs
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Sample Data Warehouse
Appliance Vendors
Netezza
Teradata
DATAllegro (now Microsoft)
Sun + Green Plum
Sun + Vertica
Sun + ParAccel
Sun + Kognitio
IBM InfoSphere Warehouse
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
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Role of Appliances in BI SaaS
Many data warehouse appliance and BI SaaS
vendors are forming partnerships
Gives SaaS vendors scalability, reliability, performance
Gives appliance vendors applications, new markets,
greater exposure
Gives customers more confidence that solution is on solid
technological footing
Performance
Support for multi-tenancy
Scalability
Applications
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Analytic Databases
Many are Massive Parallel Processing (MPP)
Can use commodity hardware
Many have column-based data organization
Limit I/O by putting similar data together – reduces reads
to only columns needed for query
Single data type per column allows for significant
compression
Data compression
Compression can be optimized for particular data types
CPU is not the bottleneck, only I/O is
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Analytic Databases
Built-in intelligence
Allows decompression of only data that must be for query
resolution and ignore all others
Is major factor in overall improved performance
Load times remain constant regardless of table size
Should also have query times that remain constant
regardless of table size
Bottom line – technology must be seamlessly scalable
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Analytic Databases
Many new vendors on the market (sample):
Green Plum
Vertica (Michael Stonebraker*)
ParAccel (Barry Zane**)
Dataupia (Foster Hinshaw**)
InfoBright (Warsaw University)
Aster Data (Stanford University)
illuminate (Former Synerra Systems founders)
One well-established vendor: Sybase IQ since 1993
Most are column based, MPP, shared nothing
architectures (not all though) * Ingres and Illustra founder
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
** Netezza founders
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Analytic Databases – Really
Fast: TPC-H 1 TB
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Analytic Databases – Really
Fast and Really Inexpensive
Solution
Pricing model
Price/unit
1 TB solution
Remarks
Vertica
Data Volume
(raw)
$ 100,000/TB
$ 200,000,-
Based on 5 nodes,
$ 20,000,- each
ParAccel
Node
$ 40,000,(+$10,000/TB)
$ 310,000,-
Based on 5 nodes,
$ 20,000,- each
ParAccel
Data Volume
(raw)
$ 1,000,-/GB
$ 1,250,000,-
From TPC-H
publication
InfoBright
Data Volume
(raw)
$ 40,000,-/TB
$ 140,000,-
Based on 5 nodes,
$ 20,000,- each
Dataupia
Node
$ 19,500/2TB
$ 19,500,-
You can not buy a
1 TB Satori server
ExaSol
Data Volume
(active)
$ 675 - $1,750
per GB
$ 940,000,-
From TPC-H
publication
Graph compliments of Jos van Dongen, Tholis Consulting, NL. Numbers are estimated.
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
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Analytic Databases
Pros
Excellent performance
Very cost-effective
Low maintenance
Partnering with
hardware vendors (DW
appliance)
Cons
Many are small
companies
May not handle mixed
work load well
New (unknown)
technology for IT
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
29
Putting It All Together
Going Beyond Traditional BI – Operational BI Takes
the Stage
Data Warehouse Appliances and Analytic
Databases – Making Life Simpler
BI Software as a Service – Feeling SaaS-y?
Open Source BI – Free Software Anyone?
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
30
BI Delivery Models
There are two BI delivery models today
On-premises – traditional model
Software as a Service (SaaS)
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On-premises – Traditional
Model
Internal IT is responsible for entire environment
from first project
Find excess capacity on machines
Upgrade memory on existing machine for usage
Leverage installed end user access tools
Buy smaller platforms that can scale
Migrate to bigger box when necessary
Use smaller box for data mart(s)
Look into data warehouse appliances for very large,
focused BI analytics
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
32
Software as a Service (SaaS)
Characteristics*
Secure, flexible, and efficient business processes &
workflows
Service level agreements
Value-added business services such as analytics & best
practices
Extensive use of service-oriented architecture (SOA) to
enable scaling, configurability, and integration
Subscription monitoring & usage-based billing
* From www.sandhill.com, “Get Ready for SaaS 2.0” by Bill McNee, Saugatuck Technology, May 8. 2006
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Advantages for SaaS Vendors
Vendors support only one platform and one version
of the application
No need to support multiple operating systems, platforms,
and older versions of the software
Decreases development costs significantly
SaaS gives vendor great visibility into how their
customers are actually using their software
See every move, every feature, every function used by
customers
Gives vendor great intelligence on how to build a better
product based on actual usage
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
34
Advantages for SaaS Vendors
SaaS model gives vendor a predictable cash flow
Subscription model is reliable for cash flow estimation
Improves start-up estimations and growth track
Vendors don’t get trapped in “feature bloat”
No need to keep adding feature after feature to get
customers to buy new versions
Create only features that are needed based on actual
customer usage
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
35
Disadvantages for SaaS
Vendors
SaaS produces lower revenues at first than
traditional vendor models
Must attain critical mass of subscribing customers
Vendor must have enough funding to tide them over
More time is needed to ramp up to mature status
Higher customer set up costs
Traditional vendor model – send customer a CD
SaaS vendors must allocate space, set up customer
support, etc.
SaaS vendor becomes IT support for their customers
(higher costs for customer service?)
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Disadvantages to SaaS
Vendors
Customers still need ability to integrate SaaS
application data with other enterprise data
Need mechanism to export data out of SaaS environment
Who supplies integration of SaaS data with customer’s
other data?
If customer is not SOA-compliant yet, what does this
mean to SaaS model?
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
37
Reasons for Adoption: Ease of
Deployment
This is the SaaS model’s greatest advantage
No installation of hardware
No installation of software
No administration of new versions of either
No need for IT expertise in the tool or application
Set up consists of getting a login and password set
up for the business users
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Reasons for Adoption: More
Flexibility for Evolving Needs
Perhaps…
You can certainly change SaaS vendors quite easily
If you are unhappy with one vendor, changing to another one is
about as easy as getting a new login and password
You can influence the direction and R & D of the current
SaaS vendor
You can easily add or subtract users
You can easily add or subtract functionality
It may not be as easy to customize the SaaS offering to
your specific needs
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
39
Reasons for Adoption: Not
Locked into Long Licenses
True
Great advantage in BI world where technology is moving
very fast
Can switch from one SaaS vendor to another
But watch for cancellation fees
And make sure you know what the subscription fee
is based on
Reduction or addition of users may be cross price break
threshold
Salesforce.com model is typical
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
40
Considerations for BI SaaS
SaaS – good at supporting particular types of users
Highly mobile work force
Field sales personnel
Product support specialists at customer sites
Telecommuters
Highly geographically disbursed workforce
International enterprises
Non-office workers (virtual offices)
Customer or partners worldwide
Must include support for various mobile devices
Phones, mobile PCs, handheld devices, PDAs, etc.
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41
Considerations for BI SaaS
Ensuring quality of delivered environment
Correct mappings, verified data lineage, transformations
Sufficient data quality processing
Data represented in analytic engine correctly
Appropriate presentation of information, e.g.,
personalized dashboards
Scalability of environment
Data volumes – small beginnings to 100’s of terabytes?
From a few users to 1000’s
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
42
Considerations for BI SaaS
Performance
From simple to complex queries
Response times – operational to strategic BI
Getting right data to right people at right time
Open Architecture
Compliance with best practices?
Non-proprietary infrastructures?
Integration with existing infrastructure?
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
43
Considerations for BI SaaS
What does SaaS vendor bring to the table?
Best practices
Quick start BI components like a library of reports,
analytic calculations, KPIs, etc.
Industry-specific knowledge
Horizontal business knowledge
Support for all employees in all levels of enterprise
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
44
BI SaaS
Pros
Fixed cost –
subscription model
Fixed time
Flexibility /
customization
Single vendor
responsible for entire
environment
Quick ramp up
Cons
New paradigm –
nervousness?
Can a company maintain
its uniqueness?
Loss of “control” over
data, quality, access
Vendor’s timeliness in
response to changes
Vendor’s industry
knowledge
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
45
Sample BI SaaS Vendors
LucidEra
Xactly
Eyeris
PivotLink (was
SeaTab)
Oco
On Demand IQ
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
Actuate
Cognos
SAP ERP
SAS
Business Objects
SalesForce.com
Dimensional Insight
46
Putting It All Together
Going Beyond Traditional BI – Operational BI Takes
the Stage
Data Warehouse Appliances and Analytic
Databases – Making Life Simpler
BI Software as a Service – Feeling SaaS-y?
Open Source BI – Free Software Anyone?
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
47
Open Source Vendors Face
Questions
The myths and doubts:
Is there support for open source BI?
How many people are really using it?
Will it scale? Is it considered enterprise class?
Is it only for developers?
These are being overcome…
According to Aberdeen*, 25% of survey respondents will adopt open
source BI in next 12 to 24 months
CEOs agree – open source is a worldwide growth story in 2008**
First nine months of 2007, open source deal flows doubled each
quarter***
Sun’s commitment to open source - $1 Billion for MySQL
* Source: “The TCO of Business Intelligence – Open Source Takes on Traditional BI”, www.aberdeen.com
** Source: www.OpenSolutionsAlliance.org
*** Source: www.the451group.com
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
48
Why Use Open Source?
Price!
Open Source software can be downloaded, installed and
operated free of charge
Return on investment (ROI) of Open Source model is
good
Open Source software is reliable and scalable
Just look at the Internet – its infrastructure relies heavily
on Open Source software
Wall Street – 8 of top 10 banks use Open Source
technologies
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49
Why Use Open Source?
Open Source community grown to significant size
Millions of developers contributing everyday
Cost of development is externalized
Ability to adapt or customize
Many companies don’t want or need feature bloat
Easy integration and performance
New tools for building browser based reports and
dashboards accessible to more people
Ad-hoc report designers with drag and drop capabilities
Enhanced wizards for custom data source
implementation
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
50
Open Source Offerings
BI projects won’t be consumed by license fees
No huge up-front fees to justify before commencing
a project
“Safe choice”
Many successful deployments
Professional services experts to work with you
Professional, public training
Support from the experts – project leaders and sponsor
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
51
Open Source BI Vendors
Proponents of open source BI point out low cost of
entry, flexibility and variety of applications available
Opponents believe open source BI lacks
functionality needed to succeed right now
Regardless, don’t be fooled by “numbers of
downloads”…
Vendors* – Actuate, JasperSoft, Jpivot, Mondrian,
Pentaho, SpadoBI
* For a more complete list, go to http://www.manageability.org/blog/stuff/open-source-java-business-intelligence
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52
Open Source ETL
Open Source ETL
ETL alternative follows industry standards for ease of use,
quick deployment, and fit into company’s needs
Users download open source ETL code and get started
Can collaborate with open source community to share
integrations and extend tool’s functionality
Will probably need to buy support and services from
company’s professional services and support
Sample Vendors*: Talend, JitterBug, KETL, Pentaho,
Octopus, CloverETL
* For a more complete list, go to http://www.manageability.org/blog/stuff/open-source-etl
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
53
Open Source
Pros
Cons
Cost effective
Easy to install and
deploy
Large development
community
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
How do they make
money?
Many are small
companies
Some offerings not
truly open source
54
Right Place at Right Time –
Get Going!
Once you have your ducks in a row, you are ready
to create the proper environment
Create an infrastructure that can withstand change –
you’ll need it
Pick technologies that support that infrastructure and
move you toward SOA compliance
Constantly monitor business community usage
Measure ROI and publish it
IT infrastructure should be to information as a power
grid is to electricity
Information should flow as freely as electricity does
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved
55
Questions
Claudia Imhoff, Ph.D.
President
Intelligent Solutions, Inc.
www.IntelSols.com
[email protected]
Copyright © 2008, Intelligent Solutions, Inc., All Rights Reserved