When SaaS and On-Premise BI Collide - 1105 Media: Home...

When SaaS and

On-Premise BI Collide:

The Pros and Cons of Moving BI to the Cloud

Wayne EckersonDirector, TDWI Research

November 19, 2009

Sponsor

Agenda

• Cloud-based computing

– Terminology

– Types

– Architectures

– Benefits

• BI in the Cloud

– Applications

– Platforms and Infrastructure

Generally speaking…..

• Cloud computing

• Software-as-a-service (SaaS)

• On Demand

Commercial hardware or software

services that you access over the internet

via a Web browser.

Virtualized services

Cloud computing hides the underlying hardware and

software used to deliver the service

Types of Cloud-based Services

Platform(IDE, OS/API, Runtime)

Infrastructure(Server, Database, Storage)

ApplicationsSoftware-as-a-service

“Salesforce.com”

Platform-as-a-service “DW-as-a-service”

Infrastructure-as-a-service “Amazon EC2”

Solu

tions

Sta

ck

BI in the Cloud

Platform(IDE, OS/API, Runtime)

Infrastructure(Server, Database, Storage)

ApplicationsSoftware-as-a-service

“PivotLink for Retail”

Platform-as-a-service “PivotLink for Analytics”

Solu

tions

Sta

ck

Infrastructure-as-a-service

- “DW as a service”

- Custom

On Demand• Pay and go

– No on-premise SW to install

– Just pay and go

• Pay as you go – Subscription (per user)

– Usage fees

• Free trial

SERVICE PAYMENT

Application service Monthly subscription (per user)

Platform service Subscription and/or usage fee

Infrastructure service Usage fee

Types of Clouds

• Public cloud

– Commercialized cloud services

– Provision servers or applications on demand

• E.g. Amazon EC2

• Private cloud

– Use of cloud in an internal data center

– Virtualization and grid computing

Hosting Architecture

Application

Users

Server

Application

Users

Server

Application

Users

Server

Application

Users

Application

Users

Server

On Premise

Virtualization Layer

Application

Users Users

Server

Virtualization Layer

Single Tenant

(ASP Model) Single Tenant Multi-Tenant

LA

N

VP

N

VP

N

SS

L

SS

L

SS

L

SS

L

Cloud vs On PremiseCLOUD ON PREMISE

Doesn’t require IT to set up and

maintain servers

Requires IT resources to set up and

maintain servers

Doesn’t require capital expenditure Requires capital expenditure

Can deploy quickly Requires IT to purchase servers, install,

and configure sofware

Software upgrades are automatic and

unobtrusive

Software upgrades must be manually

applied and often disrupt existing

applications

Can expand number of users and

processing capacity on demand

Must expand server capacity if adding

lots of users and rewrite license

agreement.

Can terminate service at any time Must continue to pay annual

maintenance fee as agreed upon in

contract.

Things to Consider

• Data loading

• Data security

• SLAs

• Integration

• Pricing

• ROI

• Vendor viability

Cloud Use Cases

• SMB and Departments

– Data mart solutions/applications

• Large enterprises

– Development environments

– Test environments

– Prototype or demonstration

– Analytical sandboxes

– Temporary application

How familiar are you with cloud

computing?

9%

42%

49%

Very familiar

Somewhat familiar

Not very familiar

Based on 183 BI professionals attending TDWI’s World Conference, November, 2009.

How much of your BI solution runs

in the public cloud?


0%

2%

0%

13%

85%

3%

4%

46%

47%

All

Most

Half

Some

None

Today

In 3 Years

What portion of your BI solution runs

in the cloud?


3%

4%

5%

2%

3%

4%

8%

14%

12%

7%

4%

7%

Hardware

Reports

BI tools

Data marts

ETL

Source data

In 3 Years

Today

Size of companies deploying BI in

the cloud TODAY


8%

4%

17%

15%

25%

11%

9%

13%

Under $50M

$50M to $100M

$100M to $500M

$500M to $1B

$1B to $10B

$10B to $50B

$50B+

All of our BI solution

Most of our BI solution

Half of our BI solution

Some of our BI solution

Siz

e o

f com

pa

ny (

revenues)


9%

9%

14%

6%

29%

67%

60%

31%

50%

58%

71%

Under $50M

$50M to $100M

$100M to $500M

$500M to $1B

$1B to $10B

$10B to $50B

$50B+





Size of companies deploying BI in

the cloud IN THREE YEARS

Siz

e o

f com

pany (

revenues)

Size of BI teams deploying BI

solutions in the cloud TODAY

5%

4%

17%

14%

6%

9%

14%

21%

Less than

1

1 to 2

3 to 5

6 to 10

11 to 25

26+

Fu

ll-t

ime B

I sta

ff






7%

5%

4%

15%

4%

57%

43%

64%

35%

41%

46%

Less than 1

1 to 2

3 to 5

6 to 10

11 to 25

26+

Fu

ll-t

ime B

I sta

ff

Size of BI teams deploying BI

solutions in the cloud IN 3 YEARS


BI SaaS – Reasons to Adopt

0% 10% 20% 30% 40% 50%

Low cost approach

Faster development time

Business not technology focused

Easy maintenance

On-demand capacity

Lack of IT budget/resources

Reduce dependence on IT

Minimize risk

Lack of BI/DW skills

Project was not an IT priority

Other

Claudia Imhoff and Colin White, “BI SaaS”, BeyeNetwork Research, 2009. 294 respondents.

SaaS BI makes sense when…

• You don’t have IT resources

• You don’t have capital to spend

• You need a solution quickly

• You can’t estimate capacity or usage

• The application fits your needs closely

• Data volumes are manageable

`

CONFIDENTIAL– Copyright, PivotLink, Inc. 2009, all rights reserved.

`

Shaklee Case Study –Aligning a Global Business with On-demand Business Analytics

November 2009

Ken Harris, [email protected]

`


Background

Ken Harris

• CIO

• 25 years of CIO

experience: Shaklee,

Gap, Nike, PepsiCo

• Multiple BI/DW

implementations

• One goal: Enable

Shaklee to make data-

driven decisions

Shaklee

• #1 natural nutrition

company in the US

• Mission: To enable a

healthier life for

everyone and a better

life for anyone

• 750,000+ Members and

Distributors

• Mid-sized 50 year-old

company

`


Business Challenge

• Massive amounts of data to manage

• Significant number of internal and external users

desiring access

• Difficult to access data in a meaningful way

• Costly data warehouse

• Limited IT resources to maintain DW

• Enable business users to collaborate globally

• Real-time analysis

`


Business Visibility Challenge

Financ

eDistributorsProduct Marketing Customers

Marketing Campaign

Efficiency

What is selling

and to whom?

Forecast vs.

Actual

Average Sale Per

Customer

`


Solution Development

• Evaluated multiple potential solutions both

in-house and SaaS-based.

• Chose PivotLink because:

• Quick time to value

• Simplicity of integration

• Implementation and ongoing processing and

support cost

• They passed our “prove-it” 3 impossible

queries, 1 quarter of data 30 days

• Highly Secure – SAS 70 Type II Certified

`


Benefits and Outcomes

“ We rely on PivotLink to make sure our data is available

24x7, and not every vendor understands what that takes. In

the 3+ years of working with the solution, PivotLink has

consistently delivered on the service and support model. “

----------------------------------------------------------

• Rapid implementation – delivered in 120 days

• Easy low-cost maintenance

• Real-time, global data access without silos

• Accurate and timely insight into customer and

product performance

• PivotLink has been adopted by multiple users in

multiple functional areas for multiple applications

Questions??

Contact Information

• If you have further questions or comments:

Wayne Eckerson, TDWI

[email protected]

Ken Harris, Shaklee

[email protected]

mailto:[email protected]

mailto:[email protected]

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