Description
A new age of business driven analytics is dawning in the enterprise. A shift is underway as the driver of innovation is moving toward the business and away from traditional IT departments.
IT & DATA MANAGEMENT RESEARCH,
INDUSTRY ANALYSIS & CONSULTING
10 Best Practices for
Cloud Business Intelligence:
Enabling the Business
An ENTERPRISE MANAGEMENT ASSOCIATES® (EMA™) White Paper
Prepared for TIBCO Spotfre
August 2014
Table of Contents
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Executive Summary .......................................................................................................................... 1
Business Driven Business Intelligence and Analytics in the Cloud ................................................... 1
Drivers of Change ............................................................................................................................. 1
Maturing User Community ........................................................................................................ 1
New Technology .......................................................................................................................... 1
Economics ................................................................................................................................... 2
Valuable Data Types .................................................................................................................... 2
How Cloud Enables the Business ..................................................................................................... 2
Pricing and Total Cost of Ownership (TCO) .............................................................................. 4
Architecture and Features ........................................................................................................... 5
Service Management and Service Level Agreements (SLAs) ........................................................ 5
Transparency and Communication ............................................................................................. 5
Application Programming Interface (APIs) ................................................................................. 5
Platform Security ......................................................................................................................... 5
Proof of Concept (POCs) ............................................................................................................ 6
Training ....................................................................................................................................... 6
Vendor Strength .......................................................................................................................... 6
Exit or Relocation........................................................................................................................ 6
EMA Perspective ............................................................................................................................... 7
About TIBCO Spotfre ..................................................................................................................... 7
Page 1
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 1
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Executive Summary
A new age of business driven analytics is dawning in the enterprise. A shift is underway as the driver of
innovation is moving toward the business and away from traditional IT departments. IT professionals
are searching for innovative tools and solutions to meet new analytic demands while building out more
fexible and agile infrastructure to support this trend. Cloud analytic platforms are embracing this
paradigm shift by meeting the economic and technological demands of the newly empowered business
data consumer.
Business Driven Business Intelligence and Analytics in
the Cloud
Enabling the business has long been part of IT’s responsibilities. Te business side of the enterprise is
the customer IT most often serves. Tere is a shift underway that’s afecting the dynamics between these
two, causing IT to scramble to execute and innovate while maintaining Service Level Agreements (SLAs)
and managing more complex data driven ecosystems. At the same time, the number of technology
users is growing exponentially, and a more diverse community of users is demanding access to the IT
managed systems. Te business leader is spearheading this evolution, bringing greater need for insights,
larger data-driven teams, the ability to fail faster, and the budgets to enact change.
Business driven Business Intelligence (BI) and analytics represent a shift
in the enterprise that is perfectly aligned with the value proposition of
cloud-based analytic solutions. Cloud analytics support agility, fexibility,
economic impact, and faster time-to-value; coupling these business
drivers with the following is a recipe for success and diferentiation.
Smart companies are embracing four drivers that propel this change, and
laggards are resisting.
Drivers of Change
Maturing User Community
New, more sophisticated workloads and demands on traditional systems are pushing these architectures
to their limits, causing performance and scalability issues and curtailing the creativity of business users.
A shift from simple reporting to more advanced views of data and the need to discover insights without
the support of IT has created a need for more agile and fexible enterprise level solutions.
New Technology
Te introduction of new technologies is enabling this shift towards innovative solutions. Cloud analytic
platforms are one of the solutions that disrupt and enhance traditional environments and meet the
needs of more sophisticated users and projects. As the business directs more of the IT strategy, they are
enamored with cloud’s ability to reduce risk, enhance deployment time, and create business value faster.
Cloud analytics support
agility, fexibility,
economic impact, and
faster time-to-value.
Page 2
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 2
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Economics
Cloud delivers new pricing and service paradigms that align well with business leaders ofering a
greater level of fexibility while insulating the business from risky CAPEX initiatives. Investing in
better performing analytics helps companies to perform at a higher level while enabling competitive
advantage. Companies with superior business intelligence and analytic strategies are less volatile in
difcult economic times as they beneft greatly from enhanced business insights.
Valuable Data Types
It’s hard to ignore the infux of new data and the value it presents to analytic applications. Social,
machine, and sensor data were once thought impractical to leverage, but are now commonplace within
the enterprise delivering new and compelling value to analytic environments. Tis data is the fuel that
drives the maturing user community mentioned above, and augmenting analytic environments with
this data gives enterprises a competitive advantage.
Each of these drivers taken separately may not evoke the massive change that we are seeing in the
analytical landscape today, but in combination, they are enabling a shift towards new technology and
feeding the demands of business leaders.
ENTERPRISE MANAGEMENT ASSOCIATES® (EMA™) research indicates that 60% of companies
working with new data types are utilizing two to three diferent platforms to complete their projects.
Cloud solutions are the top three on the list for these projects. Tis supports the thesis that cloud is a
mission critical platform for analytics.
Cloud analytic platforms complement the strategies of business driven
analytics by providing the fexibility and agility required by a new breed
of consumer. Cloud often enables the business to partially or entirely
bypass IT support, shortening the time to value for these projects. Tese
newly empowered users are leveraging faster implementation times and
elastic scale of the platforms to jump ahead and create value around their
analytic needs.
How Cloud Enables the Business
Tese new breed analytic platforms are leveraging the technology of the cloud to complement existing
data landscapes and providing greater value to the hybrid data ecosystems many companies are utilizing
to serve the needs of business users. EMA research shows that more than 30% of all big data projects
are executed utilizing cloud analytic technology.
Companies are relying on this platform to help them execute more advanced workloads that meet the
needs of business driven initiatives.
Cloud analytic platforms
complement the strategies
of business driven analytics.
Page 3
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 3
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percentage of Projects
Customer Relations Management
(e.g., ad-hoc operational queries)
Path Analysis, Customer churn (e.g.,
behavioral analysis)
Point of Sale, Customer Care (e.g.,
operational transaction processing)
Billing, Rating (e.g., operational event
and policy processing)
Fraud Analysis, Liquidity Risk
Assessment (e.g., risk management)
Grouping and Relationship Analysis,
Geographic Optimization (e.g.
clustering, social graph)
Staff Scheduling, Logistical Asset
Planning (e.g., asset optimization)
Campaign Optimization, Market
Basket Analysis, Cross-sell/Up-sell
Recommendation
Social Brand Management Analysis
(e.g., event processing with text
analytics)
Sentiment Analysis, Opinion Mining
(e.g., natural language processing,
text analytics)
30.5%
30.0%
38.3%
28.8%
27.5%
29.8%
43.9%
35.2%
34.2%
25.6%
11.9%
10.0%
15.4%
18.6%
24.6%
19.3%
14.0%
22.2%
34.2%
38.5%
15.3%
20.0%
14.9%
16.9%
15.9%
19.3%
14.0%
18.5%
10.5%
20.5%
42.4%
40.0%
38.3%
35.6%
31.9%
31.6%
28.1%
24.1%
21.1%
8.5%
Big Data Project Solution
Project Implementaiton
Employing existing hardware and software infrastructure
Purchasing additional on premises hardware infrastructure
Purchasing additional on premises software infrastructure
Cloud-based Implementation
Cloud analytic platforms are helping customers to step away from traditional and ridged strategies
that demanded that much of the data for analytics be deposited into a conventional data warehouse.
Tese new platforms provide a channel to align the data and workload to the best possible platform
for execution and economic advantage. Recent EMA research illustrates that 32% of companies who
are technically challenged by their existing environment’s ability to scale and support consumers
economically are choosing cloud as the solution.
Cloud analytic platforms are a frst-class citizen of the new hybrid data ecosystem paradigm, and
innovative companies are utilizing it for diferentiation and competitive advantage. Cloud leads in
many categories for companies with bigger and faster data needs to innovate.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percentage of Projects
Establish or maintain competitive advantage with
data management practices
Expand workload processing from sample data
to full datasets
Lower total cost of ownership (TCO) of data
management environment
Improve intelligence about customer buying
behavior
Increase competitive advantage with flexibility of
data used in business solutions
Increase operation efficiencies during offering
design and production
Government regulatory or internal policy
requirements to store larger datasets online
Establish a business edge with speed of
deployment of data management solutions
Faster response time of operational or analytical
workloads
Business requirements for higher levels of
advanced analytics
30.2%
29.1%
33.7%
28.3%
33.0%
38.6%
43.7%
40.4%
37.2%
31.9%
14.8%
18.2%
16.3%
19.2%
19.1%
20.2%
16.3%
19.2%
20.5%
25.0%
14.8%
15.5%
13.0%
20.7%
16.7%
15.2%
14.1%
14.6%
16.7%
18.1%
40.1%
37.3%
37.0%
31.8%
31.1%
26.0%
25.9%
25.8%
25.6%
25.0%
Primary business drivers for Big Data
Project Implementaiton
Employing existing hardware and software infrastructure
Purchasing additional on premises hardware infrastructure
Purchasing additional on premises software infrastructure
Cloud-based Implementation
Page 4
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 4
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Ten Tips for Success
Selecting the right solution for your cloud business intelligence project can be an exciting process. It’s
critical that before jumping in you design a strategy for success. A common mistake made by many is
the assumption that a technology as disruptive and innovative as cloud BI doesn’t require the same due
diligence as all IT projects. Be sure to follow these important steps:
• Develop a compelling project case. Be specifc and identify an opportunity that will beneft your
line of business while focusing on an area of business pain that’s relevant and timely. Pay special
attention to scope as to avoid starting with too broad of an agenda, and/or a project that’s too
difcult to get of the ground.
• Defne the project parameters and identify clear and measurable milestones. Each of these
steps should build towards a well-defned project goal that delivers benefts to all stakeholders in
the process.
• Get consensus. Build a team around a cloud BI project just as you would any similar initiative. Be
sure to create a collaborative environment that includes IT, line of business, project stakeholders,
and executive sponsors.
• Collect and align the resources necessary for the project. Look within your organization for
the proper resources and skill sets required to execute across the life of the project. Leverage these
resources to move quicker and save money.
• Set the project timeline and engage your vendor partner. If possible, enlist the assistance of your
vendor partner to better understand standard challenges and hurdles that can be avoided to carry
you to success quicker.
• Don’t forget to share your success. Te best cloud analytic projects grow and become viral.
Communicate the success of you program and build buy-in from other groups so they can help to
fund further successes.
Once the project has been defned, it’s time to identify the vendor you will partner with to execute
the project plans and address the critical needs of your company. Te following 10 best practices will
create a comprehensive roadmap for vendor selection and provide a checklist that can be used to vet
prospective solution providers.
Pricing and Total Cost of Ownership (TCO)
Cloud analytic solution providers are leveraging economics of scale along
with new purpose-built solutions to disrupt the traditional software
pricing models many customers are accustomed to. At the heart of these
models is a newfound fexibility that enables clients to avoid risky CAPEX
expenditures when beginning new projects. Te ability to avoid paying
for hardware, hosting, and maintenance can greatly impact the overall
total cost of ownership of an analytic project. Avoiding the traditional CAPEX expenditures increases
“time to value” for many projects as it circumvents the often laborious process of attaining budgetary
approvals for capital investments. Many cloud analytic solutions begin by licensing for each user on
a monthly, quarterly or annual subscription basis. Tis allows more fexibility and the opportunity to
better manage ongoing costs of a project. In the end, many cloud analytics projects can provide an
economic advantage over traditional deployments. Be sure to work through the model that fts your
frm best and take into account the overall length of the project and expected growth to ensure the total
cost of the project over time meets your goals.
Avoiding the traditional
CAPEX expenditures
increases “time to value”
for many projects.
Page 5
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 5
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Architecture and Features
Leading cloud analytic companies deliver fully featured solutions that keep pace with on-premises
competitors. Be sure to fully review the capabilities of prospective solutions to ensure the feature set
meets your needs today and for the future. Examine the release schedule and roadmap for your provider
to better understand when new releases will be available. Some cloud analytic frms have a monthly
release cadence that enables the client to beneft from ongoing feature improvements. Tese fast-paced
releases are an excellent example of why cloud analytic solutions can often outperform traditional
solutions that improve at a slower pace. Depending on the architecture of your provider, you may be
able to align these releases with your optimal IT schedule and business fow. Customization can be
difcult in many cloud environments; be sure to investigate your specifc needs and determine costs in
advance. Some environments that are multi-tenant (many customers sharing a single architecture) can
be restrictive with regards to custom features.
Service Management and Service Level Agreements (SLAs)
Relying on an outside vendor to manage and support your critical analytic environment can be a daunting
challenge and a culture shift for many companies. It pays to understand the service capabilities of your
vendor in advance to determine how they will monitor your environment, report on performance,
and help to resolve service issues. You will fnd that some smaller providers are challenged to maintain
enterprise level customer service and support. Determine how they support new user provisioning,
license management, system load balancing, and elasticity, as these are all critical components of a high
performing system. Vendors who invest heavily in the care and service side of the cloud will ofer the
ability to have assigned technical support and real-time chat support for customers. Te technologies
supporting cloud analytics is maturing fast, and new hardware and management techniques are allowing
vendors to deliver uptime, scalability, and speeds required by most enterprise projects.
Transparency and Communication
Communication is the foundation of any prosperous relationship, and you should demand a high level
of transparency from cloud analytic providers. Many of them host real-time performance portals so
customers are able to see system performance, uptime, outage scheduling, support issues, and scheduled
maintenance. Tese views behind the curtain are critical to build trust as the business relationship
grows. Some vendors host performance dashboards and ofer reporting to help support the insight
required to manage a cloud relationship.
Application Programming Interface (APIs)
APIs are a must for a successful cloud analytic environment. All too often
cloud platforms can become silos, closed of to other critical systems and
applications. Leaders in cloud analytics will ofer a wide array of connector
options that help to maintain synergy between enterprise platforms and
data. Additionally, some vendors will create an extensible environment by publishing and supporting
Software Developer Kits (SDKs) that promote the extension and functionality of the analytic platform.
If fexibility and connectivity are critical to your deployment, look for vendors who excel in this area.
Platform Security
Early on in the adoption of cloud-based analytic solutions, many clients expressed concerns over data
security and platform security. 53% of EMA research respondents ranked it number one on their list
of concerns or challenges for cloud. Analysts and press that needed to balance their coverage of these
APIs are a must for
a successful cloud
analytic environment.
Page 6
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 6
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
innovative solutions with cautionary notes promoted much of this concern. In reality, security issues are
few and far between on cloud analytic platforms. Early certifcations and audits of vendors were based
more in the physical world of security versus the cloud. New areas of focus are emerging, and leading
vendors are working to align with these strategies and certifcations. Look for vendors that take the
security challenge seriously, but don’t allow unfounded fears to drive you away from the upside these
solutions present. Leaders in the market are investing in their infrastructure and policies to deliver a
high level of performance. Take logical steps to ensure your vendor is committed to securing your data
and is transparent in its reporting on the subject.
Proof of Concept (POCs)
Because it’s easier to test an existing system, cloud analytic vendors are liberal with their test drive
or proof of concept services. Deploying a POC before committing to a long-term cloud analytic
partnership is part of a smart strategy. Beyond ensuring the platform can perform, it allows for a greater
level of buy-in and support for key stakeholders in the project, and helps to drive adoption of the
production project. POCs reduce risk and help ensure a smooth transition to the right vendor solution.
Training
Training is a requirement of most, if not all, IT-related projects. Cloud
analytics is no diferent, and it’s important that you ensure the vendor
you are reviewing can deliver the level of sophistication in training that
matches your project and support culture. Many Software as a Service
(SaaS) solutions ofer intuitive user interfaces, but training remains
important. Research whether the vendor supports a community of users
that you can leverage with and learn from. Visit the forums and FAQ
resources, research user groups, onsite seminars, and conferences designed to support you and your
team post-purchase. Expect that smaller or new entrants to the cloud analytic market will only meet
the minimum needs of most enterprise projects.
Vendor Strength
Cloud analytic projects are critical to driving a business and it’s important to gauge the strength of
the frm you choose to partner with. As new and innovative technologies enter a market, upstart
companies who have identifed the market opportunity often deliver them. Tese smaller/newer frms
can be volatile and add risk to your project. If you plan to work with one of these frms, research their
funding sources and venture capital positions, executive team, partner networks, and be sure to demand
references. Focus on examples that closely match the parameters of your project to help you assess their
ability to deliver.
Exit or Relocation
Once you have executed against all of these previous steps it may seem odd to focus on changing your
mind, but as with any project requirements and scope will evolve, and once you are up and running
there are many reasons you may need to change vendors or move your project. Before committing to
a vendor, understand the process for migrating to on-premises deployments. Some vendors are capable
of serving their solution both ways, and at some point your circumstances may require moving the
solution back behind your frewall. Migration to the competition is an exit strategy that some vendors
can hinder. Be sure there is no impractical data transfer fees or penalties in the contract that make this
process difcult. Smart vendors recognize this and are making their platforms and your data highly
portable and fexible.
Ensure the vendor you
are reviewing can deliver
the level of sophistication
in training that matches
your project.
Page 7
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 7
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
EMA Perspective
Te ten guidelines above are a practical guide to ensuring your vendor relationship is successful. Taking
care in vendor selection will help ensure a cloud analytics project will meet the needs of a more powerful
and demanding business user/customer. Meeting the needs of the business by utilizing cloud platforms
enables a company to bring an innovative solution to the problem while mitigating economic risk
and creating opportunities for faster time to value. Modern businesses are searching for a competitive
edge that enables a broader community to access and leverage critical enterprise data to make smarter
and faster business decisions. Cloud analytics have matured to meet the challenge and are a viable and
innovative alternative to less fexible solutions. EMA research shows that cloud plays a key role in Big
Data analytic projects and new, more sophisticated workloads driving highly competitive companies.
About TIBCO Spotfre
TIBCO Spotfre® is the analytics solution from infrastructure and business intelligence giant, TIBCO
Software. From interactive dashboards and data discovery to predictive and real-time analytics, Spotfre’s
intuitive software provides an astonishingly fast and fexible environment for visualizing and analyzing
your data. As your analytics needs increase, our enterprise-class capabilities can be seamlessly layered
on, helping you to be frst to insight—and frst to action.
Spotfre gives you the choice to deploy in the Cloud or on premises, with oferings for enterprises,
departments, and individuals. Learn more about TIBCO Spotfre at spotfre.com
About Enterprise Management Associates, Inc.
Founded in 1996, Enterprise Management Associates (EMA) is a leading industry analyst frm that provides deep insight across the full spectrum
of IT and data management technologies. EMA analysts leverage a unique combination of practical experience, insight into industry best practices,
and in-depth knowledge of current and planned vendor solutions to help EMA clients achieve their goals. Learn more about EMA research,
analysis, and consulting services for enterprise line of business users, IT professionals and IT vendors at www.enterprisemanagement.com or
blogs.enterprisemanagement.com. You can also follow EMA on Twitter, Facebook or LinkedIn.
Tis report in whole or in part may not be duplicated, reproduced, stored in a retrieval system or retransmitted without prior written permission
of Enterprise Management Associates, Inc. All opinions and estimates herein constitute our judgement as of this date and are subject to change
without notice. Product names mentioned herein may be trademarks and/or registered trademarks of their respective companies. “EMA” and
“Enterprise Management Associates” are trademarks of Enterprise Management Associates, Inc. in the United States and other countries.
©2014 Enterprise Management Associates, Inc. All Rights Reserved. EMA™, ENTERPRISE MANAGEMENT ASSOCIATES
®
, and the
mobius symbol are registered trademarks or common-law trademarks of Enterprise Management Associates, Inc.
Corporate Headquarters:
1995 North 57th Court, Suite 120
Boulder, CO 80301
Phone: +1 303.543.9500
Fax: +1 303.543.7687
www.enterprisemanagement.com
2943.080414
doc_788505191.pdf
A new age of business driven analytics is dawning in the enterprise. A shift is underway as the driver of innovation is moving toward the business and away from traditional IT departments.
IT & DATA MANAGEMENT RESEARCH,
INDUSTRY ANALYSIS & CONSULTING
10 Best Practices for
Cloud Business Intelligence:
Enabling the Business
An ENTERPRISE MANAGEMENT ASSOCIATES® (EMA™) White Paper
Prepared for TIBCO Spotfre
August 2014
Table of Contents
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Executive Summary .......................................................................................................................... 1
Business Driven Business Intelligence and Analytics in the Cloud ................................................... 1
Drivers of Change ............................................................................................................................. 1
Maturing User Community ........................................................................................................ 1
New Technology .......................................................................................................................... 1
Economics ................................................................................................................................... 2
Valuable Data Types .................................................................................................................... 2
How Cloud Enables the Business ..................................................................................................... 2
Pricing and Total Cost of Ownership (TCO) .............................................................................. 4
Architecture and Features ........................................................................................................... 5
Service Management and Service Level Agreements (SLAs) ........................................................ 5
Transparency and Communication ............................................................................................. 5
Application Programming Interface (APIs) ................................................................................. 5
Platform Security ......................................................................................................................... 5
Proof of Concept (POCs) ............................................................................................................ 6
Training ....................................................................................................................................... 6
Vendor Strength .......................................................................................................................... 6
Exit or Relocation........................................................................................................................ 6
EMA Perspective ............................................................................................................................... 7
About TIBCO Spotfre ..................................................................................................................... 7
Page 1
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 1
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Executive Summary
A new age of business driven analytics is dawning in the enterprise. A shift is underway as the driver of
innovation is moving toward the business and away from traditional IT departments. IT professionals
are searching for innovative tools and solutions to meet new analytic demands while building out more
fexible and agile infrastructure to support this trend. Cloud analytic platforms are embracing this
paradigm shift by meeting the economic and technological demands of the newly empowered business
data consumer.
Business Driven Business Intelligence and Analytics in
the Cloud
Enabling the business has long been part of IT’s responsibilities. Te business side of the enterprise is
the customer IT most often serves. Tere is a shift underway that’s afecting the dynamics between these
two, causing IT to scramble to execute and innovate while maintaining Service Level Agreements (SLAs)
and managing more complex data driven ecosystems. At the same time, the number of technology
users is growing exponentially, and a more diverse community of users is demanding access to the IT
managed systems. Te business leader is spearheading this evolution, bringing greater need for insights,
larger data-driven teams, the ability to fail faster, and the budgets to enact change.
Business driven Business Intelligence (BI) and analytics represent a shift
in the enterprise that is perfectly aligned with the value proposition of
cloud-based analytic solutions. Cloud analytics support agility, fexibility,
economic impact, and faster time-to-value; coupling these business
drivers with the following is a recipe for success and diferentiation.
Smart companies are embracing four drivers that propel this change, and
laggards are resisting.
Drivers of Change
Maturing User Community
New, more sophisticated workloads and demands on traditional systems are pushing these architectures
to their limits, causing performance and scalability issues and curtailing the creativity of business users.
A shift from simple reporting to more advanced views of data and the need to discover insights without
the support of IT has created a need for more agile and fexible enterprise level solutions.
New Technology
Te introduction of new technologies is enabling this shift towards innovative solutions. Cloud analytic
platforms are one of the solutions that disrupt and enhance traditional environments and meet the
needs of more sophisticated users and projects. As the business directs more of the IT strategy, they are
enamored with cloud’s ability to reduce risk, enhance deployment time, and create business value faster.
Cloud analytics support
agility, fexibility,
economic impact, and
faster time-to-value.
Page 2
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 2
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Economics
Cloud delivers new pricing and service paradigms that align well with business leaders ofering a
greater level of fexibility while insulating the business from risky CAPEX initiatives. Investing in
better performing analytics helps companies to perform at a higher level while enabling competitive
advantage. Companies with superior business intelligence and analytic strategies are less volatile in
difcult economic times as they beneft greatly from enhanced business insights.
Valuable Data Types
It’s hard to ignore the infux of new data and the value it presents to analytic applications. Social,
machine, and sensor data were once thought impractical to leverage, but are now commonplace within
the enterprise delivering new and compelling value to analytic environments. Tis data is the fuel that
drives the maturing user community mentioned above, and augmenting analytic environments with
this data gives enterprises a competitive advantage.
Each of these drivers taken separately may not evoke the massive change that we are seeing in the
analytical landscape today, but in combination, they are enabling a shift towards new technology and
feeding the demands of business leaders.
ENTERPRISE MANAGEMENT ASSOCIATES® (EMA™) research indicates that 60% of companies
working with new data types are utilizing two to three diferent platforms to complete their projects.
Cloud solutions are the top three on the list for these projects. Tis supports the thesis that cloud is a
mission critical platform for analytics.
Cloud analytic platforms complement the strategies of business driven
analytics by providing the fexibility and agility required by a new breed
of consumer. Cloud often enables the business to partially or entirely
bypass IT support, shortening the time to value for these projects. Tese
newly empowered users are leveraging faster implementation times and
elastic scale of the platforms to jump ahead and create value around their
analytic needs.
How Cloud Enables the Business
Tese new breed analytic platforms are leveraging the technology of the cloud to complement existing
data landscapes and providing greater value to the hybrid data ecosystems many companies are utilizing
to serve the needs of business users. EMA research shows that more than 30% of all big data projects
are executed utilizing cloud analytic technology.
Companies are relying on this platform to help them execute more advanced workloads that meet the
needs of business driven initiatives.
Cloud analytic platforms
complement the strategies
of business driven analytics.
Page 3
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 3
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percentage of Projects
Customer Relations Management
(e.g., ad-hoc operational queries)
Path Analysis, Customer churn (e.g.,
behavioral analysis)
Point of Sale, Customer Care (e.g.,
operational transaction processing)
Billing, Rating (e.g., operational event
and policy processing)
Fraud Analysis, Liquidity Risk
Assessment (e.g., risk management)
Grouping and Relationship Analysis,
Geographic Optimization (e.g.
clustering, social graph)
Staff Scheduling, Logistical Asset
Planning (e.g., asset optimization)
Campaign Optimization, Market
Basket Analysis, Cross-sell/Up-sell
Recommendation
Social Brand Management Analysis
(e.g., event processing with text
analytics)
Sentiment Analysis, Opinion Mining
(e.g., natural language processing,
text analytics)
30.5%
30.0%
38.3%
28.8%
27.5%
29.8%
43.9%
35.2%
34.2%
25.6%
11.9%
10.0%
15.4%
18.6%
24.6%
19.3%
14.0%
22.2%
34.2%
38.5%
15.3%
20.0%
14.9%
16.9%
15.9%
19.3%
14.0%
18.5%
10.5%
20.5%
42.4%
40.0%
38.3%
35.6%
31.9%
31.6%
28.1%
24.1%
21.1%
8.5%
Big Data Project Solution
Project Implementaiton
Employing existing hardware and software infrastructure
Purchasing additional on premises hardware infrastructure
Purchasing additional on premises software infrastructure
Cloud-based Implementation
Cloud analytic platforms are helping customers to step away from traditional and ridged strategies
that demanded that much of the data for analytics be deposited into a conventional data warehouse.
Tese new platforms provide a channel to align the data and workload to the best possible platform
for execution and economic advantage. Recent EMA research illustrates that 32% of companies who
are technically challenged by their existing environment’s ability to scale and support consumers
economically are choosing cloud as the solution.
Cloud analytic platforms are a frst-class citizen of the new hybrid data ecosystem paradigm, and
innovative companies are utilizing it for diferentiation and competitive advantage. Cloud leads in
many categories for companies with bigger and faster data needs to innovate.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percentage of Projects
Establish or maintain competitive advantage with
data management practices
Expand workload processing from sample data
to full datasets
Lower total cost of ownership (TCO) of data
management environment
Improve intelligence about customer buying
behavior
Increase competitive advantage with flexibility of
data used in business solutions
Increase operation efficiencies during offering
design and production
Government regulatory or internal policy
requirements to store larger datasets online
Establish a business edge with speed of
deployment of data management solutions
Faster response time of operational or analytical
workloads
Business requirements for higher levels of
advanced analytics
30.2%
29.1%
33.7%
28.3%
33.0%
38.6%
43.7%
40.4%
37.2%
31.9%
14.8%
18.2%
16.3%
19.2%
19.1%
20.2%
16.3%
19.2%
20.5%
25.0%
14.8%
15.5%
13.0%
20.7%
16.7%
15.2%
14.1%
14.6%
16.7%
18.1%
40.1%
37.3%
37.0%
31.8%
31.1%
26.0%
25.9%
25.8%
25.6%
25.0%
Primary business drivers for Big Data
Project Implementaiton
Employing existing hardware and software infrastructure
Purchasing additional on premises hardware infrastructure
Purchasing additional on premises software infrastructure
Cloud-based Implementation
Page 4
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 4
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Ten Tips for Success
Selecting the right solution for your cloud business intelligence project can be an exciting process. It’s
critical that before jumping in you design a strategy for success. A common mistake made by many is
the assumption that a technology as disruptive and innovative as cloud BI doesn’t require the same due
diligence as all IT projects. Be sure to follow these important steps:
• Develop a compelling project case. Be specifc and identify an opportunity that will beneft your
line of business while focusing on an area of business pain that’s relevant and timely. Pay special
attention to scope as to avoid starting with too broad of an agenda, and/or a project that’s too
difcult to get of the ground.
• Defne the project parameters and identify clear and measurable milestones. Each of these
steps should build towards a well-defned project goal that delivers benefts to all stakeholders in
the process.
• Get consensus. Build a team around a cloud BI project just as you would any similar initiative. Be
sure to create a collaborative environment that includes IT, line of business, project stakeholders,
and executive sponsors.
• Collect and align the resources necessary for the project. Look within your organization for
the proper resources and skill sets required to execute across the life of the project. Leverage these
resources to move quicker and save money.
• Set the project timeline and engage your vendor partner. If possible, enlist the assistance of your
vendor partner to better understand standard challenges and hurdles that can be avoided to carry
you to success quicker.
• Don’t forget to share your success. Te best cloud analytic projects grow and become viral.
Communicate the success of you program and build buy-in from other groups so they can help to
fund further successes.
Once the project has been defned, it’s time to identify the vendor you will partner with to execute
the project plans and address the critical needs of your company. Te following 10 best practices will
create a comprehensive roadmap for vendor selection and provide a checklist that can be used to vet
prospective solution providers.
Pricing and Total Cost of Ownership (TCO)
Cloud analytic solution providers are leveraging economics of scale along
with new purpose-built solutions to disrupt the traditional software
pricing models many customers are accustomed to. At the heart of these
models is a newfound fexibility that enables clients to avoid risky CAPEX
expenditures when beginning new projects. Te ability to avoid paying
for hardware, hosting, and maintenance can greatly impact the overall
total cost of ownership of an analytic project. Avoiding the traditional CAPEX expenditures increases
“time to value” for many projects as it circumvents the often laborious process of attaining budgetary
approvals for capital investments. Many cloud analytic solutions begin by licensing for each user on
a monthly, quarterly or annual subscription basis. Tis allows more fexibility and the opportunity to
better manage ongoing costs of a project. In the end, many cloud analytics projects can provide an
economic advantage over traditional deployments. Be sure to work through the model that fts your
frm best and take into account the overall length of the project and expected growth to ensure the total
cost of the project over time meets your goals.
Avoiding the traditional
CAPEX expenditures
increases “time to value”
for many projects.
Page 5
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 5
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
Architecture and Features
Leading cloud analytic companies deliver fully featured solutions that keep pace with on-premises
competitors. Be sure to fully review the capabilities of prospective solutions to ensure the feature set
meets your needs today and for the future. Examine the release schedule and roadmap for your provider
to better understand when new releases will be available. Some cloud analytic frms have a monthly
release cadence that enables the client to beneft from ongoing feature improvements. Tese fast-paced
releases are an excellent example of why cloud analytic solutions can often outperform traditional
solutions that improve at a slower pace. Depending on the architecture of your provider, you may be
able to align these releases with your optimal IT schedule and business fow. Customization can be
difcult in many cloud environments; be sure to investigate your specifc needs and determine costs in
advance. Some environments that are multi-tenant (many customers sharing a single architecture) can
be restrictive with regards to custom features.
Service Management and Service Level Agreements (SLAs)
Relying on an outside vendor to manage and support your critical analytic environment can be a daunting
challenge and a culture shift for many companies. It pays to understand the service capabilities of your
vendor in advance to determine how they will monitor your environment, report on performance,
and help to resolve service issues. You will fnd that some smaller providers are challenged to maintain
enterprise level customer service and support. Determine how they support new user provisioning,
license management, system load balancing, and elasticity, as these are all critical components of a high
performing system. Vendors who invest heavily in the care and service side of the cloud will ofer the
ability to have assigned technical support and real-time chat support for customers. Te technologies
supporting cloud analytics is maturing fast, and new hardware and management techniques are allowing
vendors to deliver uptime, scalability, and speeds required by most enterprise projects.
Transparency and Communication
Communication is the foundation of any prosperous relationship, and you should demand a high level
of transparency from cloud analytic providers. Many of them host real-time performance portals so
customers are able to see system performance, uptime, outage scheduling, support issues, and scheduled
maintenance. Tese views behind the curtain are critical to build trust as the business relationship
grows. Some vendors host performance dashboards and ofer reporting to help support the insight
required to manage a cloud relationship.
Application Programming Interface (APIs)
APIs are a must for a successful cloud analytic environment. All too often
cloud platforms can become silos, closed of to other critical systems and
applications. Leaders in cloud analytics will ofer a wide array of connector
options that help to maintain synergy between enterprise platforms and
data. Additionally, some vendors will create an extensible environment by publishing and supporting
Software Developer Kits (SDKs) that promote the extension and functionality of the analytic platform.
If fexibility and connectivity are critical to your deployment, look for vendors who excel in this area.
Platform Security
Early on in the adoption of cloud-based analytic solutions, many clients expressed concerns over data
security and platform security. 53% of EMA research respondents ranked it number one on their list
of concerns or challenges for cloud. Analysts and press that needed to balance their coverage of these
APIs are a must for
a successful cloud
analytic environment.
Page 6
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 6
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
innovative solutions with cautionary notes promoted much of this concern. In reality, security issues are
few and far between on cloud analytic platforms. Early certifcations and audits of vendors were based
more in the physical world of security versus the cloud. New areas of focus are emerging, and leading
vendors are working to align with these strategies and certifcations. Look for vendors that take the
security challenge seriously, but don’t allow unfounded fears to drive you away from the upside these
solutions present. Leaders in the market are investing in their infrastructure and policies to deliver a
high level of performance. Take logical steps to ensure your vendor is committed to securing your data
and is transparent in its reporting on the subject.
Proof of Concept (POCs)
Because it’s easier to test an existing system, cloud analytic vendors are liberal with their test drive
or proof of concept services. Deploying a POC before committing to a long-term cloud analytic
partnership is part of a smart strategy. Beyond ensuring the platform can perform, it allows for a greater
level of buy-in and support for key stakeholders in the project, and helps to drive adoption of the
production project. POCs reduce risk and help ensure a smooth transition to the right vendor solution.
Training
Training is a requirement of most, if not all, IT-related projects. Cloud
analytics is no diferent, and it’s important that you ensure the vendor
you are reviewing can deliver the level of sophistication in training that
matches your project and support culture. Many Software as a Service
(SaaS) solutions ofer intuitive user interfaces, but training remains
important. Research whether the vendor supports a community of users
that you can leverage with and learn from. Visit the forums and FAQ
resources, research user groups, onsite seminars, and conferences designed to support you and your
team post-purchase. Expect that smaller or new entrants to the cloud analytic market will only meet
the minimum needs of most enterprise projects.
Vendor Strength
Cloud analytic projects are critical to driving a business and it’s important to gauge the strength of
the frm you choose to partner with. As new and innovative technologies enter a market, upstart
companies who have identifed the market opportunity often deliver them. Tese smaller/newer frms
can be volatile and add risk to your project. If you plan to work with one of these frms, research their
funding sources and venture capital positions, executive team, partner networks, and be sure to demand
references. Focus on examples that closely match the parameters of your project to help you assess their
ability to deliver.
Exit or Relocation
Once you have executed against all of these previous steps it may seem odd to focus on changing your
mind, but as with any project requirements and scope will evolve, and once you are up and running
there are many reasons you may need to change vendors or move your project. Before committing to
a vendor, understand the process for migrating to on-premises deployments. Some vendors are capable
of serving their solution both ways, and at some point your circumstances may require moving the
solution back behind your frewall. Migration to the competition is an exit strategy that some vendors
can hinder. Be sure there is no impractical data transfer fees or penalties in the contract that make this
process difcult. Smart vendors recognize this and are making their platforms and your data highly
portable and fexible.
Ensure the vendor you
are reviewing can deliver
the level of sophistication
in training that matches
your project.
Page 7
©2014 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com 7
10 Best Practices for Cloud Business Intelligence:
Enabling the Business
EMA Perspective
Te ten guidelines above are a practical guide to ensuring your vendor relationship is successful. Taking
care in vendor selection will help ensure a cloud analytics project will meet the needs of a more powerful
and demanding business user/customer. Meeting the needs of the business by utilizing cloud platforms
enables a company to bring an innovative solution to the problem while mitigating economic risk
and creating opportunities for faster time to value. Modern businesses are searching for a competitive
edge that enables a broader community to access and leverage critical enterprise data to make smarter
and faster business decisions. Cloud analytics have matured to meet the challenge and are a viable and
innovative alternative to less fexible solutions. EMA research shows that cloud plays a key role in Big
Data analytic projects and new, more sophisticated workloads driving highly competitive companies.
About TIBCO Spotfre
TIBCO Spotfre® is the analytics solution from infrastructure and business intelligence giant, TIBCO
Software. From interactive dashboards and data discovery to predictive and real-time analytics, Spotfre’s
intuitive software provides an astonishingly fast and fexible environment for visualizing and analyzing
your data. As your analytics needs increase, our enterprise-class capabilities can be seamlessly layered
on, helping you to be frst to insight—and frst to action.
Spotfre gives you the choice to deploy in the Cloud or on premises, with oferings for enterprises,
departments, and individuals. Learn more about TIBCO Spotfre at spotfre.com
About Enterprise Management Associates, Inc.
Founded in 1996, Enterprise Management Associates (EMA) is a leading industry analyst frm that provides deep insight across the full spectrum
of IT and data management technologies. EMA analysts leverage a unique combination of practical experience, insight into industry best practices,
and in-depth knowledge of current and planned vendor solutions to help EMA clients achieve their goals. Learn more about EMA research,
analysis, and consulting services for enterprise line of business users, IT professionals and IT vendors at www.enterprisemanagement.com or
blogs.enterprisemanagement.com. You can also follow EMA on Twitter, Facebook or LinkedIn.
Tis report in whole or in part may not be duplicated, reproduced, stored in a retrieval system or retransmitted without prior written permission
of Enterprise Management Associates, Inc. All opinions and estimates herein constitute our judgement as of this date and are subject to change
without notice. Product names mentioned herein may be trademarks and/or registered trademarks of their respective companies. “EMA” and
“Enterprise Management Associates” are trademarks of Enterprise Management Associates, Inc. in the United States and other countries.
©2014 Enterprise Management Associates, Inc. All Rights Reserved. EMA™, ENTERPRISE MANAGEMENT ASSOCIATES
®
, and the
mobius symbol are registered trademarks or common-law trademarks of Enterprise Management Associates, Inc.
Corporate Headquarters:
1995 North 57th Court, Suite 120
Boulder, CO 80301
Phone: +1 303.543.9500
Fax: +1 303.543.7687
www.enterprisemanagement.com
2943.080414
doc_788505191.pdf