DescriptionBusiness Insights
Harvard Business School Online’s Business Insights Blog provides the career insights you need to achieve your goals and gain confidence in your business
02 FEB 2021
Tim Stobierski
Analytics, Business Analytics
Whether you manage data initiatives, work with data professionals, or are employed by an organization
that regularly conducts data projects, a firm understanding of what the average data project looks like
can prove highly beneficial to your career. This knowledge—paired with other data skills—is what many
organizations look for when hiring.
No two data projects are identical; each brings its own challenges, opportunities, and potential solutions
that impact its trajectory. Nearly all data projects, however, follow the same basic life cycle from start to
finish. This life cycle can be split into eight common stages, steps, or phases:
1. Generation
2. Collection
3. Processing
4. Storage
5. Management
6. Analysis
7. Visualization
8. Interpretation
Below is a walkthrough of the processes that are typically involved in each of them.
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The data life cycle is often described as a cycle because the lessons learned and insights gleaned from
one data project typically inform the next. In this way, the final step of the process feeds back into the
1. Generation
For the data life cycle to begin, data must first be generated. Otherwise, the following steps can’t be
Data generation occurs regardless of whether you’re aware of it, especially in our increasingly online
world. Some of this data is generated by your organization, some by your customers, and some by third
parties you may or may not be aware of. Every sale, purchase, hire, communication, interaction—
everything generates data. Given the proper attention, this data can often lead to powerful insights that
allow you to better serve your customers and become more effective in your role.
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2. Collection
Not all of the data that’s generated every day is collected or used. It’s up to your data team to identify
what information should be captured and the best means for doing so, and what data is unnecessary or
irrelevant to the project at hand.
You can collect data in a variety of ways, including:
Forms: Web forms, client or customer intake forms, vendor forms, and human resources applications
are some of the most common ways businesses generate data.
Surveys: Surveys can be an effective way to gather vast amounts of information from a large number
of respondents.
Interviews: Interviews and focus groups conducted with customers, users, or job applicants offer
opportunities to gather qualitative and subjective data that may be difficult to capture through other
Direct Observation: Observing how a customer interacts with your website, application, or product can
be an effective way to gather data that may not be offered through the methods above.
It’s important to note that many organizations take a broad approach to data collection, capturing as
much data as possible from each interaction and storing it for potential use. While drawing from this
supply is certainly an option, it’s always important to start by creating a plan to capture the data you
know is critical to your project.
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3. Processing
Once data has been collected, it must be processed. Data processing can refer to various activities,
Data wrangling, in which a data set is cleaned and transformed from its raw form into something more
accessible and usable. This is also known as data cleaning, data munging, or data remediation.
Data compression, in which data is transformed into a format that can be more efficiently stored.
Data encryption, in which data is translated into another form of code to protect it from privacy
Even the simple act of taking a printed form and digitizing it can be considered a form of data
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4. Storage
After data has been collected and processed, it must be stored for future use. This is most commonly
achieved through the creation of databases or datasets. These datasets may then be stored in the cloud,
on servers, or using another form of physical storage like a hard drive, CD, cassette, or floppy disk.
When determining how to best store data for your organization, it’s important to build in a certain level of
redundancy to ensure that a copy of your data will be protected and accessible, even if the original
source becomes corrupted or compromised.
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5. Management
Data management, also called database management, involves organizing, storing, and retrieving data as
necessary over the life of a data project. While referred to here as a “step,” it’s an ongoing process that
takes place from the beginning through the end of a project. Data management includes everything from
storage and encryption to implementing access logs and changelogs that track who has accessed data
and what changes they may have made.
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6. Analysis
Data analysis refers to processes that attempt to glean meaningful insights from raw data. Analysts and
data scientists use different tools and strategies to conduct these analyses. Some of the more commonly
used methods include statistical modeling, algorithms, artificial intelligence, data mining, and machine
Exactly who performs an analysis depends on the specific challenge being addressed, as well as the size
of your organization’s data team. Business analysts, data analysts, and data scientists can all play a role.
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7. Visualization
Data visualization refers to the process of creating graphical representations of your information, typically
through the use of one or more visualization tools. Visualizing data makes it easier to quickly
communicate your analysis to a wider audience both inside and outside your organization. The form your
visualization takes depends on the data you’re working with, as well as the story you want to
While technically not a required step for all data projects, data visualization has become an increasingly
important part of the data life cycle.
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8. Interpretation
Finally, the interpretation phase of the data life cycle provides the opportunity to make sense of your
analysis and visualization. Beyond simply presenting the data, this is when you investigate it through the
lens of your expertise and understanding. Your interpretation may not only include a description or
explanation of what the data shows but, more importantly, what the implications may be.
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The eight steps outlined above offer an effective framework for thinking about a data project’s life cycle.
That being said, it isn’t the only way to think about data. Another commonly cited framework breaks the
data life cycle into the following phases:
While this framework’s phases use slightly different terms, they largely align with the steps outlined in
this article.
Even if you don’t directly work with your organization’s data team or projects, understanding the data life
cycle can empower you to communicate more effectively with those who do. It can also provide insights
that allow you to conceive of potential projects or initiatives.
The good news is that, unless you intend to transition into or start a career as a data analyst or data
scientist, it’s highly unlikely you’ll need a degree in the field. Several faster and more affordable options
for learning basic data skills exist, such as online courses.
Are you interested in improving your data science and analytical skills? Learn more about our online
course Business Analytics, or download the Beginner’s Guide to Data & Analytics to learn how you can
leverage the power of data for professional and organizational success.
About the Author
Tim Stobierski is a marketing specialist and contributing writer for Harvard
Business School Online.
6/15/23, 6:11 PM
The Data Life Cycle – The Data Science Institute at Columbia University
The Data Life Cycle
January 23, 2018
Jeannette M. Wing
By Jeannette M. Wing
Let’s take a step back from data science and look at the larger
picture of the data life cycle.
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The Data Life Cycle – The Data Science Institute at Columbia University
The cycle starts with the generation of data. People generate
data: Every search query we perform, link we click, movie we
watch, book we read, picture we take, message we send, and
place we go contribute to the massive digital footprint we each
generate. Walmart collects 2.5 petabytes of unstructured data
from 1 million customers every hour. (One petabyte is equivalent to
20 million filing cabinets.) Sensors generate data: More and more
sensors monitor the health of our physical infrastructure, e.g.,
bridges, tunnels, and buildings; provide ways to be energy
efficient, e.g., automatic lighting and temperature control in our
rooms at work and at home; and ensure safety on our roads and in
public spaces, e.g., video cameras used for traffic control and for
security protection. As the promise of the Internet of Things plays
out, we will have more and more sensors generating more and
more data. At the other extreme from small, cheap sensors, we
also have large, expensive one-of-a-kind scientific instruments,
which also generate unfathomable amounts of data. The Large
Hadron Collider generates tens of petabytes a year. The Large
Synoptic Survey Telescope is expected to generate 1.28 petabytes
a year. The latest round of Intergovernmental Panel on Climate
Change (IPCC) will produce 100 petabytes of data.
After generation comes collection. Not all data generated is
collected, perhaps out of choice because we do not need or want
to or for practical reasons because the data streams in faster than
we can process. Consider how data are sent from expensive
scientific instruments, such as the IceCube neutrino detector at the
South Pole. Since there are only five polar-orbiting satellites, there
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The Data Life Cycle – The Data Science Institute at Columbia University
are only certain windows of opportunities to transmit restricted
amounts of data from the ground to the air. Suppose we drop data
between the generation and collection stages: Could we possibly
miss the very event we are trying to detect? Deciding what to
collect defines a filter on the data we generate.
After collection comes processing. Here I mean everything from
data cleaning, data wrangling, and data formatting to data
compression, for efficient storage, and data encryption, for secure
After processing comes storage. Here the bits are laid down in
memory. Today we think of storage in terms of magnetic tape and
hard disk drives, but in the future, especially for long-term,
infrequently accessed storage, we will see novel uses of optical
technology and even DNA storage devices.
After storage comes management. We are careful to store our
data in ways both to optimize expected access patterns and to
provide as much generality as possible. Decades of work in
database systems have led us to optimal systems for managing
relational databases, but the kinds of data we generate are not
always a good fit for such systems. We now have structured and
unstructured data, data of many types (e.g., text, audio, image,
video), data that arrive at different velocities, and data that stream
in continuously and in real-time. We need to create and use
different kinds of meta-data for these dimensions of heterogeneity
to maximize our ability to access and modify the data for
subsequent analysis.
Now comes analysis. When most people think of what data
science is they mean data analysis. Here, I include all the
computational and statistical techniques for analyzing data for
some purpose: the algorithms and methods that underlie data
mining, machine learning, and statistical inference, be they to gain
knowledge or insights, build classifiers and predictors, or infer
causality. For sure, data analysis is at the heart of data science.
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The Data Life Cycle – The Data Science Institute at Columbia University
Large amounts of data power today’s machine learning algorithms.
The recent successes of the application of deep learning to
different domains, from image and language understanding to
programming to astronomy, continue to astound me.
But it is not enough to analyze data and spit out an answer. We
need data visualization to help present the answer in a clear and
simple way a human can readily understand and visualize. Here a
picture is worth not a thousand words (that comes later) but a
thousand petabytes! It is at this stage in the data life cycle when
we need to consider, along with functionality, aesthetics and
human visual perception to convey the results of data analysis.
And also, it is not enough just to show a pie chart or bar graph. By
interpretation, we provide the human reader an explanation of
what the picture means. We tell a story explaining the picture’s
context, point, implications, and possible ramifications. It was only
after I came to Columbia and began talking to my colleagues in the
journalism school that I understood the importance of story-telling
for the end user.
Finally, in the end, we have the human. The human could be a
scientist, who through data, makes a new discovery. The human
could be a policymaker who needs to make a decision about a
local community’s future. The human could be in medicine,
treating a patient; in finance, investing client money; in law,
regulating processes and organizations; or in business, making
processes more efficient and reliable to serve customers better.
In the diagram, I omitted the arrows that show that it is a cycle and
that there are many intermediate cycles. Inevitably, after we
present some observations to the user based on data we
generated, the user asks new questions and these questions
require collecting more data or doing more analysis.
I also omitted throughout the diagram the importance of using data
responsibly—at each phase in the cycle. We must remember to
consider ethical and privacy concerns throughout, from privacy
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The Data Life Cycle – The Data Science Institute at Columbia University
preserving collection of data about individuals to ethical decisions
that humans or machines will need to make based on automated
data analysis. This dimension of the data life cycle is so important,
that I plan to devote future posts to it.
And so, from raw bits to a rich story, we have the data life cycle.
Jeannette M. Wing is Avanessians Director of the Data Science
Institute and professor of computer science at Columbia University.
JANUARY 23, 2018
Jeannette M. Wing
Executive Vice President for
The Fu Foundation School of
Engineering and Applied
Professor of Computer Science
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6/15/23, 6:12 PM
Cloud Computing Security Explained By Kansas City IT Consulting Company
Application Security Testing
Offensive 360
Scan your source code by the best SAST technology in the industry
Cloud Computing Security Explained By Kansas
City IT Consulting Company
Published May 25, 2023
Press Services
IT Consulting Company in Kansas City Explained Cloud Computing Security
Olathe, United States – May 25, 2023 / CalTech – Managed IT Services Kansas City /
6/15/23, 6:12 PM
Cloud Computing Security Explained By Kansas City IT Consulting Company
Cloud Computing Security Explained By Kansas
City IT Consulting Company
In recent years, cloud computing has transformed how small businesses like yours can
operate by providing greater flexibility, scalability, prevention against data loss, and cost
savings benefits. Anestimated 94% of organizationsnow use cloud computing services
due to these benefits.
However, a greater need for cloud security comes with the increasing use of cloud
computing. But what is cloud computing security exactly?
Engineering Programs at HCU
Cloud computing security refers to the policies, technologies, and controls that protect
cloud-based data, applications, and infrastructure from unauthorized access, theft, and
cyber threats.
In this blog, well answer the following questions to give you a better understanding of
how to navigate the different cloud security challenges:
What is cloud security?
What are cloud security threats?
What is cloud workload security?
What is data security in cloud computing?
What is infrastructure security in cloud computing?
What Is Cloud Computing Security in Business?
As of 2022, the global market for cloud computing is estimated at $480.04 billion and is
expected to reach a shocking $1,712.44 billion by 2029.
What Is Cloud Security
6/15/23, 6:12 PM
Cloud Computing Security Explained By Kansas City IT Consulting Company
As mentioned, with the increasing popularity of cloud computing comes a greater need
for cloud security solutions to protect against the ever-evolving landscape of cyber
From enabling safer cloud storage protocols to easier data access, the importance of
cloud computing security in business cannot be overstated. Here are some key reasons
Importance of Cloud Computing Security: Insights from
IT Consultant in Kansas City
1. Protection of Sensitive Data:
Your SMB, like many others, probably stores sensitive data on the cloud, such as
customer information, financial data, and intellectual property. The IT consultant in
Kansas City states that if this data falls into the wrong hands, it can cause irreparable
harm to your business. Statistics reveal that 60% of SMBs shut down within six months
or less after a data breach.
Therefore, ensuring that sensitive data is adequately secured with cloud security
controls is paramount. But what is data security in cloud computing? Some popular data
protection methods include:
Access controls
Penetration testing
Virtual private networks (VPNs)
And more
2. Regulatory Compliance:
Depending on your industry, your organization may be required to comply with various
industry regulations, such as GDPR, HIPAA, and PCI DSS.
Failure to comply with these regulations can result in heavy fines, legal action, and even
a loss of business reputation.
6/15/23, 6:12 PM
Cloud Computing Security Explained By Kansas City IT Consulting Company
Engineering Programs at HCU
This is where cloud computing security comes in to help ensure compliance with the
regulations in your industry learn more about how CalTech can help you ensure
compliance with our 34+ years of industry expertise.
3. Maintaining Business Continuity:
Kansas City IT consultant emphasizes the importance of cloud workload security. Any
interruption to a business’s cloud infrastructure can result in substantial downtime,
leading to revenue loss, decreased productivity, and damage to reputation. Implementing
a business continuity strategy is crucial to safeguard your cloud workload capabilities.
Cloud computing security can help businesses maintain business continuity by
preventing cyber-attacks and ensuring the availability of cloud resources with security
measures that include:
Migrating information from traditional data centers to secure cloud environments
Data backup
Disaster recovery
Cloud security posture management
And more
4. Protection Against Cyber Threats:
Cyber threats are becoming increasingly sophisticated and frequent in todays digital age
with43% of all cyber-attackstargeted at small businesses specifically.
What are cloud security threats to be aware of? They appear in many forms, with some
of the most common including:
1. Malware
2. Weak credentials
6/15/23, 6:12 PM
Cloud Computing Security Explained By Kansas City IT Consulting Company
3. Human error
4. Security system misconfiguration
5. Denial of service (DDoS)
6. And more
Luckily, cloud computing security can help businesses protect against these threats by
providing a multi-layered security approach, including encryption, firewalls, and access
Implementing Cloud Security into Your Cybersecurity
Now that weve answered the common question of what is cloud security?, here are
some steps your business can take to implement cloud computing security into your
cybersecurity strategy.
1. Conducting a risk assessment is the first step in developing an effective cloud
computing security strategy. This involves identifying the risks associated with
using cloud services, evaluating the likelihood of these risks occurring, and
determining the potential impact of these risks on the business.
2. Choose a reputable cloud provider:Choosing a reputable one is critical to ensuring
the security of your cloud infrastructure. Look for a provider with a strong security,
compliance, and data protection track record.
3. Implement access controls:Access controls are essential to prevent unauthorized
access to your cloud resources. Implement robust authentication methods, such as
multi-factor authentication, and limit sensitive data access to only those requiring it.
4. Encrypt data:Encryption is another effective way to protect data stored on the cloud
from unauthorized access. Implement encryption for data both in transit and at rest.
5. Monitor your cloud environment:What is infrastructure security in cloud computing?
Monitoring your cloud environment is critical to promptly identifying and responding
to security incidents. Implement security monitoring tools and processes to detect
and respond to security incidents.
6. Train employees:Employees are often the weakest link in an organizations
cybersecurity strategy, responsible for over 88% of all data breaches. Provide regular
cybersecurity training to employees to educate them on the risks associated with
cloud computing and how to avoid them.
6/15/23, 6:12 PM
Cloud Computing Security Explained By Kansas City IT Consulting Company
7. Develop an incident response plan: Security incidents can still occur despite your
best efforts. Developing an incident response plan can help you respond quickly and
effectively to security incidents, minimizing their impact on your business.
What Is Cloud Security and Why Is It Important for Your
SMB? Main Takeaways
So, what is cloud computing security by definition? Cloud computing security is essential
to protecting sensitive data, compliance with regulations, maintaining business
continuity, and protecting against cyber threats.
By taking the necessary steps to protect your cloud networks, you can better manage
security issues facing your business and ensure your cloud infrastructure is secure and
protected from cyber threats.
What is Cloud Computing Security
With 34+ years in business and 12,000+ end users served, CalTech has the technical
know-how to protect you against it all. Find out why were your best choice for perfecting
your cloud security posture management book a free consultationwith one of the leading
IT consulting companies in Kansas City!
6/15/23, 6:12 PM
Cloud Computing Security Explained By Kansas City IT Consulting Company
Contact Information:
CalTech – Managed IT Services Kansas City
13421 W 151st St
Olathe, KS 66062
United States
Allen Rodarte
(866) 962-2831
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Cloud Computing Security Explained By Kansas City IT Consulting Company
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Gartner Reprint
Licensed for Distribution
Magic Quadrant for Cloud Infrastructure and Platform
Published 19 October 2022 – ID G00756608 – 29 min read
By Raj Bala, Dennis Smith, and 3 more
I&O leaders must weave through a perilous environment consisting of increasingly aggressive
cloud providers further complicated by rising inflation, competition for cloud talent, regulatory
mandates, and security and downtime incidents. Use this research to make strategic cloud
provider selections.
Market Definition/Description
Cloud computing is a style of computing in which scalable and elastic IT-enabled capabilities are
delivered as a service using internet technologies. Gartner defines the cloud infrastructure and
platform services (CIPS) market as standardized, highly automated offerings, in which infrastructure
resources (e.g., compute, networking and storage) are complemented by integrated platform
services. These include managed application, database and functions as-a-service offerings. The
resources are scalable and elastic in near real time and are metered by use. Self-service interfaces,
including a web-based user interface (UI) and an API, are exposed directly to the customer. The
resources may be single-tenant or multitenant, and can be hosted by a service provider or onpremises in the customer’s data center.
The scope of the Magic Quadrant for CIPS includes infrastructure as a service (IaaS) and integrated
platform as a service (PaaS) offerings. These include application PaaS (aPaaS), functions as a
service (FaaS), database PaaS (dbPaaS), application developer PaaS (adPaaS) and industrialized
distributed cloud offerings that are often deployed in enterprise data centers.
Magic Quadrant
Figure 1: Magic Quadrant for Cloud Infrastructure and Platform
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Gartner Reprint
Vendor Strengths and Cautions
Alibaba Cloud
Alibaba Cloud (also known as Aliyun in Chinese) is a Visionary in this Magic Quadrant. This Magic
Quadrant evaluation is focused on Alibaba Cloud’s international business, which is headquartered in
Singapore, and our technical assessment was performed using the international service.
Alibaba Cloud is a good fit for cloud-first digital business workloads for customers that are based in
China or Southeast Asia. These customers either wish to leverage Alibaba Cloud’s technology to
support their ecosystem or need to locate cloud infrastructure in China or Southeast Asia. Alibaba
Cloud is focused on expanding its successes in Asia in addition to advancing use of ARM processors
and database PaaS offerings.
Regional and engineering leadership: Alibaba Cloud continues to have a leadership position in
China and the broader Sinosphere, and has a meaningful impact in surrounding countries in terms
6/15/23, 6:13 PM
Gartner Reprint
of market share and capabilities. Alibaba Cloud’s engineering talent is on par with any other cloud
provider, which shows in its efforts such as sustainable data center initiatives with low PUE values,
custom silicon and operating systems.
ISV partnerships: Alibaba Cloud has a rich array of ISV partnerships, including with SAP, VMware,
IBM and Salesforce, in addition to strategic Asia-focused ERP providers like Yonyou and Kingdee.
Further, Alibaba Cloud’s ISV integration accelerator program offers easy provisioning of complex
ISV configurations into customer environments.
Digital channels: Enterprises often view Alibaba Cloud as a pathway to digital transformation and
commerce capabilities. This is based on Alibaba Cloud’s big data and analytics capabilities and its
parent company.
Regulatory and competitive pressure: Alibaba Cloud’s success has been hampered by a
perception of influence from the Chinese authorities, which has created an environment whereby
more government-affiliated cloud providers have growing favor, particularly among public sector
enterprises. Regulatory influence combined with highly active Chinese competitors such as
Huawei and Tencent challenge Alibaba Cloud’s current lead in terms of market share.
MSP ecosystem: Alibaba Cloud lacks a rich MSP ecosystem that a global enterprise would
require. Alibaba Cloud has a rather uneven managed service provider partnership program in China
and a limited supply of qualified partners outside of Asia.
Consistency and transparency: Alibaba Cloud is not as consistent, transparent or predictable with
respect to discounting and pricing relative to international competitors. Gartner clients frequently
complain about the disproportional pricing between basic and premier security offerings and
professional services costs. Alibaba Cloud also lacks an element of transparency from the
perspective of technical details of service implementations. Further, Alibaba Cloud continues to
have significant differences in consistency with respect to functionality between its offerings in
China, which has far greater capabilities compared with its international regions.
Amazon Web Services
Amazon Web Services (AWS), a subsidiary of Amazon, is a Leader in this Magic Quadrant. AWS is
focused on being a broad-based provider of IT services, ranging from cloud-native and edge to ERP
and mission-critical workloads.
AWS has a future focus on expanding the size of the market it serves by moving into new territory
such as private 5G and partnerships with telecoms. AWS’s operations are global. Its customers have
diverse profiles, spanning sizes, industries and locales.
6/15/23, 6:13 PM
Gartner Reprint
Breadth of functionality: AWS continues to have the greatest breadth and depth of capabilities of
any provider in the market for CIPS. AWS has served as a guiding force in the overall market by
setting accepted standards, developing technologies and establishing methodologies that are
often copied in whole by competing cloud providers. The often poor facsimiles made by the cloud
providers commonly lack the data, reasoning and customer adoption that AWS uses to underpin
the offering.
Current market-share lead: AWS’s revenue makes it the current market-share leader in the CIPS
market, exceeding Microsoft Azure, its closest competitor, by two times. Further, AWS is one of the
few vendors in this market that does not exaggerate its business performance to customers based
upon the sale of offerings that are well outside the periphery of what is reasonably considered to
be cloud. Examples of such extraneous padding by other vendors include the sale of licenses for
operating systems and databases on other cloud providers, and on-premises deployed PaaS
platforms that make up significant portions of “cloud” revenue.
Vibrant and prosperous ecosystem: AWS is a magnet for ecosystem partners, given its market
share and momentum. ISV partners often have an “AWS first” prioritization in terms of which cloud
providers to support initially, then the others follow. Partners include SAP, Splunk and VMware.
Eroding customer relationships: Gartner client inquiry surfaces that AWS often optimizes for the
short term when dealing with customers, particularly at the time of contract renewal, resulting in
eroding customer relationships. This, along with executive management changes, changing
customer priorities, provider preferences in various regions and well-heeled competition, paint a
challenging picture for AWS ahead.
Multicloud and sovereign strategy: AWS, the leading provider in this market by market share, has a
relatively weak strategy to support customers seeking sovereign and multicloud solutions. AWS
shows little incentive or interest in pursuing meaningful multicloud strategies on behalf of its
customers, despite the fact that many of its customers also use other cloud providers.
Additionally, AWS has a fairly timid approach to sovereign clouds in Europe, where its competitors
are being more innovative.
Regional dependencies and communication: AWS’s operational incident of 7 December 2021
revealed some multiregion dependencies on the internal AWS network, which is hosted in us-east1. Because us-east-1 also hosts support ticketing for North America, AWS customers also had
difficulty communicating with technical support during the incident. Compounding this was AWS’s
failure to communicate adequately in a timely fashion about the outages as they occurred and the
confoundingly inaccurate Health Dashboard reporting, resulting in customers being left in the dark
about outages.
6/15/23, 6:13 PM
Gartner Reprint
Google is a Leader in this Magic Quadrant. Google Cloud Platform (GCP) is strong in nearly all use
cases and has made significant progress in improving its edge capabilities. Google continues to
invest in being a broad-based provider of IaaS and PaaS by expanding its capabilities as well as the
size and reach of its go-to-market operations. Its operations are geographically diversified, and its
clients tend to be startups to large enterprises.
Revenue and capabilities gains: GCP had both the highest percentage of revenue gains and
improvements across Gartner’s Critical Capabilities for CIPS of any cloud provider in this market.
This is largely the result of increased field sales, co-selling with partners and a commitment to
offering a competitive platform from the perspective of capabilities.
Sales execution: GCP’s consistent enterprise focus and shift to selling to business executives
(rather than to technical teams) is having very noticeable results, in terms of both adoption and
enterprise mind share. This is in contrast to a short few years ago when most enterprises would be
unlikely to consider Google as a supplier of enterprise IT solutions.
Sovereign cloud: GCP has a more flexible partnering stance outside its core regions. It is willing to
partner with in-country operators to create sovereign cloud alternatives in key regions and to
partner with OEM providers for deployment of Google Anthos in private data center and edge
Increasing prices: Google has historically attracted clients with aggressive pricing relative to its
competition, but clients should be warned that the prices may not stay low forever. Google recently
increased prices by 100% for some aspects of its storage services, for example. While Google is
honoring existing customer commitments, this event is notable for being the first significant
increase of published pricing by a provider in this market.
Strategic confusion: Although Google maintains customer enablement programs for both its
Rapid Assessment & Migration Program (RAMP) and Cloud App Modernization Program (CAMP),
Gartner finds RAMP to be more prevalent in the market, and we rarely hear about CAMP from
clients. Further, Google publicly promotes 39 specialized RAMP partners but maintains no
equivalent public list of CAMP partners.
Financial losses: Despite its revenue gains, GCP is the only CIPS provider with significant market
share that continues to currently operate at a large financial loss. Further, GCP’s success erodes
Google’s overall healthy gross margins, and the cloud division is a minor part of the parent
company’s overall revenue.
Huawei Cloud
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Huawei Cloud is a Niche Player in this Magic Quadrant. Huawei Cloud’s operations are mostly
focused in China, though it also has meaningful efforts in Latin America and Africa. Its clients tend to
be large and midsize enterprises. Huawei Cloud has an investment focus that includes building out
its cloud services to new regions and matching the capabilities of its more direct Chinese
Market share in China: Huawei Cloud overtook Tencent Cloud to become the second largest cloud
provider in China by market share in 2021 and is now just behind Alibaba Cloud. Huawei Cloud is
also continuously exploring the global market, especially in Latin America, Southeast Asia and
Africa where it has existing customer relationships and is amenable to catering to local market
preferences such as billing in local currency.
On-premises and edge expertise: Huawei’s roots in enterprise IT are in delivering on-premises and
edge infrastructure for customers. As such, Huawei is able to deliver both public cloud and private
cloud solutions to give customers flexibility in deployment.
Enterprise pedigree: Huawei Cloud has an edge on the competition with its differentiated
enterprise pedigree and customer reach as it relates to telecom customers. This advantage,
particularly over its main competitors based in China, positions it for the advent of more telcocloud provider partnerships, which are developing around the world.
International sanctions: International sanctions have had a massive impact on Huawei’s overall
revenue, sinking by one-third and complicating Huawei Cloud’s access to markets and
components. Further, the success of Huawei Cloud’s business can be hard to gauge, at times
offering conflicting statements around financial performance of its cloud offerings.
PaaS immaturity: The majority of Huawei Cloud’s revenue outside of China comes from the sale of
IaaS. Its PaaS offerings should be considered immature until it sees greater adoption from a wider
base of Huawei Cloud’s customers.
Nascent consulting partner ecosystem: Huawei Cloud has a limited number of consulting and
channel partners, which are mostly focused on Asia. Huawei Cloud’s online marketplace of thirdparty offerings has a very limited selection, most of which are paid nonevaluation SKUs.
IBM is a Niche Player in this Magic Quadrant. IBM Cloud’s operations are geographically diversified
and mostly focused on lift-and-shift and extended enterprise use cases. Its clients tend to be large
and midsize enterprises. IBM has an investment focus that includes hybrid and distributed cloud,
quantum computing, regulated industries and industry-focused cloud services.
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Focused strategy: IBM has chosen to focus its strategy on regulated industries. For example, it
has built a distinct reference architecture and partner validation around the financial services
industry (FSI). Further, IBM has developed innovative retail solutions based upon IBM Cloud’s
confidential computing technology.
Modernization vision: IBM has a differentiated vision for modernizing enterprise workloads, such
as those that run on IBM Power systems and IBM zSystems, to derive the agility benefits of cloud.
IBM is one of the few providers with the assets and know-how to bring mainframe workloads
focused on testing and development into modern environments.
Container management: OpenShift is the dominant on-premises container management software
in the market and is offered as a fully managed service, extended to distributed cloud
environments via IBM Cloud Satellite. As such, Red Hat and OpenShift are core to IBM’s cloud
strategy and serve as the foundation for delivering IBM software on providers such as AWS and
Microsoft Azure through the jointly branded offerings.
Historic reliability: IBM had major incidents in 2021, some of which had global impact and
widespread multiservice disruption. Reliability has improved significantly in 2022, but IBM will
need to maintain these improvements and ensure continuously available critical services to retain
customer confidence.
Market responsiveness: IBM Cloud has not yet found its competitive identity when compared with
other providers in the market for CIPS. IBM is still in the process of integrating its traditional
assets (Z, Power, Db2) with newly acquired platform technologies from Red Hat into a more
cohesive “Gen2” hybrid and multicloud offering. This new IBM Cloud, while promising in vision and
scope, is not yet fully competitive with the Leaders in this Magic Quadrant.
Sovereign cloud: IBM Cloud’s sovereign cloud strategy is less comprehensive relative to some
other providers in this market. Sovereign cloud capabilities are dependent upon legal ownership
and authority within geographies as well as the physical location of infrastructure and
data/processing residency. While IBM can deliver on some of these dependencies, it lacks core
cloud capabilities demonstrated by market leaders. IBM must bolster sovereign and core
capabilities, independent of its penetration of regulated industries, to deliver success with its
sovereign strategy.
Microsoft is a Leader in this Magic Quadrant. Microsoft Azure is strong in all use cases, which
include extended cloud and edge computing. Azure is particularly well-suited for Microsoft-centric
organizations. Microsoft has an investment focus on hybrid and multicloud, and making architectural
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and security improvements to the Azure platform. Its operations are geographically diversified, and
its clients tend to be midsize and large enterprises.
Market share: Microsoft Azure continues to make year-over-year progress in closing the gap in
market share with AWS, Microsoft’s strongest competitor. With Azure’s current pace, the worldwide
gap with AWS will significantly shrink within the foreseeable future and is already happening in
Solutions-oriented: Microsoft Azure has an impressive solutions orientation with a broad range of
Microsoft cloud capabilities and complementary ecosystem partners to satisfy customer use
cases. Microsoft has an early, differentiated position in broad segments such as telecom,
healthcare, manufacturing, retail and financial services.
Hybrid and multicloud: Microsoft’s vision for this market is underpinned by a committed belief
that most enterprises will remain hybrid and multicloud, and that simplified operations and
governance are required to operate such diverse environments securely and effectively. Microsoft
is offering this through the set of technologies known as Azure Arc, which attempts to address
these needs but has nascent adoption thus far.
Security issues and lack of innovation: Despite Microsoft Azure’s market share gains, 2021 was a
relatively unremarkable year for Microsoft Azure as it relates to novel innovations in the market for
cloud infrastructure and platform services. Gartner interprets this as time largely spent by
Microsoft on the reliability and security issues Azure customers faced after a continuous stream
of incidents. Lastly, Microsoft’s competitors such as Google and Oracle are not standing still and
will likely match and even exceed Azure’s capabilities on some dimensions in time.
Opaque costs: Many Gartner clients report frustration with watching their Azure costs increase
over time without knowing why. Critical enterprise features are often only in the most premium tier.
Azure’s native cost management capabilities lag behind some competitors in maturity and
completeness, meeting only half the “required” criteria Gartner uses to evaluate cloud provider
cost management capabilities. In addition, Microsoft CSP partners are very uneven in their
knowledge of and support for cloud cost optimization practices. Lastly, the complexity of
Microsoft licensing and support costs extends to Azure: Customers find it difficult to consolidate
their spend and negotiate private discounts in a simple and predictable way.
Punitive licensing: Microsoft plans to adhere to Fair Software Licensing Principles. However,
Microsoft is using licensing for its products, such as Windows and SQL Server, punitively against
competitive cloud providers by making it more expensive to deploy Windows workloads anywhere
other than Azure. There are also restrictions with the use of Microsoft licensing on Azure itself that
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are often not communicated to customers. For example, customers are not told about restrictive
rules under Azure Hybrid Use Benefits in Azure multitenant environments.
Oracle was a Niche Player in last year’s Magic Quadrant and is now a Visionary. Oracle Cloud
Infrastructure (OCI) is mainly focused on lift and shift, hybrid and multicloud, and HPC, though OCI
endeavors to have broad capabilities outside of Oracle-focused applications. Oracle has a future
focus on offering sovereign cloud capabilities (largely outside of North America) and multicloud
offerings on Azure and AWS.
Business model innovation: Oracle is out-innovating the market with respect to emerging
enterprise needs such as sovereign clouds. This is particularly valuable to customers in countries
with stringent regulatory and data privacy requirements as mandated by law. Allowing third parties
to private label OCI and operate completely isolated regions is highly differentiated in the market
for CIPS. This also helps promote the sovereign cloud needs in regions such as Europe and the
Middle East.
Multicloud architectures: Oracle is building compelling multicloud offerings leveraging its heritage
in mission-critical database and data warehousing technology. Multicloud architectures, where
one workload spans multiple cloud providers, are central to OCI’s vision and its future offerings
that live within and alongside providers such as AWS and Azure. These approaches to deploying
and operating workloads in the cloud are unique critical capabilities for providers in this market.
Market responsiveness: Oracle continues an impressive year-over-year pace of feature velocity
that brings it closer to the market leaders in terms of hyperscale cloud capabilities. If the pace
continues, Oracle will meet or exceed some of the providers in the Leaders quadrant in terms of
capabilities within the foreseeable future.
Brand reputation: Oracle has negative brand association for many organizations, which was
caused by years of tough compliance enforcement and inconsistent sales and support. As a
result, many enterprises resist the thought of using Oracle technologies any more than is
absolutely necessary. It is for this reason that most of OCI’s success stems from top-down
directives rather than bottom-up eagerness to use Oracle’s platform. Private labeling OCI may just
delay the inevitable, unsavory discovery by the prospective customer that Oracle is inside.
Non-Oracle, midmarket, small and midsize business (SMB): OCI’s sales efforts and partner
network are not suited to adequately address the non-Oracle workload market, and clients do not
consider Oracle to be a general-purpose solution for all enterprise workloads. Further, OCI is not
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positioned for adoption by midmarket enterprises and SMBs. OCI is a product aimed at large
enterprises with established IT expertise.
MSP and partner ecosystem: OCI has an immature ecosystem and limited commitment from
MSPs, and global systems integrators that are often forced to compete with Oracle services. This
leads GSIs to view Oracle services as competitive rather than complementary to its own services,
which has resulted in less support for Oracle Cloud among cloud integrators compared with
competing cloud platforms. Further, the number of apps in OCI’s marketplace is significantly lower
than those possessed by the Leaders in this Magic Quadrant.
Tencent Cloud
Tencent Cloud is a Niche Player in this Magic Quadrant. Tencent Cloud is mainly focused on serving
multinationals in China or Chinese multinationals expanding overseas. Tencent is investing in
network capabilities to support the low latencies required for gaming workloads along with low-code
platforms, video on demand, security, database and virtual video meeting services.
High-touch service: Tencent Cloud combines a portfolio of IaaS services optimized for highperformance networking and scale-out application architecture, combined with a pricing and a
support model that are customized for strategic high-value customers. This can make Tencent
attractive to customers with specific workload requirements that map well to Tencent’s
capabilities and that are looking for an in-depth relationship.
Pricing incentives: Tencent Cloud offers a zero commitment free trial of all services, with flexible
private pricing with rapid decision making on exceptions and discounts for larger customers.
Gaming customers are eligible to receive special incentives for use of gaming platform services in
selected regions.
Consumer internet and low code: For customers particularly focused on consumer internet in
China, Tencent Cloud is willing to leverage its parent company’s larger ecosystem of investment
partnerships to offer large customers more benefits and opportunities. Further, Tencent Cloud has
built a compelling cloud-native coding platform to enable enterprises to penetrate digital markets
more effectively through Tencent’s highly used social media platforms.
Commitment to enterprises: Upheaval among Chinese cloud providers has significantly impacted
Tencent Cloud. This leads Gartner to question Tencent Cloud’s commitment to serve largeenterprise customers with general-purpose IT workloads over the long term rather than returning
to focus solely on workloads such as gaming. In particular, Tencent Cloud executives recently
noted a shift in strategy to focus on higher-margin platform services including video on demand,
security, database and collaboration based on its VooV Meeting software.
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Scant ecosystem: Tencent Cloud’s partner programs are scant in depth and breadth. Tencent
Cloud has a limited number of partner successes, and its third-party marketplace is quite minimal
with fewer than 60 products, mostly from a handful of vendors, none of whom are category
leaders in the worldwide software markets. Lastly, customers outside of China will find it
especially difficult to find partners to work with Tencent Cloud.
Modest market share and innovation gains: Tencent Cloud had very modest year-over-year gains
in market share and a rather uneventful year in terms of novel innovations in the market for CIPS.
These factors placed it near the bottom of all providers in this Magic Quadrant.
Vendors Added and Dropped
We review and adjust our inclusion criteria for Magic Quadrants as markets change. As a result of
these adjustments, the mix of vendors in any Magic Quadrant may change over time. A vendor’s
appearance in a Magic Quadrant one year and not the next does not necessarily indicate that we
have changed our opinion of that vendor. It may be a reflection of a change in the market and,
therefore, changed evaluation criteria, or of a change of focus by that vendor.
Huawei Cloud was added to this year’s Magic Quadrant.
No vendors were dropped.
Inclusion and Exclusion Criteria
For Gartner clients, Magic Quadrant and Critical Capabilities research identifies and then analyses
the most relevant providers and their products in a market. Gartner uses by default an upper limit of
20 providers to support the identification of the most relevant providers in a market. On some
occasions, the upper limit may be extended by Gartner Methodologies where the intended research
value to our clients might otherwise be diminished. The inclusion criteria represent the specific
attributes that analysts believe are necessary for inclusion in this research.
To qualify for inclusion, cloud providers need the following.
Market participation. They must sell public cloud IaaS as a stand-alone service, without the
requirement to use any managed services (including guest OS management), or to bundle it with
managed hosting, application development, application maintenance, or other forms of outsourcing.
They may, optionally, also sell a private or hybrid offering that uses the same architecture but is
Market traction and momentum. They must have ISO 27001-audited (or equivalent) data centers on
at least three continents. They must have at least one public cloud IaaS offering that meets the
following criteria:
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If the offering has been generally available for more than three years: A minimum of $1 billion in
2021 public cloud IaaS/dbPaaS revenue (excluding partner operated and/or
distributed/hybrid/private cloud infrastructure deployed outside of a cloud provider’s data centers),
excluding all managed and professional services. Additionally, $250 million of the public cloud
IaaS/dbPaaS contract revenue must come from outside of the country where greater than 50% of
data centers are located.
For the sake of clarity, revenue qualification is based upon the combination of the following:
Compute (VMs, bare metal, container services in the public cloud)
Storage (block, file and object storage in the public cloud)
Networking (software-defined networking that underpins operation of public cloud resources)
Database PaaS (fully managed database services in the public cloud)
If the offering has been generally available for less than three years: A minimum of $500 million in
public cloud IaaS/dbPaaS in revenue during 2021, excluding all managed and professional services,
as well as a growth rate of at least 50% exiting 2021.
Business capabilities relevant to Gartner clients. They must offer public cloud IaaS services globally
(they must be purchasable outside their home region), be able to invoice, offer consolidated billing,
and be willing to negotiate customized contracts. They must have 24/7 customer support (including
phone support). There must be an option for English-language localization of the contract, service
portal, documentation and support.
Technical capabilities relevant to Gartner clients. They must have public cloud IaaS and PaaS
services that are suitable for supporting mission-critical, large-scale production workloads, whether
enterprise or cloud-native. Specific generally available, first-party service features must include:
Software-defined compute, storage and networking, with access to a web services API for these
Cloud software infrastructure services facilitating automated management, including at a
minimum, monitoring and autoscaling
A managed database PaaS offering
A managed FaaS offering with integrated HTTP API gateway platform whose underlying
infrastructure is not exposed to the user
Company developed, publicly available SDKs in three or more programming languages
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A distributed, continuously available control plane supporting a hyperscale architecture
Managed CI/CD offerings to support the complete application life cycle including automated build
and deployments
A distributed cloud offering as defined by Gartner (see ‘Distributed Cloud’ Fixes What ‘Hybrid
Cloud’ Breaks)
Real-time provisioning for compute instances (small Linux VM in five minutes, 1,000 Linux VMs in
one hour) and a container service that can provision Docker containers in seconds
An allowable VM size of at least 16 vCPUs and 128 GB of RAM
A service-level agreement for compute, with a minimum of 99.9% availability
The ability to securely extend the customer’s data center network into the cloud environment
The ability to support multiple users and API keys, with role-based access control
Evaluation Criteria
Ability to Execute
Table 1: Ability to Execute Evaluation Criteria
Evaluation Criteria
Product or Service
Overall Viability
Sales Execution/Pricing
Market Responsiveness/Record
Marketing Execution
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Evaluation Criteria
Customer Experience
Source: Gartner (October 2022)
Completeness of Vision
Table 2: Completeness of Vision Evaluation Criteria
Evaluation Criteria
Market Understanding
Marketing Strategy
Sales Strategy
Offering (Product) Strategy
Business Model
Vertical/Industry Strategy
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Evaluation Criteria
Geographic Strategy
Source: Gartner (October 2022)
Quadrant Descriptions
Leaders distinguish themselves by offering a service suitable for strategic adoption and having an
ambitious roadmap. They can serve a broad range of use cases, although they do not excel in all
areas, may not necessarily be the best providers for a specific need and may not serve some use
cases at all. Leaders in this market have appreciable market share and many referenceable
Challengers are well-positioned to serve some current market needs. They deliver a good service that
is targeted at a particular set of use cases, and they have a track record of successful delivery.
However, they are not adapting to market challenges sufficiently quickly or do not have a broad
scope of ambition.
Visionaries have an ambitious vision of the future and are making significant investments in the
development of unique technologies. Their services are still emerging, and they have many
capabilities in development that are not yet generally available. Although they may have many
customers, they might not yet serve a broad range of use cases well or may have a limited
geographic scope.
Niche Players
The Niche Players in the market for CIPS may be excellent providers for particular use cases or in
regions in which they operate, but they should ultimately be viewed as specialist providers. They
often do not serve a broad range of use cases well or have a broadly ambitious roadmap. Some may
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have solid leadership positions in markets adjacent to this market, but have developed only limited
CIPS capabilities.
There are no providers in the CIPS market that do not require enterprises to accept significant tradeoffs that may fall into technical or business downsides. The track record of cloud providers in terms
of resiliency and security varies widely by provider. Major outages have continued to plague several
cloud providers in this Magic Quadrant over the past year. In some cases, providers offered scant
transparency and mitigation measures to work around provider-oriented failure. Further complicating
matters is the impact on enterprises when a cloud provider has substantial, systemic dependencies
on third parties that it does not control.
The nature of competitive providers beholden to public stock market investors eventually forces the
providers to use aggressive measures to meet sales objectives because it’s faster than attempting to
win hearts and minds.
Ultimately, enterprises considering meaningful use of hyperscale cloud providers need to prioritize
against the trade-offs of each provider and then develop subsequent strategies for mitigating the
Market Overview
The market for CIPS is changing in significant ways that have long-lasting ramifications to the future
of enterprise IT. The hyperscale cloud providers are in a race to colonize enterprises in an attempt to
become the primary strategic supplier of cloud services to address a broad range of IT workloads.
The efforts to colonize enterprises are at odds with most enterprise prerogatives to “be multicloud”
with respect to sourcing strategies. Further complicating matters is that the “best of breed” approach
historically used on-premises is treacherous in the cloud, given the dissimilarity in identity systems,
resilience characteristics, network latency and general apprehension by the leading providers to work
together in the interest of customers. Ultimately, multicloud architectures are still only suitable for
the most sophisticated customers who can deal with the myriad challenges that await.
Once enterprises are in the dominion of a cloud provider, it is unlikely that the cloud provider remains
benevolent for very long. The ultimate goal of the cloud providers is to move enterprises further up
into the PaaS layer where the margins are higher and the ability to extricate workloads and processes
become more difficult. But traditional workloads such as those focused on ERP become difficult to
move as well due to their mission-critical nature.
The negative consequences of being in the dominion of a cloud provider are already beginning to
surface. Gartner client inquiry across a broad array of worldwide regions reveals unscrupulous
behavior on the part of the cloud provider once enterprises are fully locked-in.
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Some cloud providers use strong-arm tactics to force enterprises into agreeing to increasingly higher
committed spend levels. Others use software licensing from an entrenched base of operating system
and relational database management system utilization to direct more cloud usage to their
respective offerings.
Early indications are that some enterprises are fiercely resisting and are making significant plans for
IT supplier diversification as a result. But the complexity and overhead of managing multiple cloud
providers, combined with lower discounts due to lower provider commitments, often result in a
multicloud strategy increasing TCO, rather than lowering it as desired.
The market for cloud infrastructure and platform service is in play again.
Evaluation Criteria Definitions
Ability to Execute
Product/Service: Core goods and services offered by the vendor for the defined market. This
includes current product/service capabilities, quality, feature sets, skills and so on, whether offered
natively or through OEM agreements/partnerships as defined in the market definition and detailed in
the subcriteria.
Overall Viability: Viability includes an assessment of the overall organization’s financial health, the
financial and practical success of the business unit, and the likelihood that the individual business
unit will continue investing in the product, will continue offering the product and will advance the
state of the art within the organization’s portfolio of products.
Sales Execution/Pricing: The vendor’s capabilities in all presales activities and the structure that
supports them. This includes deal management, pricing and negotiation, presales support, and the
overall effectiveness of the sales channel.
Market Responsiveness/Record: Ability to respond, change direction, be flexible and achieve
competitive success as opportunities develop, competitors act, customer needs evolve and market
dynamics change. This criterion also considers the vendor’s history of responsiveness.
Marketing Execution: The clarity, quality, creativity and efficacy of programs designed to deliver the
organization’s message to influence the market, promote the brand and business, increase
awareness of the products, and establish a positive identification with the product/brand and
organization in the minds of buyers. This “mind share” can be driven by a combination of publicity,
promotional initiatives, thought leadership, word of mouth and sales activities.
Customer Experience: Relationships, products and services/programs that enable clients to be
successful with the products evaluated. Specifically, this includes the ways customers receive
technical support or account support. This can also include ancillary tools, customer support
programs (and the quality thereof), availability of user groups, service-level agreements and so on.
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Operations: The ability of the organization to meet its goals and commitments. Factors include the
quality of the organizational structure, including skills, experiences, programs, systems and other
vehicles that enable the organization to operate effectively and efficiently on an ongoing basis.
Completeness of Vision
Market Understanding: Ability of the vendor to understand buyers’ wants and needs and to translate
those into products and services. Vendors that show the highest degree of vision listen to and
understand buyers’ wants and needs, and can shape or enhance those with their added vision.
Marketing Strategy: A clear, differentiated set of messages consistently communicated throughout
the organization and externalized through the website, advertising, customer programs and
positioning statements.
Sales Strategy: The strategy for selling products that uses the appropriate network of direct and
indirect sales, marketing, service, and communication affiliates that extend the scope and depth of
market reach, skills, expertise, technologies, services and the customer base.
Offering (Product) Strategy: The vendor’s approach to product development and delivery that
emphasizes differentiation, functionality, methodology and feature sets as they map to current and
future requirements.
Business Model: The soundness and logic of the vendor’s underlying business proposition.
Vertical/Industry Strategy: The vendor’s strategy to direct resources, skills and offerings to meet the
specific needs of individual market segments, including vertical markets.
Innovation: Direct, related, complementary and synergistic layouts of resources, expertise or capital
for investment, consolidation, defensive or pre-emptive purposes.
Geographic Strategy: The vendor’s strategy to direct resources, skills and offerings to meet the
specific needs of geographies outside the “home” or native geography, either directly or through
partners, channels and subsidiaries as appropriate for that geography and market.
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