Greater Choice and value for advanced analytics and AI

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However, most organizations are stuck in experimentation in silos. Industrializing AI

throughout the enterprise is not easy. There are many deployment challenges associated with

data, talent and trust especially as data volume, velocity and variety continue to explode.

To amplify the value of AI and make it pervasive, it is imperative that clients consider best

practices and solutions that address these challenges holistically across several dimensions:

Business, Process, Applications, Data and Infrastructure. Doing so provides clients

extensive choice and flexibility to maximize the Total Value (Benefits – Costs) of Ownership

(TVO) from their investments. This is the goal of the IBM + Cloudera strategic alliance.

are deeply committed to open source and hybrid multi-cloud technologies to provide this IA.

Without being prescriptive, this paper provides an overview of the rich and extensive

portfolio of IBM and Cloudera products and services. Clients have complete flexibility to

choose and customize their specific Analytics/AI solutions including selecting individual

components. Anchored on an open framework that supports on-premises and multi-cloud

deployments, this portfolio provides clients a valuable array of business, process,

applications, data and infrastructure capabilities with unprecedented flexibility and choice to

maximize the TVO of their Analytics/AI investments.

industrialize Analytics/AI with greater choice and value.

Copyright

®

2019. Cabot Partners Group. Inc. All rights reserved. Other companies’ product names, trademarks, or service marks are used herein for identification only and belong to their

respective owner. All images and supporting data were obtained from IBM /Cloudera or from public sources. The information and product recommendations made by the Cabot Partners

Group are based upon public information and sources and may also include personal opinions of both Cabot Partners Group and others, all of which we believe to be accurate and reliable.

However, as market conditions change and not within our control, the information and recommendations are made without warranty of any kind. The Cabot Partners Group, Inc. assumes

no responsibility or liability for any damages whatsoever (including incidental, consequential or otherwise), caused by your or your client’s use of, or reliance upon, the information and

recommendations presented herein, nor for any inadvertent errors which may appear in this document. This paper was developed with Lenovo funding. Although the paper may utilize

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Analytics, Artificial Intelligence (AI) and Machine Learning (ML) are profoundly

transforming how businesses and governments engage with consumers and citizens. Across

many industries, high value transformative use cases in personalized medicine, predictive

maintenance, fraud detection, cybersecurity and more (Figure 1) are rapidly emerging. In

fact, AI/ML adoption alone has grown an astounding 270% in the last four years and 40% of

organizations expect it to be a game changer.

The economic impact of AI/ML is immense.

However, for Analytics, AI and ML to become a crucial integral part of an organization,

numerous challenges must be overcome. In fact, 77% of respondents in another recent

survey

say that “business adoption” of big data and AI initiatives continues to be a

challenge and only 31% have a data-driven organization, fewer (28%) have a data culture.

To amplify the value of AI and make it pervasive, it is imperative that clients consider best

practices and solutions that address these challenges holistically across several dimensions:

Business, Process, Applications, Data and Infrastructure. Doing so will enable clients to

maximize their Total Value of Ownership (TVO) from their investments. This is the goal of

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