Data & Enterprise Intelligence

The Market Challenge

Enterprises are faced with two seemingly conflicting drivers: meeting regulatory demands for the tight control of information, and the business pull to liberate that same information for use in value-adding analytics. However, these objectives need not be at odds. Comprehensive control of data has downstream benefits for the entire enterprise, delivering both analytics-led business value and compliance.

It is not just a technology problem, culture is at the heart of the issue as well. As the enterprise looks towards digital transformation and the implementation of new technologies like artificial intelligence, the culture of the enterprise will need to be receptive before business value can be realized. By managing data at the source, whether on-premises or in the cloud, business drivers can be aligned and data leveraged equally both reactively and proactively.

How Ovum Helps You

Explore and understand how compliance can be a driver to business value not just a matter of ticking boxes.

Learn best practices for building a data-driven enterprise culture that does not compromise governance.

Marshal the march to the cloud with a multi-cloud approach to delivering data and analytics.

Evaluate emerging data science & artificial intelligence technologies that can augment and improve everyday business processes.

Understand why mobility is a vital digital transformation pillar and how it can be exploited in modernizing legacy systems and optimizing business processes.

“Cloud BI & analytics software spend across industry verticals will hit $7.1bn by 2021″

Key Deliverables

Protecting information for business value – best practices and hands-on advice for effective protection of information to help achieve compliance and business value

Cloud platforms for data and analytics – market landscapes and vendor assessments of key cloud data and analytics solutions to successfully navigate the transition to the cloud

Data science and AI – practical thought leadership tackling the challenge of new AI-powered capabilities and data science, their adoption and finding enterprise value

Building the digital workspace – frameworks and blueprints for building the data-driven digital workspace

Themes for 2018

Compliance as a source of competitive advantage
Compliance has traditionally been approached in a reactive manner, missing the business benefits that compliance can achieve. Most regulatory imperatives, such as the EU’s GDPR, are about driving better enterprise control and accountability for data. Compliance and information management technology are intertwined, tools like metadata management, NLP, machine learning, cataloging, and data masking/protection are all critical to making sense of an enterprise’s data. Compliance goals, when closely integrated with business strategy, can amplify analytics outcomes and drive profitability.


Defining a viable multi-cloud strategy for data management and analytics
As enterprises move business-critical workloads and the data that powers them to the cloud, they will be making de facto platform decisions. They are facing a repeat of the same generational platform migrations decisions that enterprises faced when they conducted their “open systems” migrations. This strongly influences data management & analytics because, increasingly, analytics are being pushed into the data tier. The goal should be implementing viable multi-cloud strategies that maximize the benefits of data and analytics in, and out of the cloud, while minimizing the risk of cloud platform lock-in and creating new data silos.


Using AI and data science to accelerate digital transformation
The future of AI – and the data science that is its foundation – in the enterprise is a story of integration and orchestration across enterprise applications. Digital transformations have begun, powered by the transition to cloud and a proliferation of connections: from and between consumer to business to device or application. These connections generate reams of data – consuming, analyzing and acting upon such vast and fast-moving data is beyond human capability. Integrating AI into enterprises’ applications will tackle this opportunity through automation. For those who can orchestrate multiple AI, a benefit greater than the sum of its component parts is waiting.


Fostering a strong data culture for effective enterprise analytics
Enterprises must establish and nurture a strong data culture to harness and profit from the wealth of data, and the myriad tools to access and analyze it. Data management technology and governance frameworks are required to mitigate risk, and successfully integrate data-driven decision making into enterprises’ everyday business – freeing users to seek and find value without compromising corporate or compliance standards. Data initiatives – whether technology, people or process related – demand sponsorship at the C-level, helping foster a sense of business ownership of data. The tools for non-expert users to source and explore data are here, enterprises must now make what they can achieve part of their culture.

What’s New

Track the transition to the cloud – with new cloud market forecasts covering data & content management, BI, analytics and big data

New topic packs of research covering key enterprise challenges – including GDPR and Artificial Intelligence

Understand enterprise investment plans for cloud deployments – in Information Management with an expanded ICT Enterprrise Insights survey


Managing security, identity, and privacy is the number one IT trend across all enterprises in Ovum’s ICT Enterprise Insights survey 2016/17

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