Becoming Information-Driven Begins with Pragmatic AI

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Written by guest blogger, David Schubmehl, IDC Research Director, Cognitive/Artificial

Intelligence Systems.  Sponsored by Sinequa.

Over the last several years, I’ve spoken to many organizations that have all asked the same question: How can we most effectively make use of all of the research, documents, email, customer records and other information that our employees have collected over the years, especially those that are now retiring? In the past, organizations had corporate libraries and corporate librarians whose job it was to help collect, organize, and disseminate information to employees and staff when and where they needed it. That department and positions are long gone from most organizations today. Why have they gone? The rate of data and documents (including research papers, contracts, and even emails) has exploded, making this task impossible. But let’s be honest: even before today’s information explosion, no classification system could ever keep up with the fast pace of change in the economy. No one could have foreseen today’s most important questions, in content categories that did not exist until today. And with the baby boomers retiring at an ever-increasing rate, an urgent question must be asked: How do organizations get the most value from the vast amounts of information and knowledge that they’ve accumulated over decades?

IDC has identified the characteristics of organizations that are able to extract more value out of the information and the data available to them. Leader organizations make use of information access and analysis technologies to facilitate information access, retrieval, location, discovery, and sharing among their employees and other stakeholders. These insight leaders are characterized by:

  • Strategic use of information extracted from both content and data assets
  • Efficient access to unified and efficient access to information
  • Effective query capabilities (including dashboards)
  • Effective sharing and reuse of information among employees and other stakeholders
  • Access to subject matter experts and to the accumulated expertise of the organization
  • Effective leverage of relationships between information from different content and data sources

So how can artificial intelligence (AI) and machine learning affect information access and retrieval? The types of questions that are best answered by AI-enabled information access and retrieval tools are those that require input from many different data sources and often aren’t simple yes/no answers. In many cases, these types of questions rely on semantic reasoning where AI makes connections across an aggregated corpus of data and uses reasoning strategies to surface insights about entities and relationships. This is often done by building a broad-based searchable information index covering structured, unstructured, and semi-structured data across a range of topics (commonly called a knowledge base) and then using a knowledge graph that supports the AI based reasoning.

AI-enabled search systems facilitate the discovery, use, and informed collaboration during analysis and decision making. These technologies use information curation, machine learning, information retrieval, knowledge graphs, relevancy training, anomaly detection, and numerous other components to help workers answer questions, predict future events, surface unseen relationships and trends, provide recommendations, and take actions to fix issues.

Content analytics, natural language processing, and entity and relationship extraction are key components in dealing with enterprise information. According to IDC’s Global DataSphere model developed in 2018, of the 29 ZB of data creation, 88% is unstructured content that needs the aforementioned technologies to understand and extract the value from it. In addition, most of this content is stored in dozens, if not hundreds of individual silos, so repository connectors and content aggregation capabilities are also highly desired.

AI and machine learning provide actionable insights and can enable intelligent automation and decision making. Key technology and process considerations include:

  • Gleaning insights from unstructured data and helping to “connect the dots” between previously unrelated data points
  • Presenting actionable information in context to surface insights, inform decisions, and elevate productivity with an easy-to-use application
  • Utilizing information handling technologies that can be used in large scale deployments in complex, heterogeneous, and data-sensitive environments
  • Enriching content automatically and at scale
  • Improving relevancy continuously over time, based on user actions driven by machine learning
  • Improving understanding by intelligently analyzing unstructured content

IDC believes that the future for AI-based information access and retrieval systems is very bright, because the use of AI and machine learning coupled with next-generation content analysis technologies enable search systems to empower knowledge workers with the right information at the right time.

The bottom line is this: enabled by machine learning–based automation, there will be a massive change in the way data and content is managed and analyzed to provide advisory services and support or automate decision making across the enterprise. Using information-driven technologies and processes, the scope of knowledge work, advisory services, and decisions that will benefit from automation will expand exponentially based on intelligent AI-driven systems like those that Sinequa is offering.

For more information on using AI to be an information leader, I invite you to read the IDC Infographic, Become Information Driven, sponsored by Sinequa at https://www.sinequa.com/become-information-driven-sinequa/

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Big Projects on Track: Achieving the Goals of Long, Complex Projects

big-track-manufacturing-06-2019-1024Big projects, well executed, are the lifeblood of large, distributed manufacturing organizations.

Such projects solve existing and future problems that enable the organization and its stakeholders (and sometimes all of society) to move forward economically. These projects are naturally chaotic and require significant organization and planning to manage the chaos. Successfully executing these projects also means bringing together the right people and making it easy for them to collaborate, share ideas and provide inspiration.Today’s large, distributed manufacturing organizations cannot successfully plan and execute big projects without intelligent automation to help connect project stakeholders to relevant information and to each other.

Download the Big Projects On Track solution white paper to learn how one of the largest rolling stock manufacturers in the world addressed this challenge.

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Accelerating GDPR Compliance with an Information-Driven Approach

With GDPR in full effect, Ovum has published a new white paper featuring Sinequa and outlining how cognitive search can be a compliance accelerator.  The full white paper can be found at http://go.sinequa.com/white-paper-gdpr-ovum-2018.html.

ovum-gdprThe white paper, written by Ovum senior analyst Paige Bartley, outlines the challenges of aligning existing business objectives with GDPR compliance and how companies can accelerate GDPR compliance with an information-driven approach.

There is a new precedent with GDPR for enterprise control of data of all kinds, both structured and unstructured. Gaining better control of data is a deceptively simple concept, but requires numerous capabilities, such as the ability to search for data across silos and granularly manage who has access to what. Sophisticated search and analytics capabilities, spanning organizational silos, are key to both facilitating compliance and driving informational value.

According to the white paper: “GDPR compliance requirements should not be thought of as an antithetical force against enterprise initiatives to leverage and analyze data. The more the enterprise can align its compliance obligations with existing business objectives – such as the demand to provide excellent customer service via a 360° understanding of customer desires – the more it can benefit from the perceived ‘burden’ of GDPR compliance. Enterprise-wide search is central to these capabilities and will help the enterprise gain a centralized view of subjects and topics in the increasingly distributed IT ecosystem.”

As an example of this concept, the white paper highlights Sinequa’s platform deployment at Stibbe, a global, full-service law firm with an internationally oriented commercial practice. Stibbe implemented Sinequa’s Cognitive Search & Analytics Platform to provide secure, unified access to millions of documents and legal matters. The result was a holistic view of the firm’s informational landscape, with the ability to quickly retrieve all material related to individual topics, cases or clients.

This Ovum white paper gets at the heart of Sinequa’s approach to GDPR and data analytics. By taking control of data and unleashing it as a strategic tool, organizations can become information-driven in a way that meets compliance requirements while accelerating innovation and creating a key competitive advantage.

The full white paper can be found at http://go.sinequa.com/white-paper-gdpr-ovum-2018.html

 

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Best Practices for Intelligent Search

This article originally appeared as part of a KMWorld Best Practices White Paper on Intelligent Search

Best Practices for Intelligent Search

Sinequa provides an intelligent search platform that enables organizations to become information-driven, which means having actionable information presented in context to surface insights, inform decisions, and elevate productivity, consistently and reliably. Our platform consists of packaged technology that allows this to happen quickly and without sacrificing context or quality as typically happens with “lossy” approaches involving data migration.  (more…)

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3 Ways to Use Data to Fight Terrorism and Money Laundering

This article was originally published on Nextgov.

nextgovCognitive search and analytics technologies are all about accessing the right information at the right time.

The increased severity of domestic security breaches due to terrorist threats and cyber crime poses a strategic challenge for federal and state security services. The strengthening of human resources, now widely deployed around the world, is not enough to meet the challenge alone. Increasing efficiency and speed, controlling the means of communication used by terrorists, but also, and above all, anticipating the lead-up to such actions, are all challenges that persist. (more…)

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