What are intelligent insights?

In a time when information is the new commodity, it is crucial for businesses to proactively maximize value from all data—structured and unstructured. Yet for…

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Virgil Dodson

August 9, 20235 minutes read

Close-up of a person's fingers holding onto a small wooden block to complete a pyramid of blocks to show how intelligent insights build foundations

In a time when information is the new commodity, it is crucial for businesses to proactively maximize value from all data—structured and unstructured. Yet for many companies, content remains more of a burden than a blessing, plagued by too much data, not the right data, poor data quality or data without context. Without the ability to turn data into intelligent insights and real-time intelligence, your organization’s data is not able to live up to its potential, unable to automate repetitive tasks, predict trends or uncover ways to streamline operations.


To help you turn information into insights, let’s define the role of business intelligence and the importance of analytics, dashboards and content analytics as key business insights essentials.  


What are business insights and intelligence?

According to Gartner®, massive amounts of unused content combined with increasingly complex decisions within organizations has led to a content chasm for decision makers.[1]

This is due in part to the free-form, complex and ambiguous nature of unstructured data. Unlike structured data, such as numbers, tables, rows and columns, which has a specific framework, unstructured data has no defined format, making it tough for traditional databases and data visualization tools to make use of the information.

Yet deriving value from unstructured data is essential, as effective decision-making depends on timely and actionable information, presented clearly and in context. Business intelligence is the organization and analysis of information, delivered in an easily digestible, user-friendly way to enable more informed decisions.

To surface value from unstructured data, the data must first be aggregated across multiple sources and then artificial intelligence (AI) techniques, such as natural language processing (NLP) and machine learning, turn data into business insights for operational users. For example, in the pharmaceutical industry, embedded analytics can provide decision-makers with an analytics dashboard to provide a clear picture of the drug approval process, identifying regulatory roadblocks for fast action.

Why do we need data intelligence for our business?

Gartner also highlights that existing approaches to decision making have been unable to adapt in time to address global uncertainties, leading to three (less than desirable) outcomes, including: 1) an abundance of uncontrolled decision risks that lead to inaccurate, ineffective or inconsistent decisions; 2) a negative impact on business outcomes, such as poor customer sentiment or health and safety violations and 3) missed business opportunities for providing better decision support.[2]

The complexity of business decisions are driving organizations to better use data and analytics to maximize the value of business intelligence in unstructured content and improve the quality of decisions. Having technology for data discovery and data analysis delivers several important benefits to the business, including:  

  • Improve visibility: Business users can delve deep into massive amounts of data with self-services business insights powered by advanced AI.
  • Better support a global workforce: Remote users can securely access the insights they need from any device embedded within their applications.
  • Mitigate risk: Leverage machine learning to find and remediate high-risk content, such as harmful, sensitive and inappropriate text, images, video and audio files within organizational content.
  • Work better together: Empower IT teams, operational users and business analysts to share insights and findings, make more informed decisions and act with more impact.
  • Operationalize actionable insights: Eliminate the need for business users to rely on analytics developers and data scientists, making business insights accessible, easy to use, visual and shareable across functions.

What’s the role of dashboards in business intelligence?

Employees can perceive relationships, patterns and trends much faster through images than words and numbers, creating a need to help users visualize insights in a way that makes sense for their tasks at hand.

A content analytics platform implementing artificial intelligence technology allows enterprise users to transform big data into self-service visualizations, including interactive dashboards and reports. This allows business users to get valuable business insights without waiting on already strapped IT resources, in essence, delivering business intelligence to the masses.

When business intelligence tools aggregate multiple data sources and views into a unified, interactive experience, the results are powerful, allowing users to explore data and pull relevant information into graphical snapshots, benefitting from:  

  • Personalized dashboards, such as operational, strategic or tactical, with agile, on-the-fly analysis  
  • Easy interaction with users able to change views, drill down into data and zoom into graphics, charts and tables
  • Mix and match options, blending charts, crosstabs, tables, map and data visualizations and other analytic content and services
  • Broad sharing and consumption for department-level and organization-wide monitoring and input

What makes a good content analytics tool?

Building an effective content analytics system typically requires high-powered data science talent—a scare resource. Similarly, assembling the components of a cognitive analytics platform from disparate proprietary technologies is costly and complicated, and limits customization options.

When assessing tools, look for three must-have features:

  1. An open foundation that can be easily customized
  2. The ability to scan disparate forms of data to deliver AI-enabled insights
  3. Fast, self-service analytics that anyone can use

With a single, ready-to-go AI-powered analytics platform, which includes machine learning, data discovery, text analytics and visualization and dashboarding, businesses gain the power of business intelligence at their fingertips.

Are you ready to reshape enterprise decision-making by gaining more value and insight from your data? Learn how to master intelligent insights with OpenText.


[1] Gartner®, Use Multistructured Analytics for Complex Business Decisions, David Pidsley, 10 November 2022.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

[2] Ibid.

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Virgil Dodson

Virgil Dodson is a marketing director for the OpenText Magellan Analytics and AI products. Virgil is a developer at heart who enjoys solving problems with IoT, big data, AI and machine learning. In his spare time, he enjoys Rubik’s cubes, solving puzzles, collecting coins, and taking pictures. Lately, he has spent time understanding how Magellan integrates with other OpenText products to help expose Analytics and AI to every business application.

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