New Magellan suites offer easy onramps to AI

Start small and build up to full machine learning-powered solutions

By now, the benefits of adding AI and machine learning (ML) to your digital business processes have been well-demonstrated, yet many organizations are still hesitant about moving towards AI. You know your organization would flourish. You know that more current, accurate, easily readable and sharable insights and predictions would add value. And you know that you organization has vast amounts of information generated inside and outside your walls that can be invaluable. And you’ve heard that AI-enhanced analytics applications can, somehow or other, sift through all that information to deliver the insights you need.

But selecting and setting up an AI solution can be overwhelming. It can feel like there is just too much complexity to navigate, which would require more data science expertise than you have on staff.  Or perhaps you’re only interested in AI to address one specific need and not sure you need a full-sized enterprise solution.

Content first or data first? Either way, our suites offer a hand with AI

OpenText™ understands that AI is a journey, and some customers are still working up to full-fledged AI implementations. That’s why we’re rolling out pre-configured suites that combine various modules of OpenText™ Magellan™, our flagship AI-enhanced analytics platform, in convenient packages designed to address common business issues, make deployment easier, and speed time-to-value. (Think of them as “meal kits” à la Blue Apron, where the shopping and much of the preparation are taken care of for you.)

Moreover, we’ve arranged these new Magellan suites into well-marked upgrade paths that offer customers entry points at every step along the way, from simple (our classic analytics applications) to a complete platform of AI and machine learning modules offering sophisticated analytics for even the largest data arrays. They’re available today, so read on for details.

These solution suites fall into two tracks, reflecting customers’ typical paths on the analytics and AI journey:

  1. Content analytics: Typical users in this track have a lot of unstructured, textual data (written reports, PDFs and scanned document images, social media streams, customer support chats, and the like). Their pain point is to create more structure around all this data for easier search, re-use, analysis, or removal – often by adding metadata. Eventually, they may want to streamline and automate their current manual processes for handling content, such as adjudicating insurance claims, so as to make faster, better decisions.  And that’s where adding AI and machine learning can help.
  2. Data analytics: These users have large quantities of structured data (e.g. the kinds of numbers and labels that fit into databases). Their initial need is simply to make sense of it through basic analytics, delivered via dashboards, reports, and alerts. Then, to make fuller use of all this information (for example, for asset performance optimization), they may want to apply AI in order to perform sophisticated predictive analytics. Ultimately, they may want to fold in analysis of their unstructured, textual data for a 360-degree view of their operations.

Before we start explaining the exact contents of each solution set, a quick note:

Many of their basic components are the same solutions we’ve proudly offered for years. But to more accurately reflect the functions we are constantly adding and upgrading, and to standardize all our offerings as part of the overall Magellan platform, we’ve updated the names. Here’s the translation key:

And here’s how they fit together into sets:

Illustration of two parallel tracks of Magellan solutions, content analytics on the top. data analytics on the bottomIn the content track, the entry point is the Magellan Content Analytics Suite. This contains Magellan Text Mining, which can intelligently interpret the meaning of text in a wide range of formats (from documents to web content and social media feeds) for easier classification and processing, and Magellan BI & Reporting, which provides convenient, visually appealing analytics, reporting and dashboards.

Combine those with Magellan Data Discovery, the powerful analytics and data exploration tool, plus upgrading the platform’s capacity to analyze up to 700 million rows of data, and you get the Magellan Advanced Content Analytics Suite.

Then add the Magellan Notebook, the powerful, flexible data science tool based on the Jupyter Notebook, and the Apache Spark computing platform, and you get the full Magellan Platform, which has a nearly unlimited data processing capacity. The added Magellan Notebook capacity provides the ability to create, save, and share your own machine learning models for predictive and prescriptive analytics.

In the data analytics track, the starting point is the Magellan Analytics Suite, which comprises Data Discovery and BI & Reporting. On its own, it can already handle very large data sets.

Add to the basic Analytics Suite the Magellan Notebook, the Apache Spark platform, and the capacity to process an extra 200 million rows of data, and you get the Magellan Artificial Intelligence Suite.

Then add the last piece, Magellan Text Mining, and you arrive again at the full Magellan Platform, with its nearly unlimited data processing capacity, plus the capacity to analyze unstructured data such as text.

More machine learning at every step

In each track, it’s easy to move up from a basic set of solutions to a more advanced one. And each can be customized to the database size and number of users you expect.

“We know customers don’t generally dive directly into ML from the very beginning,” explains Carlos Araya, one of the lead Magellan designers at OpenText. “They generally follow these steps in the ‘path of value’ for analytics and AI: first descriptive analytics, then diagnostic, decision support, predictive, and lastly prescriptive analytics.

“The new Magellan suites are aligned with this path in that the first one in each track focuses on enabling the descriptive and diagnostic portions, then setting the stage for decision support. As you move to more extensive Magellan suites, you get further into predictive and prescriptive value propositions – at each step adding more machine learning-derived insight and direction towards the best course of action. OpenText is always working to help customers unlock more value from their enterprise information.”

Interested in finding out more about these new Magellan offerings? Contact us for more information.

 

Stannie Holt

Stannie Holt is a Marketing Content Writer at OpenText. She has over 20 years' experience as a journalist, market research analyst, and content marketing expert in the fields of enterprise business software, machine learning, e-discovery, and analytics.

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