We should be living in an information utopia. Ever more powerful and affordable technology means you can gather data out of nearly any process, from overheating train brakes to citizen comments about the quality of service at their local airport, and share it widely and near-instantly.
With relatively little effort, a company or agency can amass petabytes of data – more information than the entire human race had collected up till the 20th century. And information-collecting is vital, because in an increasingly competitive economy companies need to take advantage of every possible insight in order to grow their business and stay ahead of competitors.
The problem is, having so much data can be overwhelming to manage. Organizing enormous volumes of data, searching them for patterns and relevant insights, and reporting those findings in a timely and useful way takes data science expertise and programming horsepower your organization may have trouble finding (or paying for).
OpenText can help.
We’re introducing Magellan, a flexible, pre-wired AI-powered analytics platform that combines open source machine learning with advanced analytics, enterprise-grade BI, and capabilities to acquire, merge, manage and analyze Big Data and Big Content stored in your Enterprise Information Management (EIM) systems.
Magellan offers faster, smarter decisions at scale
Magellan enables machine-assisted decision-making, helping you automate and optimize your business operations. You can gain value and insight from your data stores with Magellan, and leverage the benefits of AI-powered analytics for faster decision making and task automation.
What this means in real-world terms is that you can make decisions and take actions with the help of Magellan with greater speed and scale than you could unassisted. You can leverage machine learning to unlock the value of Enterprise Information Management (EIM) data – for example, understand and analyze customers, trading partners, employees, orders, invoices, cases, documents and other data managed by your OpenText solutions.
And you can easily overcome technical problems that used to stymie large-scale analytics projects, because Magellan can easily digest a wide range of data types (structured or unstructured) and formats. Because it’s a single, cohesive infrastructure with pre-integrated components, it minimizes the effort and expertise you need to go live. This also means shorter time to value!
Democratizing your data
We designed the Magellan platform to help you democratize your data by simplifying collaboration and access to data insights.
With state-of-the-art AI capacities, it empowers data scientists to create custom analytic and predictive algorithms that business analysts and operational users can leverage to answer nearly any relevant question.
It’s not limited to structured data (i.e. numbers and other database content). Magellan can also deliver insights from unstructured data such as text and social media because it includes powerful natural language processing capabilities for Big Content, including concept identification, categorization, entity extraction, and sentiment analysis.
Magellan also lets users continuously refine their results, drawing on the powerful Apache Spark computing foundation (including MLlib, its built-in machine learning library) to keep examining their existing data and bring in new information, measuring predicted results against successive outcomes to achieve the most current and complete insights.
Because Apache Spark is open-source, Magellan lets you take advantage of the flexibility, extensibility, and diversity of an open product stack while maintaining full ownership of your data and algorithms.
Designed to drive autonomy
Magellan enables self-service access to insights throughout your organization, because it draws on the OpenText Analytics heritage of putting visually appealing, user-friendly analytics and reporting in the hands of the people who need them. No longer are sophisticated analytics programs only usable by highly trained data scientists; once you set up your Magellan queries, business users can draw conclusions and derive useful insights and predictions from even the most complex data sets.
This ability is thanks in large part to the Magellan Notebook, a virtual online computing environment based on the Jupyter Notebook application. The Magellan Notebook lets data science experts create “Notes” combining live code, equations, visualizations, and explanatory text that define custom algorithms and machine learning routines. These Notes are easily shared with operational users, who can leverage the routines to make smarter decisions without needing to understand the science behind it.
Built from the best components for power and versatility
Magellan incorporates best-of-breed components, carefully engineered and integrated to work smoothly together to drastically reduce the set-up time and expertise needed and put the power of AI-assisted analytics and BI directly at your fingertips.
It builds on the time-tested OpenText™ Analytics Suite, which has helped thousands of organizations in every industry around the world move from insight to action and operate more efficiently, inventively, and profitably. Magellan then adds highly regarded open-source platform and AI components including Apache Spark and the MLlib Machine Learning library, which are regularly expanded and improved by the global Open Source community.
The bottom line: Magellan puts AI within reach for a wide range of business users
Easy to use and cost-effective aren’t generally used to describe machine learning and business intelligence technologies. The Magellan platform offers both advantages, plus speed and scalability, so organizations can immediately see insights from their data and take action.
The integrated, pre-wired analytics platform lets you get up and running with AI-powered insights faster than you thought possible.
Over the weeks and months to come, we at OpenText will be sharing more details about Magellan, such as typical use cases where different industries or function can find value, plus deep dives into the technology. We hope you’ll join the conversation with us. Meanwhile, click here to learn more.