AI-augmented data democratization powers OpenText Analytics, Release 16.4

Even bigger data in a single view, from any source, visualized with smarts

Data democratization and putting AI to practical use are the major themes of OpenText Analytics Suite and OpenText Magellan, Release 16.4, which become generally available this month. Expanding on our mission of putting AI-augmented, enterprise-grade analytics insight into the hands of anyone who wants it, not requiring data scientists to prepare the data and run queries, this new release includes dozens of improvements to usability and function that improve data preparation, analysis, and display.

Because enterprises have to accommodate diverse data environments, where business partners or even other departments may use different technology stacks, OpenText Analytics Release 16.4 allows easy connection to a wider range of external data sources and smooth integration with popular Enterprise Information Management systems, both inside and outside the OpenText family.

This release also upgrades the OpenText Analytics platform to robust 64-bit architecture. This allows for faster processing and “future-proofs” it by enabling interoperability with 64-bit-based file systems such as Amazon’s Elastic File System.

And it makes the overall solution smarter through industry-leading machine learning and AI, able to mine useful insights out of unstructured data such as text documents and social media posts.  This way, it can proactively handle routine business processes, dramatically reducing the amount of intervention needed by human staff.

All these improvements make OpenText Analytics and Magellan 16.4 a powerful self-service, end-to-end AI-augmented analytics and reporting solution that opens new frontiers of real-time insight into your operations. You can then visualize your findings in a rich variety of new formats, including word clouds, bell curves, and histograms, letting users see data trends and relationships at a glance.

New data connecting and loading options

With EP4, provisioning and loading data is no longer a task that needs the skills of database administrators. Now business analysts and other serious users have self-service connections to popular third-party relational databases and Big Data sources including:

  • Oracle
  • DB2
  • PostgreSQL
  • Hive
  • MySQL
  • Salesforce
  • SparkSQL
  • Sybase
  • IBM Netezza
  • SAP HANA
  • MSSQL

There’s also an Open Database Connectivity (ODBC) driver for custom sources and a remote data provider option for loading data from a web address.

In addition, we’re launching a new ETL module that lets business analysts load data from the OpenText Analytics Suite’s front end (an environment they’re used to), directly into Hadoop-based data lakes via Apache Spark, the open-source analytics engine underpinning the suite. They can manage projects, log their history, and schedule future projects in a new workflow for tasks and events.

This democratizes data access. Instead of requiring data scientists to perform specialized coding for ETL processes in Hadoop, analysts who are familiar with their organization can work directly with the information they want answers from. The result is faster, more flexible and cost-effective analysis of very large data sets, which today’s information-rich business processes require.

Analytics Suite Data Prep feature

Smarter data preparation

Meanwhile, we’ve infused more intelligence into our self-service data preparation. The Analytics Suite 16.4 data preparation features can automatically add data hierarchies to the models defined in a data object. For example, it knows that a country is made up of states or provinces, which in turn are made up of cities and counties. (An intuitive drag-and-drop UI lets the user define the terms of a specific hierarchy.)

This lets users of that data object easily create report and dashboard charts that “know how” to navigate these hierarchies. For example, clicking on the bar for USA in a bar chart automatically drills the chart down to the State level and displays all the relevant states.

We’ve also enhanced the Magellan Text Mining function for smarter content mining functions, letting users more easily create and manage taxonomies by letting them upload their own spreadsheets or CSVs for specific language or named entity types. As a result, customizing the content analytics and mining engine to work for their own unique contexts is simpler and more straightforward.

Closer integration with a multitude of Enterprise Information Management systems

In today’s globally connected economy, an organization may have customers, suppliers, regulators, and even internal business units operating in a kaleidoscope of different data formats and EIM solutions. OpenText Magellan 16.4 accommodates that diversity by adding native integrations into other OpenText EIM solutions including Documentum, Content Server, Archive Center, and eDocs, for easy analysis of ECM data alongside other sources.

Direct integrations into popular third-party tools such as Box, Dropbox, Gmail, Google Drive, IBM® FileNet®, Microsoft® Exchange®, and SharePoint® are also now available as add-ons. A generic CMIS connector offers interoperability with still other content management systems.

Even more responsive and stunning dashboard visualizations, plus new “word cloud” option

New graphic libraries included with the suite make visualizations of your data more compelling and attractive. New formats include the bell curve, bullet chart, histogram, parallel coordinates chart, Pareto chart, Sankey diagram, 3D scatter chart, stream graph, sunburst, variable pie, variwide, vector plot, wind barbs, heat maps, and the ever-popular word cloud.

Further, all Analytics Suite charts and dashboards have been engineered to resize and reposition intelligently on a wide range of smartphones, tablets, and other mobile devices.

“Follow the money”… through better data tracking

We’ve added some very important data handling functions that will keep customers up to date with the newest, most rigorous financial reporting standards worldwide.

First, we’ve enhanced the data lineage functions of our built-in FastDB columnar data storage, based on open-source Apache Atlas, to track exactly which data source a column or table is coming from, and which transformations occurred during the ETL process. The Analytics Suite will then display the lineage in a user-friendly graph visualization – a feature banking regulators appreciate.

Data Lineage Big Data Analytics

Second, the Analytics Suite adds the ability to work with high-precision decimal numbers down to, say, the millionth of a cent. Obviously, microscopic amounts like this won’t make or break your payroll. But tiny changes in, say, currency exchange rates can add up when you’re looking at transactions involving billions of dollars or Euros.

Less sophisticated analytic applications round amounts like 50,000.00000001 up or down, which can lead to discrepancies in the figures required by financial regulators. But Release 16.4 keeps track of even the most microscopic differences in your data.

Added big data analytics capabilities leverage Hadoop and Spark to help non-experts

Building on our existing highly scalable foundation with open-source Hadoop and Spark technologies, Release 16.4 adds the ability to perform crosstab and Venn diagram analysis in the business user view, using Spark as the repository. Business users can also now transform and enrich data in Spark via a simple drag-and-drop interface. This new functionality also boosts the usability of Magellan, our AI-enriched analytics platform.

OpenText Analytics EP4: Putting the power in everyday users’ hands

Taken as a whole, the improvements to OpenText Analytics Release 16.4 add up to greater self-service for ordinary users, who get an added range of do-it-yourself data preparation and visualization functions. Our goal is to minimize the need for IT involvement, so that business analysts and other non-data scientists can quickly get the answers they need.

Download a free trial version of the Analytics Suite. Or learn more about it here.

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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