Are We There Yet With Content Analytics and Intelligence?
Artificial Intelligence is a disruptive yet intuitive technology that is shaping the Enterprise Content Management systems of the future. While ECM systems have relied on passive responses, AI is stressing the use of active responses and making workflows based on findings from the machine learning aspects of AI.
The use of AI is seen as beneficial in increasing enterprise knowledge or leveraging the enterprise assets. Today ECM implementations are often faced with questions on how to boost AI or make content intelligent. This blog discusses how the ECM offering from OpenText has embraced the challenges posed by AI.
Content Intelligence Services
Content intelligence is the ability to provide structure for unstructured content – a process enabled by the intelligent, automated tagging and categorizing of business content for personalized delivery and easy search. Tagging and categorizing content with rich metadata makes it available for reuse across multiple initiatives such as customer and employee portals, custom applications, and personalized sites where capabilities such as precise search, easy navigation, and personalization are critical to productivity and customer satisfaction. By extending the value of content through reuse, content intelligence also cuts the costs of recreating information.
However, despite the value of content intelligence for advanced searching and personalization, companies have been slow to embrace this technology because it is often perceived as complex or difficult to implement and deploy. There are multiple debates within both business and technical domains as to the most optimized manner for creating the taxonomies and hence the tags for the content.
Furthermore, this technology is sometimes considered inflexible, particularly when changing market conditions or new business opportunities require changes in the way content needs to be organized. Many point solutions break down under these conditions because complex integrations with other products need to be reconfigured, resulting in re-implementation costs and valuable time wasted.
OpenText Documentum Content Intelligence Services
OpenText™ Documentum Content Intelligence Services help enterprises create taxonomies and tag their content automatically. OpenText Documentum CIS is a high-performance extension of the OpenText Documentum platform which automates and controls the enrichment and organization of enterprise content based on powerful information extraction, conceptual classification, business analysis and taxonomy and metadata management capabilities. It is fully integrated with the Documentum platform and thus provides an automated solution for all kind of content managed within an OpenText Documentum repository.
OpenText Documentum CIS turns unstructured enterprise content into intelligent structured content with powerful, unique capabilities:
OpenText Content Intelligence
OpenText™ Content Intelligence is an add-on to the OpenText™ Content Suite Platform that helps increase user adoption, productivity, and management insight by accelerating the deployment of tailored applications, actionable dashboards, and reports. It bundles accelerated Tile/Widget creation, enhanced REST API, and a powerful sub-tag library with a complete set of instantly deployable and easily modifiable prebuilt reports, dashboards, and applications.
OpenText™ Analytics revolutionizes analytics and reporting functions of the ECM solution. The Analytics suite enables creation of dashboards, visualizations, and analytics applications that answer vital questions across the organization.
OpenText Analytics Suite comprises two deeply integrated products: Big Data Analytics and Information Hub (iHub). Working in tandem, these two products give business users, business analysts and citizen data scientists the ability of independent data preparation, data exploration, advanced analytics and sharing and socializing the analysis results in compelling dashboards, as interactive data visualizations, or pixel perfect reports.
OpenText Information Hub (iHub)
OpenText™ Information Hub (iHub) is a scalable analytics and data visualization platform. iHub enables IT teams to design, deploy, and manage secure, interactive web applications, reports, and dashboards fed by multiple data sources. iHub supports high volumes of users, and its integration APIs enable embedded analytic content in any app, displayed on any device. iHub enables report developers to design, deploy, and deliver secure, interactive web applications, personalized reports, and dashboards fed by multiple data sources.
With an iHub application, business users can explore data on their own with interactive capabilities such as drill-downs, filter, group, build new calculated columns. Also available:
OpenText Big Data Analytics
OpenText™ Big Data Analytics is an analytics software solution for business users and analysts looking for an easy, fast way to access, blend, explore and analyze data quickly without depending on IT or data experts. Advanced analytics helps businesses understand their customers, markets, and business operations as well as managing IT budgets effectively, leveraging expert resources as needed.
Big Data Analytics combines an analytical columnar database that easily integrates disparate data sources, with built-in statistical techniques for profiling, mapping, clustering, forecasting, creating decision trees, classification and association rules, doing regressions, and correlations.
Users can get a 360-degree view of their business, explore billions of records in seconds and apply advanced and predictive analytics techniques all in a drag-and-drop experience, with no complex data modeling or coding required.
Working in an easy-to-use, visual environment business user can upload their own data, clean and enrich it, blending data from disparate sources. They can then apply pre-coded algorithms and analytical techniques to gain insights from massive data sets on the fly.
OpenText has both on-premises as well as cloud versions of Big Data Analytics solutions for the customers. There are also solutions specifically tailored for certain industries:
- Analytics for Energy & Utilities
- Analytics for Public Sector
- Analytics for Manufacturing
- Analytics for Financial Services
- Analytics for eCommerce & Retail
- Analytics for Logistics & Warehouses
- Analytics for Telecommunications
- Analytics for Publishing & Media
- Analytics for Healthcare
- Analytics for Marketing Service Providers
Some of the advantages of choosing OpenText Big Data Analytics are:
- All your data in a single view: Access huge data sets from multiple sources quickly and easily.
- Analyze billions of records in seconds: Leverage high-performance, real-time Big Data analysis of hundreds of tables, millions of rows, billions of records—at once—for deeper business insights.
- No complex data modeling: Eliminate the need for data cubes, pre-processing and modeling. Minimize data analysis-related IT workload and dependency on data scientists.
- Best Practices analytical techniques: Pre-built algorithms and ready to use predictive analytic techniques. Discover threats, hidden relationships, patterns, profiles and trends to make fact-based decisions.
- No coding required: Go from raw data to sophisticated data visualizations in minutes with a few clicks.
- Easy to use visuals: Analyze Big Data quickly and visually with decision trees, association rules, profiling, segmentation, Venn diagrams and more.
- User autonomy and self-sufficiency: Empower users without statistical backgrounds to run deep analytics with pre-packaged algorithmic functions.
- Automate with Workflow: String together multiple steps into one process and schedule it to run on a regular basis.
For more details on the benefits of OpenText Big Data Analytics, click here
Big Data Analytics is well targeted towards specific industries and allows the business users to create rich reports by analyzing data from various data sources. The solution provides easy configuration tools for the business users and reports creators to design and develop a report quickly.
At the same time, Documentum Content Intelligence Services provides a mechanism for users to mine structured and unstructured content to automatically gather information as configured by the business users. Both solutions allow easy information extraction from unstructured content and allow for readable and meaningful reports.
While both solutions provide two different sides of the puzzle, there seems to be an opportunity remaining in Information Extraction techniques and development of self-learning, intelligent algorithms to parse the unstructured data into meaningful structures. The resulting structures could then be utilized for creation of reports and providing a feedback to the users or system workflows, thus rendering the system even more intelligent. More to follow on this topic shortly.