Leverage the Data in Content
The IT Strategist’s Guide to Transforming ECM
Every organization has two types of content:
Structured content (loosely termed “data”) found in ERP, CRM, line-of-business applications, and other core systems.
Unstructured content (loosely termed “documents”) that exists outside core systems and contains information critical to business operations and decision-making. Examples include Word documents (proposals, contracts, project plans, service reports, etc.), PowerPoint presentations, Excel spreadsheets, pdf files, CAD drawings, e-mails, images, videos, and more
Consider the following when building solutions to extract and amplify the value of unstructured content.
Metadata is the key to unlocking and amplifying the value of unstructured content. Metadata allows you to effectively control, organize, track, and secure unstructured content as it moves through business processes, between systems, and across its lifecycle.
Today, metadata extends well beyond the familiar file type, author, and date created to include custom metadata that gives unstructured content more meaning and context. For example, you might tag a sales agreement with customer name and close date, or attach policy number and status to the files associated with an insurance claim.
Contextual metadata enables connections between pieces of content so related information can be retrieved and leveraged. It also allows you to link content with business processes and to ensure that all relevant information is available at the right time to support fast, effective decision-making.
Add Metadata Automatically
So why isn’t all this unstructured content already categorized with metadata? Common challenges include a rigid, hierarchical information architecture that’s complex to manage and hard to change, and manual processes that are time consuming and error prone. Asking busy knowledge workers to tag files with metadata almost always fails.
Automation is the only practical way to enrich content with consistent, accurate, high quality metadata at enterprise scale. Technologies for automatically categorizing content with metadata include:
Here are some of the most important ways you can benefit the business by extracting more data and value from your content.
AI is a game-changer when it comes to unlocking the value of enterprise content. At the most basic level, AI and machine learning technologies can answer the question, “What’s in this content?” When applied at scale, they can uncover the insights, patterns, and relationships hidden in massive volumes of documents, images, videos, and other digital content.
Amazon Web Services (AWS), Google, and Microsoft all offer fully-featured AI services that are accessed via APIs. They support a wide range of AI and machine learning techniques, including entity extraction, key phrase extraction, sentiment analysis, and more.
How to Integrate a Cloud AI Service with Alfresco
An open, extensible content services platform makes it easy to use cloud AI services to analyze and enrich your content.
For content stored in a corporate data center, you simply write a metadata extractor that sends a file to the AI service, and then stores the resulting metadata—sentiment, summaries, entities, categories, relationships, etc.—in the repository alongside that file. You can even configure rules to trigger the analysis automatically, such as when a file is added to a folder.
Mining unstructured content with AI technologies and tagging it with contextual AI insights opens up a world of possibilities as you pursue a digital transformation agenda. A content services platform with an open, extensible approach to leveraging third-party AI services gives you maximum flexibility as technologies advance and business needs change.
Look for these capabilities to mine, enrich, and act on content with greater intelligence and effectiveness.
Act on Enriched Content