The Smart Data Blog

The Need For Anzo Unstructured

Posted by Richard Mallah on Feb 8, 2016 11:31:34 PM

The Need
Unstructured data is all around us: in news stories, web pages, journal articles, social media posts, patents, research reports, presentations, and a variety of other sources. These items are unstructured in that they don’t start out with a predefined, explicit schema or structure. Historically, these documents have been read by humans looking to find information relevant to their particular tasks or roles. In today's deluge, however, the need for scalable reading, repeatability, traceability, and speed has driven the advent of text analytics platforms.

Introducing Anzo Unstructured
Anzo Unstructured (AU) is both the most comprehensive text analytics platform available today and quite easy to use. Anzo Unstructured is uniquely suited to excel at seamlessly blending and integrating structured and unstructured information, cross referencing information between documents and structured databases, applications, or spreadsheets. Among other outputs and benefits, AU produces a knowledge graph, also called a semantic network, which links together the concepts, topics, and documents you need in a manner that's both machine-usable and human-intuitive. Anzo Unstructured understands the conceptual schema of not only different document and annotation types, but also of the domain objects, business objects, and source concepts that inform your solutions. It actually points out facts and ideas in terms your subject matter experts will relate to.

How Our Customers Are Using Anzo Unstructured Today
The variety of ways enterprises use Anzo Unstructured today ranges widely across different industries, functions, languages, and workflows. Since Anzo Unstructured can improve many aspects of business, enterprises have also found it natural to evolve their use of the platform beyond a single use case to accommodate multiple, somewhat connected, uses in tandem. Verticals heavily utilizing Anzo Unstructured include finance, pharmaceuticals, consulting, intelligence, and publishing.

Finance Use Cases
Applications in financial services range across alpha generation and compliance. Understanding the ever changing webs of correlations, alliances, suppliers, owners, investors, competitors, and clients within the worlds of business or of equities is far too time consuming for any individual. Unleashing AU for such applications to contextualize and enrich news, secondary research reports, wire services, and Bloomberg chats as they are written helps equity analysts, traders, or portfolio managers remain informed of such developments. Compliance applications within financial services are another compelling and popular use of AU in tandem with the broader Anzo platform. Combining, connecting, and analyzing relationships among databases of trades and audit logs, email archives, IMs, call logs, current, historical, public and commercial news feeds and correlating entities — while recognizing trends and anomalies — paints a holistic picture of activities, context, and likely motivations. Such advanced and exploratory analytics on these knowledge graphs make the platform ideal for insider trading surveillance, fraud detection, anti-money laundering, and adverse media searches.

Bioscience and Pharmaceutical Use Cases
Applications in biosciences range across the full drug development life cycle, from early R&D informatics to trial site selection, competitive intelligence, and many steps in between. AU can mine patents, journal articles, press releases, specialty books, and internal documents for relationships between pathways, biomolecules, genes, targets, mechanisms, and to other compounds, building a knowledge graph that can power multiple biopharma use cases at once. Pharmacovigilance, the finding of unexpected side effects of medications, is one important pharma application of this. As AU reads relevant documents and notes, it can differentiate medical history ailments from currently presenting symptoms, distinguish indications from co-presenting issues, and differentiate expected side effects from unexpected side effects. The unified information environment AU generates makes for more powerful and flexible semantic searches enhanced by bioscience knowledgebases.

Summary
As the marketplace evolves increasingly faster, understanding the nuances of the landscape will take an ever increasing amount of time by default. Organizations can largely automate this process with Anzo Unstructured, regardless of vertical industry. Any organization can also use AU to automatically map out what knowledge it lacks about the reams, stacks, and drives of content it has accumulated throughout the years that contains useful, sensitive, or valuable information. On moving to a broader strategic view for the relationship between your enterprise and unstructured data, Anzo Unstructured will be seen as a framework for supporting a wide range of unstructured processing activities, providing a transformational and foundational new capability for your organization.

Topics: Semantics, Big Data, Text Analytics, Financial Services, Data Lake, Anzo, Analytics, Unstructured Data