The challenge for analysts seeking trading opportunities that outperform the market is not a lack of information. It is an over-supply of information from widely disparate sources. How do you sift through the overwhelming flow of reports, news feeds, articles, blogs and social media posts to find the sentiments, relationships, patterns, unique insights and powerful nuggets of information that drive performance?
While there are many point tools that assist with pieces of the analysis, for the most part this is still a labor intensive, time consuming, and inefficient process - like searching for a needle in a haystack.
What if there were a holistic research platform that could combine information from disparate sources, both structured and unstructured, inside or outside the enterprise, into a unified view? A discovery and investigative platform where users could easily add and harmonize new data sources, find unknown relationships and answer questions that they did not anticipate in advance. All at enterprise scale.
At Cambridge Semantics, under the leadership of our Director of Advanced Analytics, Richard Mallah, we have configured our Anzo Smart Data Lake to deliver exactly this capabiltiy.
Anzo is an end-to-end data integration, management, discovery and analytics platform, built on open semantics web technology standard (RDF, OWL and SPARQL). It enables the rapid harmonization of diverse data and user self-service discovery and analytics, at big data scale and without coding. Anzo runs on existing big data technologes including Hadoop HDFS, Apache Spark, Amazon S3, Google Cloud Platform.
The key capabilites of the platform leveraged for this solution include:
- The abiliity to quickly combine together information from any source, regardless of format, without any coding
- Harmonization of data based on its meaning, enablings deep semantic search and analytics across combined structured and unstructured data sources
- User driven, interactive, investigative model empowering idea generation, identification of performance drivers and discovery of unknown relationships
- A massively parallel in-memory graph engine for interactive analytics on very large datasets
Anzo's native graph representation of data is a natural fit for discovering unknown relationships (e.g. between people, companies and across supply chains):
Anzo's self service tools allow users to build their own visualizations (e.g. explore and compare company and market sentiment over time):
To learn more about text analytics, watch Richard's on-demand webinar "Introduction to Anzo Unstructured".
