The expert.ai natural language (NL) API enriches data sets with insights from unstructured language data to improve analytics – Using NLP with Tableau
The insights gained from business intelligence applications can easily be extended using the expert.ai NL API to enrich data sets. By leveraging the comprehensive set of natural language understanding capabilities provided by the NL API, developers and business analysts can augment their data sets with information extracted from external unstructured language resources. By executing Python code directly within their BI tools, enterprises can both improve results as well as extend the reach of analytics.
There’s data in that data: Enriching Data Sets With NLP– the case of Tableau
Livestream event – September 16 11 am ET / 5 pm CEST
NL-based data enrichment improves the analysis of unstructured data – which makes up a massive 80% of all enterprise data – and pushes business intelligence boundaries as data in the form of language typically can’t be analyzed by BI tools. The expert.ai NL API analyzes unstructured language data in a matter of seconds, returning a wide variety of meaningful information (entities, key phrases, topics, sentiment, emotional and behavioral traits, relationships between concepts and entities) that can be easily employed directly within BI tools executing Python code.
During today’s livestream session There’s Data in That Data: Enriching Data Sets With NLP, our AI experts will discuss how natural language processing (NLP) can extract additional information from unstructured language data to enrich BI data sets and provide business users with deeper insight. Using Tableau Prep as an example, we will demo two use cases to show how NLP capabilities can be added to BI data flows to enhance data sets directly within Tableau.
Adding sentiment from customers reviews – Tableau BI case OVERVIEW
Given 84% of people trust online reviews as much as friends, e-commerce sites, blogs, forums and social media represent an invaluable resource for brands to gather insightful data about how they are perceived by customers to boost their conversion and improve their market position. Amazon, which according to recent industry figures, is the leading e-retailer in the United States with close to 386 billion US dollars in 2020 net sales with over 200 million unique monthly US visitors, offers a very rich repository of consumer reviews. The problem is that reviews are expressed in natural language that is not analyzed by BI tools – expert.ai offers this capability, allowing sentiment-based data enrichment through Python script on Tableau via the NL API.
IPTC-based metadata enrichment – Tableau BI case OVERVIEW
The advantage of natural language understanding for publishing & media spans from enhancing search of content and categorization to AI-powered recommendations that are gaining more and more popularity and, according to recent industry researches, are one of the reasons why people binge-watch Netflix, YouTube and other highly addictive media streaming platforms. During the livestream session, we will focus on the capability of the expert.ai NL API to provide out –of-the-box IPTC categorization and semantic tagging to enrich a data set of articles and news available in Tableau to get to a more accurate and comprehensive analysis.
“Today’s enterprises face a growing need for natural language outcomes ensuring completeness, accuracy and efficiency to business intelligence database,” said Brian Munz, product manager, NL API & developed experience for expert.ai. “This puts more pressure on analysts and the developer ecosystem to provide accurate language understanding at speed and scale. Data enrichment with our NL API is a simple, very practical and powerful way to fill in gaps in data sets and augments BI tools reach. There’s data in that data… and we can definitely help businesses find it!”
