Sisense News is your home for corporate announcements, new Sisense features, product innovation, and everything we roll out to empower our users to get the most out of their data.

As consumers, we’ve become used to intuitive search engines like Google that learn about our consumption habits. The results we see online are incredibly personalized towards our own digital behavior. A recent Fortune special report on Artificial Intelligence (AI) pointed to the recent developments in the field of Natural Language Processing (NLP) over the last 18 months as “revolutionary” for better search engines, smarter chatbots, and digital assistants. Similarly, while creating this blog post, I’m given suggestions that aim to help complete my sentences via a “Smart Compose” function. 

While analyzing data, business users can now ask questions of their data and receive insights around results. By 2021, Gartner predicts that NLP and conversational analytics will boost adoption of analytics and business intelligence from 35% of employees to over 50%, mostly because the historical challenges of understanding data are now easier. This enables a new class of users, front-office workers, to benefit. It’s one of Gartner’s top 10 data and analytics trends, and it’s poised to drive better outcomes as insights will now be delivered to business users— deeper and more personalized than ever before. 

Sisense for Product Teams

AI throughout is in our DNA

At Sisense, we’re deeply committed to AI because it feeds both parts of our “Power to the Builders” and “Insights for Everyone” mission. Sisense aims to enable all parties across the organization to perform their best work with minimal effort. In Q1 2020, we’re rolling out Sisense NLQ (Natural Language Query), which automates the process of receiving answers to sophisticated questions within our platform. 

Over the course of 2020, Sisense will continue to develop and leverage its AI capabilities, bringing to market numerous new benefits for both modern builders and each organization’s business users to better engage with their data and achieve faster times to insight and action. 

Sisense NLQ: Deeper data exploration and faster time-to-insight

Sisense NLQ allows users to better explore their data and more easily receive insights. By beginning to type a word such as “What” or “How”, the system will begin to ask questions and recommend personalized suggestions that auto-complete fields and values, filters and break by, and analyses over time. The Sisense NLQ engine provides suggestions to fix typos, correct spelling mistakes, or search alternate words. Recent and saved searches can be reused through a single click, and answers can be quickly applied to modify a visualization through an intuitive UI. This new functionality allows users to go beyond predefined models created by a designer. 

A look under the hood

Sisense NLQ utilizes cutting-edge (or revolutionary, according to Fortune) NLP technologies, including the pre-trained language model called BERT. Developed by AI researchers at Google, BERT(which stands for Bidirectional Encoder Representations from Transformers) better understands natural language. BERT is not the only AI model named after a Sesame Street character. There’s also ELMo, Grover, Big BIRD, two ERNIEs, KERMIT, and more. Here at Sisense, our AI team is using a distilled version of BERT to enhance our NLQ  offering with better semantic understanding. In other words, if I search for “income” the system will also understand that I mean “profit.”

Another important development empowering Sisense NLQ is the Sisense Knowledge Graph, the patent-pending foundational layer for many of our AI capabilities. Sisense Knowledge Graph is a powerful engine that was developed with over a decade’s worth of data, studying over 650 billion events that indicate organizational usage patterns. Sisense Knowledge Graph thus brings more “human” and context-aware recommendations to Sisense NLQ.  Finally, in addition to the semantic analysis with BERT, Sisense NLQ works to resolve ambiguities that are typical within the syntactic and lexical structure of your text, translating it into a DB-ready query.

Augmented Analytics

Sisense Q1 release includes numerous customer benefits

Here are some of the highlights, and for more details, check out our New Features or Q1 Release Notes.

  • Live Pulse Alerts: Automatically identify critical changes in your live data and proactively alert other stakeholders. 
  • Premium Ingestion Connectors: Ingest data from popular data sources directly into Sisense Managed Warehouse or Bring Your Own Warehouse to unify your data sources and build efficient, cost effective cloud data pipelines. 
  • MongoDB Connector: Process big, unstructured data stored in MongoDB databases using Sisense’s award-winning analytics engine.
  • OpenID Connect for SSO: Easily integrate and provide users with a more usable and secure authentication.
  • Data Model APIs: Fully automate data workflows to save time and minimize risks, including the programmatic creation and modification of Sisense data models across deployments
  • Embedded Playground for Developers: Discover and experiment with Sisense embedding and customization capabilities in a rich, interactive environment. 
  • Sisense GitHub: Join the official Sisense Open Source GitHub community, a space for public Sisense projects including open-source projects.
  • Report Manager (Premium Add-on): Set up and share customized reports on a predefined schedule or triggered by events.

Explore these and other capabilities on the release page and join our webinar on April 16th at 1 pm Eastern Time to learn more.

Sisense for Product Teams

Julie Zuckerman is a senior product marketing director at Sisense, bringing over two decades of experience in marketing and product marketing at tech companies. Her debut novel, The Book of Jeremiah, was published in 2019.

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