Predictions are becoming cheaper, faster, more automated and more ubiquitous in our lives, and we have artificial intelligence to thank for that.
AI is essentially a predictive technology. No matter what its algorithmic underpinnings, its core function is to make sophisticated inferences about what’s likely to happen based on myriad variables that have been distilled both from historical and real-time data. When it’s embedded in every device and refined continuously with fresh data, AI becomes a ubiquitous resource helping us all to anticipate what’s coming and do what’s necessary to keep our lives running smoothly.
Business intelligence (BI) is a substantially different market now from when I first started covering it in the mid-2000s. One of the core trends has been the convergence of BI’s traditional focus on historical analytics with a new generation of predictive analytics tools that allow any business user to do many things that used to require a trained data scientist. In addition, most BI solutions now offer their functionality through subscription-based software as a service (SaaS), but it’s all self-service, in-memory, interactive, guided, and otherwise amazingly search-like in user experience and easy for anybody to master in no time.
Today’s most sophisticated BI solutions also incorporate a deep dose of AI to automate the distillation of predictive insights from complex data. One of the pioneers in that BI segment is ThoughtSpot, a Palo Alto-based vendor that has come far since its founding in 2012 and just this week put on its first user conference.
With what ThoughtSpot calls its “relational search engine for data analytics,” everyday business users can use single-click Google-like search to rapidly analyze complex, large-scale enterprise data and automatically gain trusted insights to questions they didn’t know to ask. Emphasizing its focus on modeling-free ad-hoc analytics, the company has a keen focus on user experience as a key differentiator in democratizing AI-driven business analytics.
Among its many experience-boosting BI features, ThoughtSpot’s solution delivers the following AI-driven capabilities:
- transparent calculations into how each insight is derived;
- automatic generation of natural language narratives accompanying each chart that’s rendered;
- adaptive self-learning that leverages interactive user feedback to automatically refine results to match user preferences;
- guided search experience that automatically and dynamically generates suggestions with an AI-driven understanding of the user’s role, search history and entire data model
With a founding team from Google and Amazon and currently led by industry veteran CEO Sudheesh Nair, the company now has a valuation of $1 billion, counts 32 of the Fortune 500 companies as customers, and has 350 employees at locations in the US, UK, and India. At Beyond 2018, ThoughtSpot’s executives brought users up to speed on some important innovations in its user experience, solution portfolio, and partnerships in the data science and cloud arenas. These announcements included:
- Enabling AI-powered voice-driven analytics: Conversational user experiences are permeating every niche of the cloud analytics market. This week, ThoughtSpot announced the beta of its version 5 next-generation platform ThoughtSpot 5, which incorporates a new voice-driven analytics interface, called SearchIQ. Built on Falcon, ThoughtSpot’s in-memory calculation engine, SearchIQ enables employee to find insights buried in billions of rows of data with just a simple spoken sentence. In addition, this platform update incorporates the latest enhancements to ThoughtSpot’s AI-driven SpotIQ analytics engine. It now supports speedy search-driven queries on more complex data schemas, recommends related content in context, automatically pushes relevant insights to users, and quickly surfaces interesting data findings that would otherwise be buried deep in data stores. It also includes new integrations with R that simplify how business users build predictive models and analyze them through searches.
- Automating AI-driven search, query, and predictive analytics: Automated machine-learning pipelines have taken root throughout the data science and AI marketplace. In this regard, ThoughtSpot announced its partnership with DataRobot. The new solution capabilities under this partnership, to be rolled out in the first half of 2019, will streamline data science workflows while simplifying search for machine-learning-driven insights. The forthcoming solutions will leverage DataRobot’s automate machine learning processes to rapidly deploy models into production analytics within ThoughtSpot. The automatically generated predictive insights will be available to anyone through a simple search experience. It will enable data-savvy business analytics professionals to rapidly build, test, and deploy machine learning models, applying them to business data, and use search to surface relevant predictions.
- Delivering AI-power analytics in multiclouds: Multicloud computing is becoming more prevalent as enterprises combine their investments in public, private, hybrid, and edge cloud offerings. To address these requirements, ThoughtSpot announced its partnership with Google Cloud Platform (GCP). It has certified that its in-memory calculation engine Falcon and new v5 platform can run on GCP, certification of its v5 platform on GCP, and general availability of this deployment option. ThoughtSpot has integrated Falcon with GCP’s Machine Learning Engine to enable merger of search-driven analytics and data science workflows. This integration improves pipeline efficiency for data science teams, while making insights derived from data science searchable in seconds within ThoughtSpot’s solutions. Data science teams can quickly test and deploy Google Cloud Machine Learning Engine algorithms and incorporate them into their data models. The vendor also announced that it is deepening existing support for Amazon Web Services and Microsoft Azure. It enables enterprises to analyze data across their public cloud, private cloud, and on-premise environments.
Wikibon sees solutions such as ThoughtSpot as forerunners of the next wave of BI solutions that deliver “anticipatory intelligence” in every cloud application. What this refers to is any solution that leverages AI in any of the following use-case scenarios:
- Anticipatory devices: Devices will leverage embedded AI to anticipate what users are trying to do and help them take those actions faster or in an automated fashion.
- Anticipatory conversations: Conversations will tap into natural language processing AI to anticipate what users are trying to say and help them communicate their intent more rapidly and effectively.
- Anticipatory contexts: Apps will use self-learning adaptive AI to anticipate the dynamically shifting contexts and intents of users’ engagement.
To the extent that AI applications drive their predictions from deep historical data and continuously optimized statistical models, users will treat them as a natural adjunct of our organic intuitions. ThoughtSpot delivers these capabilities in diverse public, private, hybrid, on-premise, edge, and embedded scenarios. It’s clear to Wikibon that this visionary vendor, through its platform evolution and partnerships, is actively driving its AI-infused next-generation BI into all of these opportunities.
