Tellius recently announced that the company has been named a Visionary in the 2022 Gartner® Magic Quadrant™ for Analytics & Business Intelligence Platforms — a rigorous independent evaluation of the top 20 analytics software vendors. It is our first time in the report, and we are honored by this recognition.
So, what exactly is Tellius?
This blend of capabilities helps organizations go beyond dashboards to gain comprehensive insights without relying on data experts — making ML/AI accessible to business and analytics teams — ultimately accelerating data-driven decision making.
How did we get here?
While other BI platforms are bolting on augmented capabilities to their legacy platforms, we built — from the ground up — a platform that delivers a seamless user experience blending analytics and artificial intelligence capabilities.
We believe we were named a Visionary because of our vision of building a unified platform that enables anyone, regardless of their analytical skills, to get insights into “what” is happening, “why” metrics changed, and “how” to improve business outcomes at cloud scale.
This post is to share how Tellius came to be, the journey taken to the land of giants, and where we’re going next.
The Shifting Landscape
The Magic Quadrant™ has many vendors. It is an honor and humbling to stand amongst them.
But the land beneath everyone’s feet is shifting. Two worlds — Analytics/BI…and Data Science — are colliding. New analytics vendors are emerging in the space between.
The Dream
When Tellius was founded six years ago, “Decision Intelligence” was not a term, nor was there a widely recognized notion of “Augmented Analytics”.
We were simply obsessed with solving a big problem: the artificial divide between tools designed for business teams, data analysts, and data experts which caused friction.
- Business users used drag-and-drop tools for visual exploration like dashboards and reports to identify what is going on (descriptive analytics) but relied on analysts to get to why behind the what
- Analysts had SQL/Python, Excel pivots, and BI to answer questions around why KPIs are changing (diagnostic analytics), but still relied on data experts to go deeper
- Advanced analysts and data scientists had notebooks, advanced Data Science (DSML) tools, and statistical techniques to identify the deeper why and how (predictive/ prescriptive analytics)
Increasingly complex business environments mean increasingly complex questions asked from granular data. But it all takes too much time and effort. Handoffs and inefficiencies abound. Current tooling was designed to answer pieces of the problem, not the whole thing (what, why, and how). The analysis is delayed, produced too late to be useful, and decisions are still far too frequently made by gut and heuristics.
Our dream was simple: unite users and analytic approaches in a seamless analytics experience so anyone can answer business questions with data. Bust the silos between BI, data analysis, and data science. Build a unified modern analytics layer that overcomes the artificial divides between technical and non-technical users to uncover deep business insights at the cloud scale.
We have come a long way as a platform and as an industry and I am extremely proud of what we have accomplished so far as a team.
The Journey
A key early challenge to overcome was building the right technology architecture. We wanted to build a product that did not compromise – it had to handle customer’s data no matter where it resided, provide deep insights across many use cases, and be a delight to use for business people and data experts alike. We needed a foundational architecture that was different.
Dual Analytics Engine
We set out to deliver the best of both worlds: blazingly fast columnar-based compute engine for highly performant ad hoc search and visualization, combined with a robust distributed-compute ML engine.
This was the genesis of our purpose-built dual analytics engine that powers all aspects of the Tellius platform today. It works in two main modes:
- Live mode for pushing down queries within cloud DWs such as Snowflake and Google BigQuery without moving the data
- In-memory mode for processing data for deep insights and ML models not supported by cloud DWs as of today
Yay! Problem solved. Now to conquer the world, right? Wrong. Solving the architecture piece was only the beginning of our journey…
Comprehensive Insights
While our dual analytics engine is one part of the secret sauce, intelligent automation and augmentation to uncover insights is the other part.
Tellius’s Automated Insights are the most comprehensive on the market today. Our Insights engine automates complex data analysis to uncover root causes, understand key business drivers, compare cohorts, and identify meaningful segments in data, going beyond first-order facts/drivers.
Instead of incrementally improving pieces of the analysis layer separately, our approach is a single platform optimized for seamless transitions between ‘what’, ‘why’, and ‘how’-type questions to short-circuit the analytics layer and drastically cut down the frustrations and time between questions and answers; people, analysis modes, and technologies.
OK, differentiated insights, powerful engine, intelligent automation. Anything else?
Natural Language Queries (NLQ)
Data exploration and ad-hoc analysis is critical to decision making. Natural Language Query (NLQ) allows any user — regardless of data skills — to flexibly explore and analyze terabytes of unaggregated enterprise data in plain English, democratizing exploration and analysis by making it as simple/intuitive as a Google search.
Well, we can’t ignore data prep and transformations. Can we?
Data Prep and Transformation
Data is the bedrock underlying analysis and insights for better decisions. Modern insights-driven decisioning requires blending data, developing metrics/calculations, and flexibility to add new sources or metrics as analysis evolves. Tellius offers low code/no code capabilities to clean and transform data while providing full support for SQL and Python for custom business logic and calculations.
Multi-Persona
Recall the dream was for anybody to answer complex business questions. This means making the platform as
- easy to use as a consumer app like Google or Yelp, yet
- flexible enough for power users
That’s exactly what we did with Tellius. You can do everything from quickly visualizing “sales in the Northeast in Q3” to creating a predictive model that’s fully programmatically controlled and accessible via APIs or embedded in a 3rd party app, all in Tellius, all for one price, no user limitations.
How Does it All Fit in the Modern Data Stack?
While there has been a lot of innovation in the modern data stack, the analytics consumption layer for Modern Data Stack is fragmented with tools designed based on the individual skill set (Analysts, business users, citizen data scientists) and the type of analysis being performed.
We envision this new modern unified consumption layer will give superpowers to business analysts and users with an ability to do ad-hoc data exploration using natural language, uncover deep insights, and create ML models with ease to solve complex business problems at cloud scale, while providing flexibility to bring SQL, Python code for customization as needed.
As the modern data stack coalesces around a handful of ELT players powered by cloud infrastructure, the analysis layer remains stubbornly fractured. We see Tellius solving this critical last-mile of the analytics value chain.
What Does it Mean for Our Customers? Faster Decision Intelligence at the Fingertips
Tellius customers are solving business problems at massive scale for countless use cases. With Tellius, the journey from data to decisions is easier than you may think. Tellius meets you where you are to up your analytics game.
You might be a global enterprise with 1000s of business users breathing down your analytics team’s neck for more dashboards, more reports, and deep insights RIGHT NOW. Tellius democratizes data exploration of granular data to business users in a code-free Google-like experience. You can slash your backlog by empowering true self-service ad hoc exploration and analysis.
You might be looking for greater speed to insights by leveraging automation. A global food & beverage firm was able to create 360o shopper profiles 10x faster with 90% effectiveness rating to optimize/ target promotions, resulting in multi-million dollar revenue impact.
You might have a solid analytics team but have a desire to supercharge your analysis by analyzing all the variables (not just the handful you have time to compare). Tellius’s comprehensive automated insights help you leapfrog analysis, to go deeper faster.
What’s Next?
Today’s recognition by Gartner is exciting, validating, but also only the beginning.
We will continue to invest in our core competencies of empowering data consumers and data creators to easily and flexibly scale the impact of their analytic efforts to drive insights-driven decisions.
We are committed to continued innovation and pushing the boundaries of what’s possible once siloes among people and tools are broken and the barrier to analysis is finally lowered for everyone to participate.
We hope you will join us on our journey to a world of better, faster insights-driven decisions. Sign up for a free trial at Tellius.com or download the report here.
Gartner “Magic Quadrant for Analytics and Business Intelligence Platforms,” 22 March 2022, Austin Kronz, et. Al
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Written by: Ajay Khanna,
Founder and CEO at Tellius
