We’re thrilled Gartner recently recognized Tellius as a Visionary yet again in the 2023 Gartner® Magic Quadrant™ for Analytics & Business Intelligence Platforms! We think If THIS doesn’t cement our place in your mind as an innovative analytics vendor, I’m not sure what will. 😉
Jokes aside, in this blog post, we’ll explore why we believe Tellius was named a Visionary and what it means for our customers.
First, what does Tellius do?
We make it dead simple (and fast!) to bring all your data and analytics to the party. 🎉
Any user can ask questions across billions of records via a Google-like interface; understand “why” metrics change via automated insights that surface hidden key drivers and trends; and get predictive recommendations—all in a self-service manner, expediting speed to insights and ultimately deriving better business-impacting decisions.
Tellius enables no-code ad hoc analysis; automated insights and anomaly detection; and business-friendly advanced analytics in an analytics platform designed for cloud-scale, while playing nicely with a variety of data sources and business systems:
- Business users 💜 how accessible and easy we make getting answers from data.
- Analysts 💜 how we supercharge their work, helping them identify hidden insights.
- Experts 💜 how we automate their grunt work and enable others to answers their own questions.
OK, why do we think we were recognized as a Visionary?
The Gartner® Magic Quadrant™ for Analytics & Business Intelligence Platforms assesses 20 vendors’ Strengths and Cautions. The vendors are evaluated on the basis of their Completeness of Vision (X-Axis) and Ability to Execute (Y-Axis). In our opinion, recognition in the Visionaries Quadrant is an honor considering today’s super-crowded analytics landscape. We believe being named a Visionary means that Tellius has demonstrated an innovative approach to analytics that sets us apart from other vendors in the market.
So, what do you think exactly sets us apart? Glad you asked. 🙂
- 💪True Self-Service Analytics at Scale: Decision Intelligence is the missing piece of the self-service analytics puzzle. It provides users with the ability to generate insights automatically without requiring extensive knowledge of data science or statistical analysis. By integrating AI and machine learning algorithms into our analytics platform, we’re providing a level of automation that is unmatched by traditional self-service analytics tools so anyone can actually answer their own questions, rather than proliferate dashboard sprawl and contribute to analytics backlogs that the last decade of self-service analytics initiatives has largely resulted in.
- 🦾 AI-Powered Analytics Throughout: At Tellius, we do more than just pay lip-service to augmented analytics. We embody it. From day one, we have been integrating AI augmentation throughout the platform in visible and invisible ways—from detecting data types to seamless natural language-based data exploration and autoViz to predictive modeling and data storytelling, our platform is designed to help users leverage AI to generate insights at every stage of the analytics process. Our AI augmentation saves users time, reduces the risk of errors, and enables any user—regardless of technical acumen—to make better decisions faster by automating routine tasks and providing insights that would be difficult or impossible to generate manually. AI augmentation powers true self-service analytics mentioned above. 👆
- 🧘 Analytics Agility: Finally, our platform is designed for analytics creators and consumers to collaborate for quicker analytics iteration. This is possible because our platform’s architecture is based on a unique dual-analytics engine that enables sub-second queries of billions of datapoints, coupled with a robust distributed compute engine for scalable predictive analytics—all in one platform, with seamless switching between analytics modes. By integrating BI’s visualization, dashboarding, reporting, and monitoring with data science platform’s advanced analytics techniques such as machine learning and predictive modeling, our platform enables all users to rapidly move through discovery and answering questions, into deep or complex data analysis, to generate insights quickly and easily. This reduces switching costs, improves efficiency, and promotes collaboration amongst business users, analysts, and data experts.
Cool. But what’s all this mean for me?
Let’s bring this back to earth and talk about some real examples of our platform driving value.
Pharmaceutical & Life Sciences. The sales operations team at a pharmaceutical firm was struggling to effectively target the right healthcare professionals (HCPs) for their newly launched rare cancer treatment. The drug was only applicable to a specific patient at a specific period in their treatment cycle, so identifying relevant HCPs was a “needle in a haystack” challenge. Cold calls and office visits were infeasible, and manually sorting through vast amounts of third-party claims data to identify the right HCPs was time-consuming and labor-intensive and was leading to inaccurate targeting and wasted resources. The client’s sales team used Tellius—without any data scientists—to join internal and external prescriber datasets, upon which they trained an ML-based HCP targeting model. The model helped the team identify 30% new sales opps, driving multimillion-dollar revenue by putting lifesaving drugs into the hands of the right patients, all while significantly reducing the time and resources required for targeting and optimize targeting efforts.
CPG. A global consumer goods company wanted to optimize its product pricing strategy to better match customer demand and maximize revenue. They had previously relied on manual analysis and historical sales data to set prices, which often resulted in suboptimal pricing decisions and missed revenue opportunities. The firm used Tellius to proactively track customer demand data across various channels, including social media and e-commerce platforms. This allowed the company to make more informed pricing decisions based on real-time market data. The firm was able to increase revenue by 5% by optimizing its pricing strategy to match customer demand.
Finance. A global investment bank wanted to improve its risk management processes by better predicting market volatility. The company had previously relied on traditional statistical models and historical market data to make risk management decisions, which often resulted in inaccurate predictions and increased financial risk. They now analyze real-time market data, including social media sentiment and news articles, to better predict market volatility and inform risk management decisions. The investment bank was able to reduce its financial risk exposure by 20%, resulting in improved profitability and increased investor confidence.
In each of these scenarios, traditional BI tools and manual SQL slicing/dicing or Excel pivoting were not able to handle the disparate data sources and dataset sizes, nor pinpoint key drivers and advanced analytics that the Tellius platform could.
For us, recognition as a Visionary in the Gartner® Magic Quadrant™ for Analytics & BI Platforms for two years running is a significant milestone for our company. We’d like to take a moment to thank several people:
- First and foremost, to our customers, whose own vision to augment their analytics drives our vision forward.
- To our employees, who pour their heart and soul into the work every day and have propelled this product to new heights.
- To our investors, whose faith in our mission/vision and doubling down with us in this tough macroeconomic environment is underneath.
Upwards and onwards! 🚀🚀🚀
Gartner, Magic Quadrant for Analytics and Business Intelligence Platforms, 6 April 2023, Kurt Schlegel, et al.
Gartner, Market Guide for Multipersona Data Science and Machine Learning Platforms, 2 May 2022, Pieter den Hamer, et al.
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