Nika Tamayo Flores, Product Lead at Railsware, brings a wealth of experience building data-driven products. She dives into the transformative power of conversational analytics, contrasting it with traditional static dashboards. Nika discusses the integration of AI into data analytics, emphasizing how it enhances understanding and user experience. She shares challenges faced during implementation and reveals how AI Insights in Coupler summarizes data and suggests actions. Nika also suggests that conversational analytics will complement, rather than replace, existing BI dashboards.
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insights INSIGHT
Data As A Two-Way Conversation
Conversational analytics turns static dashboards into a dialogue you can ask questions of in plain language.
It meets users where they are and reduces the need for technical skills like SQL or pivot tables.
insights INSIGHT
Shift From Access To Understanding
Pre-AI analytics focused on democratizing access and automating data extraction tasks.
AI-era analytics focuses on democratizing understanding by surfacing insights, recommendations, and actionable next steps.
volunteer_activism ADVICE
Handle Context Limits And Trust Upfront
Overcome model context limits by sending schema and a small sample of rows, then let the model write queries you run on full data.
Address trust, cost, and safety by explaining data handling, managing quotas, and providing opt-out options for model training.
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Today, we are another episode in our series, sponsored by our good friends at Railsware. Railsware is a leading product studio with two main focuses - services and products. They have created amazing products like Mailtrap, Coupler and TitanApps, while also partnering with teams like Calendly and Bright Bytes. They deliver amazing products, and have happy customers to prove it.
In this series, we are digging into the company's methods around product engineering and development. In particular, we will cover relevant topics to not only highlight their expertise, but to educate you on industry trends alongside their experience.
In today's episode, we are speaking with Nika Tamayo Flores, Product Lead at Railsware, specifically for the Coupler product. She's been leading complex data-driven products for over eight years, and will enlighten us on conversational analytics, and how they can change a data focused product.
Questions:
Before we jump to the topic, let’s define what exactly conversational analytics is. How does it differ from traditional dashboard-based data analysis?
You’ve been integrating AI capacities into Coupler, Railsware’s product focused on data analytics. How would you describe data analytics in pre-AI and AI era?
What were the key challenges to embedding conversational analytics into Coupler?
And what’s the result? You’ve already released AI Insights – how do they transform user experience for data exploration?
How do you ensure conversational analytics provides accurate and reliable insights?
How does conversational analytics change who can be a "data user" in an organization?
What's the learning curve like for organizations adopting conversational analytics?
Where do you see conversational analytics heading - will it eventually replace traditional BI tools, or complement them?
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