Today we’re excited to announce the public beta launch of Continual, the first operational AI platform built specifically for modern data teams and the modern data stack. We’re also announcing our $4M Series Seed, led by Amplify Partners, and joined by Illuminate Ventures, Wayfinder, DCF, and Essence, as well as new partnerships with Snowflake and dbt Labs.
Enterprises using Microsoft Azure can now deliver secure, automated data pipelines while boosting compliance with privacy and industry mandates using Fivetran Business Critical.
For decades, the technologies and systems that deliver analytics have undergone massive change. What hasn’t changed, however, is the goal: using data-driven insights to drive actions. Insight to action has been a consistent vision for the industry. Everyone from data practitioners to technology developers have sought this elusive goal, but as Chief Data Strategy Officer Cindi Howson points out, it has remained unfulfilled — until now.
Over the course of my next two blog posts, I would like to share my thoughts around a debate raging in data architecture circles. The bone of contention? That the 21st century needs a new data management paradigm for modern analytics. First up, I’ll frame the argument and explain the two prominent approaches of data hub and data fabric. Then, I’ll cover data mesh and compare all three architectures. As always, I’d love to get your input, feedback, queries and comments!
The following is Part III of a three-part series. Welcome to the final installment of a three-part series discussing the areas to take seriously when you want to drive business with analytics. In Part I of this series, I discussed how to prioritize data accessibility and how to address the challenges that come with it. Those challenges include: Part II discussed where the disconnect is and addressed how organizations can bridge the gap.
