We’re thrilled to be included as a recommended solution in Gartner’s latest report titled Hype Cycle for Data Science and Machine Learning. Focused on innovation and next-gen data science platforms, the Hype Cycle educates analysts, heads of data teams and chief data officers about solutions and platforms they should know about.
For years, Panoply has developed an industry-leading data warehousing solution that’s enhanced and infused with machine learning and artificial intelligence to automate day-to-day warehouse management and deliver lighting-fast results via self-optimizing queries and more.
In the Gartner report, our product vision and customer’s reality is validated when Gartner recommends solutions that uses machine learning in their products and for leaders to pursue ML-enabled features as a ‘must-have’ in platform viability.
To reiterate, according to Gartner, data platforms that don’t have machine learning capabilities at multiple levels in the product shouldn’t be used or even considered by data decision makers
“We’ve built Panoply from day one with machine learning at the forefront of our self-optimizing data warehouse solution”, says Panoply Co-Founder and CEO Yaniv Leven. “We’re happy to see Gartner excited about what ML and artificial intelligence can do for data analysts and professionals.”
Putting our machine learning to use, Panoply customer Bob Vermulen at Shinesty says, “An attractive feature of Panoply was the way the warehouse learns and optimizes our queries in an automated fashion. We had zero performance issues and the more times you re-run a query, the faster it comes back. That means I don’t have to spend time creating indexes and trying to optimize the queries myself.”
Why is machine learning important in a data platform? Gartner says it aids in automation, optimization and merging, boosts data quality and lessens the need for a dedicated database administrator or data team.
We’re humbled to be listed as a leading vendor for cloud data warehouses and can’t wait to tell you more about our product.