The product vision of Ask Bigger

Bringing to life the product vision of Ask Bigger today & for tomorrow 

Over the past couple of years, my colleagues and I have met with dozens of organizations worldwide to discuss their data needs.

What we noticed, rather quickly, is that we are hearing the same thing over and over – across every industry and in every region. Namely, what everyone is looking to do is to Ask Bigger questions from their big data and to get answers fast. But this task is just too challenging to undertake. 

For example, a leading manufacturer in APAC told us that they need to get insights from their data on the very same day it is being created. They generate dozens of new terabytes from the production floor every day. And being able to get timely answers from this data is critical for preventing product faults and defects. But same-day insights is simply too ambitious.

Another example comes from a conversation we had with a data engineering team lead at a global tier-1 Telecom. She told us that they need to be able to leverage their data to figure out how network quality is impacting customer churn. She said that they are running queries on datasets that are too big. The result is that they can’t get the insights they need when they need them.

What it’s all about (for me)

This is why I’m such a firm believer in the SQream Ask Bigger vision. For me, as VP of Product, enabling organizations to Ask Bigger is about solving these challenges with a solution that enables them to get strategic insights from big data fast. 

It’s about empowering them to maximize the value they get out of their data by enabling them to run more complex queries on more data, to get answers when they need them (even on the same day!), and to do this on data wherever it is and in whatever format it’s stored. 

In other words, to Ask Bigger, you’ve got to be able to dig deeper, go faster, and reach anywhere. which is aligned with the offering that we designed

• Deal with your most complex SQL queries, joining as many dimensions as you wish, and concluding all your relevant data.
• Running analytical queries five times faster and preparing your data at the remarkable rate of 5TB/hour per machine.
• Both on-premise and native-cloud offerings, for any size of dataset and any type of use case.

Designing the future of Ask Bigger 

To make sure that any organization can be ready for the data challenges of tomorrow, some of the developments we are working on today include:

• Reducing MLOps latency to go deeper by enabling the fastest environment for ML data preparation when using the same GPU (In-database machine learning) for analytics MLOps. Read more about it here
• Improving performance and resilience to go faster by parallelizing all statements over multiple instances, while assuring no single point of failure.  
• Enabling more formats and greater flexibility for data anywhere by supporting table formats such as Iceberg and Hive and connecting to additional ecosystems (such as, Kafka, Spark, and Presto), while operating as a data lakehouse on top of any cloud storage. 

Our inspiration 

SQream anticipated the need to Ask Bigger with big data analytics over a decade ago. As our company grew and evolved, our vision of the future had become reality. Data is not only big today, it’s massive – and for all types of organizations, both large enterprises and SMBs. Analyzing all this data, in its entirely, is a tremendous challenge.

Helping these organizations overcome the challenge is our inspiration. This is what fuels our drive to continue innovating every single day, so that every organization anywhere in the world and in any industry can always get at those (seemingly) unachievable insights and answer what used to be off-limits questions.