By Jenna Boller, Director of Marketing at Ocient
Big Data LDN reached a record number of attendees this week with over 13,500 registered guests gathering at the Olympia in London to discuss all things Big Data. The conference featured over 200 sessions and several vendors across data analytics, observability, governance, business intelligence, and more.
In addition, Chris took to the stage along with Mike Ferguson (Intelligent Business Strategies), Benoit Dageville (Co-Founder and President of Products at Snowflake), Shinjin Kim (Founder and CEO at Select Star), and Tomer Shiran (Co-Founder and Chief Product Officer at Dremio) for the flagship keynote panel, the Great Data Debate.
How the post-pandemic economic slowdown is impacting data and analytics
Mike Ferguson opened the debate asking the panel about the fate of data and analytics priorities among customers during our current economic downturn. Across the board, the panelists are seeing growth in data and analytics projects looking to streamline and optimize current business operations and identify new growth opportunities powered by data.
Benoit Dageville touched on Snowflake’s recent earnings announcement which outperformed market projections and signaled strong growth for the industry despite the downturn.
Chris Gladwin noted that the slowdown is coming off an historic high, with the pandemic accelerating digital transformation and therefore catapulting customers towards more data to be analyzed than ever before.
Shinjin Kim suggested that while companies may slow hiring, they will look towards automation, AI, analytics, and more to streamline business processes, make current employees more efficient, and automate repetitive tasks.
The economics of working in the cloud at scale are driving doubt and reconsideration of on premises deployments
After addressing general growth within the industry, the panel moved on to discuss how the jump to cloud computing is demonstrating to be expensive at scale.
For Benoit, the opportunity to scale data analytics in the cloud is limitless. He talked about the benefits of a cloud-based infrastructure, elasticity, and ability to isolate compute for workloads.
That’s all well and good for organizations with infinite resources, however, at hyperscale, cloud costs may quickly get out of control. In other sessions at Big Data London, we heard jokes about analysts and data scientists going to lunch and “forgetting to turn their queries off.” Needless to say, they come back to a large bill.
The idea that organizations are starting to look at the cost per query which begins to show how the scale of queries may quickly become cost prohibitive rather than limitlessly scalable.
Chris Gladwin talked about Ocient’s ability to scale infinitely at a predictable cost by leveraging our Compute Adjacent Storage Architecture™ (CASA) to condense compute and storage into a single tier connected by the PCI lanes and unleashing hundreds of millions of parallel tasks per second.
The conversation then shifted to data governance and the importance of planning and managing growing workloads to ensure the organization is not leveraging the scale and elasticity of the cloud without balancing cost.
Data warehouse development and the shift from monolithic applications to microservices
As more legacy solutions reach end of support, the panel of modern data and analytics leaders discussed the growing number of tools and services available in the cloud to organizations in need of robust operations and internal services powered by data. From data catalogs to data marketplaces, data observability to data governance, the panel essentially aligned with the varying exhibitors at the event.
And while modern data warehousing is alive and well, there are more players to consider across data lakes (Databricks was a Diamond sponsor at the event alongside Snowflake), lakehouses (like Dremio), Ocient going after the high end of hyperscale workloads, and more.
Perhaps the most important topic of discussion for the panel and on the show floor at Big Data London was how to enable more lines of business across the enterprise to leverage more of their data. Making data available across siloes, managing data from a centralized point of view without acting as a bottleneck, empowering various departments with tools and pipelines to innovate and drive their functions. These were tackled throughout a range of case study sessions, the panel, and in the individual conversations we had across the two days.
We had a sizable amount of conversations about leveraging third party data to enrich first party data. From climate and weather data to economics to more. And from private equity to manufacturing to banking to retail. The desire to grow massively in data and analytics even during an economic downturn was clear, and the ability to leverage additional services and technologies to unlock value from data at scale is critical.
The future of data science and analytics
To close out the panel, Mike Ferguson asked the group to share their predictions about the future of data science and business intelligence. Of course, there was no doubt that the industry will only get bigger, even as automation and new tools increase productivity and drive efficiencies.
Gladwin said that leveraging hyperscale data warehousing technologies like Ocient will enable organizations to work “better, faster, and cheaper,” but at least 80% of the use cases will bring new capabilities that were previously infeasible with legacy systems. He predicts the industry is at the beginning of a 10-year lifecycle in disruptive new technologies powered by the latest advances in modern hardware. For companies like Ocient, this means running software as fast as the hardware can go and maximizing every single ounce of performance from industry standard drives, networking, and CPU cycles.
One thing the panel didn’t mention is the diversity of ideas and creativity laying in wait for this industry. Several university students attended Big Data London. From film makers to psychology students, those interested in pursuing careers in data and analytics were just your typical tech-focused students. The combination of disruptive technology and growing awareness and interest in data and analytics among the next generation of talent in this field bodes well for the industry. It’s no surprise the conference is growing both in sponsors, in speakers, in attendees, and in reputation.
We had a great time meeting with some of the world’s top brands at Big Data London. I invite you to check out the full panel discussion and let us know what you think of the Great Data Debate.
Ocient CEO Chris Gladwin on stage at the Big Data London flagship keynote panel with Mike Ferguson, Benoit Dageville, Shinjin Kim, and Tomer Shiran