Interview With Tarik Dwiek, Director of Technology Alliances at Snowflake

Dataiku Company, Scaling AI Catie Grasso

Upon engaging in a strategic partnership earlier this year, the teams at both Dataiku and Snowflake have continuously untapped new ways to drive value for organizations as they aim to build robust, end-to-end data science workflows and accelerate their data science and AI initiatives, infusing agility and collaboration along the way.

Recently, Dataiku achieved “Elite Partner” status from Snowflake, signifying another important moment in time for the partnership. We sat down with Tarik Dwiek, Director of Technology Alliances at Snowflake, to hear more about the recognition, as well as the current state of cloud adoption — key trends, benefits, challenges, and more. We hope you enjoy the discussion!

Catie Grasso: In your opinion, what is the value for organizations today in moving to the cloud?

Tarik Dwiek: Hopefully, most organizations in the year 2020 are bought in, if not all in, on the cloud. The cloud is that change agent for digital transformation and for gaining significant competitive advantages, so leveraging the cloud has become key for delivering the strongest user experiences and improving overall business efficiencies. Customers have told us they want to be able to take advantage of things like agility to make quicker and better business decisions. They want to realize the cost benefits and the scale associated through leveraging the elasticity of cloud resources and they want to achieve the best use of data and analytics in order to increase innovation.

CG: I think that absolutely makes sense. We hear a lot today about this notion of agility and hyper-agility specifically in the post-COVID environment, so I think that's a really hot topic for a lot of organizations right now. Next, what are some of the trends you’re seeing when it comes to cloud adoption?

TD: Let me highlight three or four key ones that we’ve been seeing. First, a multi-cloud strategy is becoming more standard because customers want to remain independent and avoid lock-in as they leverage the major cloud providers.

Cost optimization is another big one, as companies want to understand how to use the cloud most effectively and manage the cost of that usage.They're building this appetite for consuming applications as a service because they want to pay for just the resources that they use, so they want to be able to adjust to that demand without having to over or under provision.

Another trend is that customers want secure and governed access to data. Now that the cloud is opening up the ability to manage data at scale, these customers see both the opportunity and the critical need to enable data governance at scale.

And, of course, the most relevant trend to our discussion here is leveraging AI and machine learning in the cloud. If organizations can achieve those cost and scale optimizations for capturing and managing all of their data, they can start to realize the full potential of AI and machine learning at enterprise scale.

With COVID-19 and with the world moving to a remote workforce, there are more users engaging online. It’s becoming even more critical to take full advantage of capturing all of that engagement at scale and optimizing from there. We're starting to do things together at Dataiku and Snowflake around COVID-19 data — we did a joint initiative around accessing a COVID-19 dataset on our Snowflake Data Marketplace and identifying patterns that could drive decisions to improve recovery. We’re seeing that some customers that were on the fence about moving to cloud have now accelerated all of their cloud initiatives due to COVID-19.

CG: What would you say are your customers’ biggest challenges when they come to your team at Snowflake?

TD: Time and time again, customers are struggling with data management challenges that are caused by silos of data that have been built up through the last few decades (i.e. if it's a big enterprise that has made multiple acquisitions and built a bunch of different systems). We see that they're spending up to 80% of the time trying to find and integrate the data instead of extracting the gems of value hidden in this data. This is slowing down or preventing them from achieving that disruptive transformation so that they can innovate and gain market share. To me, these are the challenges that Snowflake and Dataiku were built to solve.

CG: Absolutely, we hear about that a lot. Siloed data and siloed teams often lead to non-optimal outcomes, so by breaking down those silos, whether it's through a tool, team restructuring and reorganizing, process-driven changes, or a combination of these, I think that's spot on and speaks to the value that both companies bring to the table. For the next question, what role do you see data science and machine learning platforms playing in the move to the cloud?

TD: Data science and machine learning platforms are already playing a key role in this move to the cloud. We’re seeing a shift from a business intelligence-centric world to an artificial intelligence-centric one. We’re also noticing a shift to cloud and data science platforms that enable automation and self-service capabilities to empower users of all skill sets and all levels to become data and AI driven.

Specifically, we're seeing customers accelerate these AI initiatives for use cases such as process automation to streamline business processes, which improves service delivery and quality and helps contain costs. Personalization to gain the closest customer experience in this age of high customer expectations, especially with the impact of COVID, is crucial. Then, things like fraud detection come into play, not just in financial services companies, but for all organizations. How do they prevent and gain trust with customers by making sure that they minimize risk for their customers accessing data?

Cloud is allowing this sourcing of data at scale and importing and processing datasets from a variety of sources that normally would be too large and costly to store on premise. So all of this is leading to this great synergy with data science platforms becoming more and more mainstream, such as Dataiku, which allows enterprise-scale AI projects and initiatives to actually be completed, be successful, and be deployed into production.

CG: Snowflake and Dataiku launched an official partnership in early June. What are you most excited about regarding the future of the partnership?

TD: So many things, what am I not excited about? Both Dataiku and Snowflake share a common vision to help customers unlock the value of their data. Both companies want customers to take full advantage of data democratization and empower everyone within the organization to be AI driven. We're both removing the barriers of entry to successfully launch enterprise-grade AI projects by removing the complexity and taking full advantage of the benefits of the cloud so customers can easily and quickly build enterprise-scale AI solutions.

Within the concept of collaboration (a big one for Dataiku) I'm excited about some of the things we're working on to leverage and differentiate our offerings, with Snowflake’s Data Marketplace as an example. Dataiku built this platform that combines collaboration, automation, and ease of use to empower business users, business analysts, data scientists, data engineers, and more. Analysts and business users can leverage automation to take advantage of things like data exploration and uncover patterns on large datasets without needing advanced coding skills.

Data scientists and data engineers can be working on innovating and differentiating the business instead of the minutia of repetitive data management. Both of us, Dataiku and Snowflake, are seeing this positive impact across a vast number of customers and differing industries are taking advantage of our joint solution. That's what excites me. We’re just scratching the surface on the success of this partnership.

CG: Dataiku recently achieved “Elite Partner” status from Snowflake. Can you shed some light on what this recognition entails?

TD: Partners are critical to Snowflake’s success and we wanted to create a program which provides our partners with the tools and resources to develop and deliver world-class solutions. The elite tier within our program is our top tier and identifies our most strategic partners where we're both fully investing resources to deliver unique and compelling business solutions. With Dataiku recently becoming elite, it further demonstrates the focus on us jointly delivering cloud-ready enterprise AI solutions to the market.

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