Rabab Zehra, Executive Editor of TECHx Media, sat down with Sid Bhatia, Regional Vice President – Middle East & Turkey at Dataiku for a Special Feature on ‘Bridging The Gap Between Technology And Business,’ to learn more about the role Dataiku plays in empowering businesses during the ongoing wave of digital transformation.
TECHx: Could you please tell our readers about the recent initiatives you’ve taken to use data science and AI to empower individuals & enterprises?
Sid: The Dataiku Middle East customer base is growing very aggressively. Regionally, we are working with top tier organizations in the Telecommunication, Financial Services, Manufacturing, Oil & Gas & Large Public sectors that are focused on moving beyond talking about AI/ML as buzzwords and are instead laser-focused on finding practical use-cases for the technology, in a way that is collaborative and sustainable for the long term, and creates true business value.
While business value creation will ultimately end up looking different at every organization, at its core, business value comes from making key processes and functions better, faster, or more cost-effective. We are actively helping organizations connect the dots between accelerating their AI maturity and generating value, both of which will pave the way for additional use cases and knowledge sharing to enhance democratization and enterprise-wide adoption.
To ensure that the focus remains on generating impactful business outcomes for our customers using our data science and AI platform, Dataiku makes significant investments in customer service and experience. As a matter of fact, as part of the Data Science team, a Customer Success Manager (CSM) is engaged with clients to understand their goals and match these with Dataiku capabilities to drive business value. The CSM acts as a trusted advisor to foster not only adoption of the software but also appropriate and productive uses of the product’s features. Also, in order to cater to the growing customer base, we are building out our team and each quarter we are onboarding niche roles ranging from Data Scientists, Implementation Managers and Field Engineers to Customer Success Managers and Solution Engineers. We are also growing our sales & partner teams based out of our Dubai Office, which serves as the HQ for Middle East & Turkey.
TECHx: Dataiku was positioned as a Leader by Gartner for Data Science and ML Platforms in the 2021 Magic Quadrant. What is your company’s most distinguishing feature that sets it apart from competitors?
Sid: Dataiku is supporting agility in organizations’ data efforts via collaborative, elastic, and responsible AI, all at enterprise scale. At its core, Dataiku believes that in order to stay relevant in today’s changing world, companies need to harness Enterprise AI as a widespread organizational asset instead of siloing it into a specific team or role.
To make this vision of Enterprise AI a reality, Dataiku is the only platform on the market that provides one simple UI for the entire data pipeline, from data preparation and exploration to machine learning model building, deployment, monitoring, and everything in between.
Dataiku was built from the ground up to support usability in every step of the data pipeline and across all profiles — from data scientist and cloud architect to analyst. Point-and-click features allow those on the business side and other non-coders to explore data and apply AutoML in a visual interface. At the same time, robust coding features — including interactive Python, R, and SQL notebooks, the ability to create reusable components and environments, and much more — make data scientists and other coders first-class citizens as well.
The commitment to openness and flexibility in Dataiku doesn’t stop there. Because each company’s path to Enterprise AI looks different, Dataiku supports the creation of a spectrum of applications, whether that means building out a self-serve analytics platform or fully operationalized AI integrated with business processes.
No matter what the underlying changes in architecture or advancements in technology, Dataiku remains at the center — the cornerstone of data governance and responsible AI. Dataiku continuously integrates the most recent technologies in its stack in order to lower the barrier to integration for the companies themselves. These include computation, storage, programming languages, machine learning technologies and more.
Dataiku’s centralized, controlled, and elastic environment fuels exponential growth in the amount of data, the number of AI projects, and the number of people contributing to such projects. The platform was built to scale as businesses strive to go from a handful of models in production to hundreds (or thousands). The bottom line is that Dataiku is built for every industry, every use case, and also for everyone.
Finally, I would like to add that Dataiku’s focus on project and customer success is the real difference. We are committed to ensuring that companies achieve positive business outcomes through their engagement and interaction with our product, and our customer success team does this by interacting regularly with and understanding each individual enterprise’s unique needs. We want to highlight the incredible work of Dataiku’s Customer Success team and show what role they play in the day-to-day data science efforts of our customers.
TECHx: How can Dataiku support organizations in their digital transformation endeavors by bridging the technological and business divide?
Sid: Today, the democratization of data science across the enterprise, and tools that put data into the hands of the many and not just the elite few (like data scientists or even analysts), means that companies are using more data in more ways than ever before. And that’s extremely valuable; in fact, the companies that have seen the most success in using data to drive the business take this approach.
Data democratization is the path forward to eventually enabling AI services. The idea is deeply intertwined with the concepts of collaboration as well as self-service analytics. With a Data Science platform like Dataiku, organizations get access to key capabilities that are crucial to successful enterprise AI initiatives:
- A Simple UI for data wrangling, mining, visualization, machine learning, and deployment.
- A collaborative and team-based user interface accessible to anyone on a data team, from data scientist to business analyst.
- Instant insights on datasets via automatic reports, detailed dataset audit reports, and the ability to filter and search data as easily as a spreadsheet.
- Visual processors for code-free data wrangling and transformation.
Collaboration is about making AI more widespread and relevant through access to a wider population within the enterprise. Dataiku is one of the world’s leading AI and machine learning platforms, supporting agility in organizations’ data efforts via collaborative, elastic, and responsible AI, all at enterprise scale.
Dataiku believes that those companies who succeed in deploying and scaling AI will do so by ingraining a culture of working with data throughout the enterprise instead of siloing it into a specific team or role.
TECHx: For years, we’ve all been utilizing AI-enhanced technologies and platforms, often without noticing it. How can we all move up a level in 2021?
Sid: When picturing a data scientist, many people might imagine a highly skilled individual working alone. Indeed, data scientists are often very specialized, and it is therefore challenging for individuals to replicate these capabilities. However, over the next few years, we will see a trend in the region of businesses focusing on enabling non-technical profiles to engage in data analysis and exploration through citizen data science. This involves working with platforms like Dataiku to build plugins and different tools that analysts can use.
Such efforts make data more accessible and lower the entry barrier to data analysis. Analysts can directly get insights to line of business (LOB) owners, enabling them to make real decisions and essentially deliver better service to customers.
It is worth pointing out however that while platforms like Dataiku do help democratize data science and analytics, there will always be need for specialized data scientists — organizations need them to make sure processes are robust and those insights are well tested and true. For example, teams need specialists to build the plugin in the first place and then to teach people how to use it.
But the bottom line is data analytics is becoming increasingly democratized, and more companies are starting to consider how citizen data scientists can help them reduce costs and risks.