When trying to scale out data, analytics, and AI efforts, every large enterprise reaches a critical point where they need to figure out: How can I bring data experts and non-experts together in one place?
With Generative AI on the scene, this challenge becomes even more pressing. People across organizations (including — and especially — business people who aren’t experts at working with data) are excited about bringing the power of data and AI to their day-to-day work, but they often lack the tools to safely and effectively do so from an enterprise standpoint.
Enter: Dataiku, the platform for Everyday AI that enables both data and domain experts to work together on everything from advanced analytics to Generative AI projects. Combined with AWS cloud services (e.g., Bedrock) and AWS infrastructure, organizations using Dataiku power more insights across more teams for smarter, faster decision making — all while effectively using existing cloud resources.
As a testament to the strength of our partnership, Dataiku received the 2023 AWS Global ISV AI/ML Partner of the Year Award at AWS re:Invent in November 2023. But it doesn’t stop there — read on to learn more about why AI leaders use Dataiku + AWS to scale their data programs.
Empower Business Teams
With Dataiku, business teams can access data in AWS S3 and Redshift and use a visual, no-code environment to prepare data as well as building machine learning models using Dataiku AutoML.
The result? Everyone is working together in a single environment to create and deploy data, analytics, and AI solutions, making everyone more efficient and effective.
Our AWS-powered Common Data Hub, in seamless partnership with Dataiku, accelerates value creation across multiple ENGIE entities through hundreds of use cases. It’s the backbone of our dynamic, data-driven strategy, unlocking thrilling insights and value in a secure environment!
— Jean-Pierre Pelicier, Group Chief Data Officer at ENGIE (source)
Deliver More Solutions on the Cloud, Faster
The strength of Dataiku plus AWS isn’t just about empowering business teams. Dataiku also offers a range of features that complement AWS services, enabling data scientists and engineers to deploy more solutions, faster, and at a lower cost on AWS.
For example:
- Seamless data access and orchestration: Dataiku is natively integrated with various AWS managed services for storage, compute, and collaboration, allowing data scientists to benefit from the scalability and performance of AWS (including taking advantage of elastic cloud computing resources) without having to manage infrastructure.
- Faster data prep and modeling: Dataiku provides visual data preparation, automatic feature engineering, and AutoML to speed up time-to-value (even for profiles who could work in code).
- Start faster with customizable Dataiku solutions: Pre-built projects and ready-to-use templates bring an AI-driven approach to key business challenges in your industry so data scientists can spend more time focusing on high-value use cases.
- Scalable MLOps: Deploy, monitor, and manage machine learning models and projects in production with Dataiku’s easy-to-integrate MLOps tools and maximum visibility. This includes the ability to democratize deployed SageMaker models through Dataiku’s external models as well as to monitor the status and health of Dataiku and SageMaker models in Dataiku’s single Unified Monitoring hub.
- Get up and running in minutes: Leverage Dataiku Cloud to get started fast while democratizing your AWS resources across the organization.
Build Trust in Analytics & AI
Today’s leading organizations are using Dataiku to build and maintain trust with oversight, processes, and transparency. What does that mean in practice when it comes to Dataiku and AWS?
At a more granular level, with Dataiku on AWS, users maintain complete control over data storage, compute, and deployment infrastructure. This ensures that data remains secured in the customer AWS environment.
Dataiku's unique in-database execution requires no data movement from sources like AWS Redshift or separate third-party data stores, ensuring that data remains secured in AWS. Moreover, Dataiku’s LLM Mesh allows users to seamlessly log in to their own AWS tenant, further reinforcing security and compliance when utilizing GenAI and LLMs.
And at a more macro level:
- Business teams build visual projects and pipelines that are transparent, auditable, and thoroughly documented.
- Data experts can provide oversight for business projects,
- Executives have complete visibility into the analytics program and can put governance processes in place to ensure proper review and final sign-off for projects going to production.
For example, at Macquarie Group, the integration of Dataiku’s data governance capabilities with AWS’s cloud infrastructure for parts of the organization’s Commodities and Global Markets Group has enabled the development of highly governed, agile data workflows. This allows for increased data management efficiency and more responsive delivery of data insights to end clients and stakeholders.