7 Reasons Dataiku Is the Trusted Source for Modern Analytics

Use Cases & Projects, Dataiku Product, Scaling AI Dan Darnell

In my prior post, I shared the seven reasons analytics and IT leaders should upgrade to a modern, cloud-native analytics platform. In short, the world has changed, and teams must collaborate and take advantage of the latest cloud and AI technology in a safe and governed environment to create production projects that will generate value for their business. It’s time to move analytics to the Generative AI era. In this article, we’re going to highlight how Dataiku addresses the seven core challenges lined up in the previous article.

1. From Analytics to AutoML to Generative AI, We Meet You Where You Are (Plus, Upskilling Is Inherent!)

Legacy analytics and reporting platforms focused on descriptive analytics, but AutoML enables more people to access predictive capabilities and increased interest in predictive analytics on business teams. 

Dataiku includes visual tools for predictive analytics that virtually anyone in the organization can use as part of a single platform for data and analysis, so users can build data pipelines, perform data preparation, and build predictive models all in one place. Having a single platform has the added benefit of making it easy for analysts and subject matter experts to upskill to take on new responsibilities and drive more value in their roles.

Dataiku allows everyone to build predictive models with AutoML and Expert modes.

Dataiku allows everyone to build predictive models with AutoML and Expert modes.

💡SLB decided to scale data science and AI in the organization by internally upskilling over 3,000 energy experts. A custom Dataiku portal was launched for SLB employees, offering modular learning, hands-on exercises, and certifications, with a gamification campaign to motivate employees to complete the courses. It took the HR team less than two years to reach 600+ certified data science practitioners and 5,200+ Dataiku Academy certifications. Now, domain experts use Dataiku to build automated data pipelines, data analytics, and machine learning solutions without code.

2. Robust AI Governance and Oversight, Plus Explainability and Safety Guardrails

As data privacy regulation has increased, legacy applications exposed organizations to risks from data duplication and poor visibility into data usage on desktop systems. Dataiku solves this challenge by providing a rich analytics governance layer on top of analytics projects. 

Dataiku is a visual and shared environment that allows teams and executives to see and understand projects. Dataiku also offers robust automated project and model documentation tools to create maximum transparency and trust. Dataiku also includes a configurable governance module that empowers organizations to take control of the step-by-step process to ensure projects are built and deployed using responsible practices that help to manage risk. 

Dataiku’s built-in governance capabilities make it easy to manage projects through design and production.

Dataiku’s built-in governance capabilities make it easy to manage projects through design and production.

Further, Dataiku was recently named a Leader in the IDC Marketscape for AI Governance Platforms 2023. IDC said it best in the report when they said, “Choose Dataiku if you need an AI Governance platform that prioritizes democratization, trust, and scalability. Dataiku distinguishes itself through powerful integration capabilities, robust governance features, and proactive customer service. It is suitable for businesses of all sizes and has a user-friendly interface that enables users with varying levels of technical expertise to efficiently harness the potential of AI. Plus, Dataiku offers so much more than just AI Governance capabilities. 

💡At Regeneron, the complete picture of information includes different voices: patient, clinician, and scientist data. From genomic and demographic data to clinical data and real-time biometric data, Regeneron is focused on connecting billions of data points to accelerate and improve confidence in critical decisions. 

Thanks to technology frameworks, people, and processes already in place from the hundreds of successful ML and deep learning-powered solutions Regeneron already has in production, they are able to quickly capitalize on the opportunities afforded by Generative AI and LLMs, rapidly deploying applications for use use cases such as document summarization, medical assistance, competitive intelligence, ad more. 

Where does trust come into play for Regeneron? They use governance and adoption as key levers for trust, ensuring explainability, drift and bias monitoring, observability, and more. On the Responsible AI side, they leverage AI Governance, acceptable use guidelines, model registry, technical standards, and more. 

3. Modern Data Access Methods (Including Cloud Data)

Traditional data access methods via flat files and spreadsheets are inadequate for modern business needs. Dataiku connects to leading cloud data sources, data warehouses, and datalakes, including AWS, Azure, GCP, Snowflake, and Databricks. 

The pre-built connectors make it easy for anyone to find and use the data they can access in cloud data sources. Beyond the cloud data sources, Dataiku provides a visual and powerful data catalog for teams (i.e., analysts, data scientists) to share datasets so everyone can easily access the best data without starting from scratch every time. This, in turn, empowers other business departments to derive greater insights, build data products, and unleash the true potential of data, culminating in a profound appreciation for data within an organization.

The Data Catalog in Dataiku provides easy access to data connections and reusable datasets.

The Data Catalog in Dataiku provides easy access to data connections and reusable datasets.

💡A five-star review on Gartner Peer Insights says, “Dataiku is a highly effective cloud-based ETL platform with scalable tools for team members across the technical skillset spectrum. The cloud-based nature of the application enables various users to build different parts of the workflow while staying abreast of developments in their collaborator’s pipelines.”

4. Simplified Cloud Computing for Everyday AI 

Legacy analytics tools struggle to harness the power of cost-effective cloud environments, hindering teams from utilizing new cloud resources and budgets. As a modern analytics platform, Dataiku integrates with AWS, Azure, GCP, Snowflake, and Databricks computing to take full advantage of cloud resources. 

Dataiku creates workloads that run directly on cloud computing for all users, from visual no-code to those using code — everyone can take advantage of cloud computing budgets and resources. 

💡Cloud-native architecture is critical to scaling analytics, machine learning, and AI, but cloud computing also offers opportunities beyond scaling to innovate and deliver more value across the AI lifecycle. Dataiku’s cloud innovations make analytics and AI at scale more productive and cost-effective.

Example of Dataiku reading data from AWS and Databricks and running workloads on Databricks.

Example of Dataiku reading data from AWS and Databricks and running workloads on Databricks.

5. One, Centralized Platform = Multi-Faceted Acceleration

Desktop tools can make data projects challenging to operationalize and maintain due to the lack of collaboration and version control. With Dataiku, users have one platform to design, automate, and deploy projects. 

This single environment makes it much faster to move projects into production and makes projects more robust. The result is that more data and analytics projects are up and running and easier to maintain, creating more value at a lower cost.

Dataiku provides a complete system from design to production.

Dataiku provides a complete system from design to production.

💡A global luxury group with multiple subsidiaries needed a tool that would allow them to overcome heterogenous skill sets and data maturities within the company. IT and digital teams built an internal, pre-packaged offer based on Dataiku and Google Cloud Platform to allow entities to leverage data regardless of maturity and skills. This led to a 10x faster time to market for a client detection use case, along with other multiple use cases generated.

Further, the R&D team at global biopharmaceutical company Alkermes wanted to accelerate therapeutic discovery by identifying novel gene targets from patent applications (in context of gene ontologies) and move from manual review (which was impossible with millions of patents). Using Dataiku NLP and machine learning capabilities, the data science team of the Alkermes CoE managed to classify and rank patents on relevance and novelty, which led to uncovering new possibilities in drug discovery.

6. Built-In Collaboration for Ever-Evolving Work Dynamics

It is now table-stakes in today’s work dynamics to include seamless remote collaboration for cross-functional teams. Dataiku is a browser-based and cloud-powered platform where everyone works in a shared environment with built-in collaboration, including project wikis, discussion boards, and shared projects, so teams can do more together, no matter where they are.

Dataiku gives teams a shared cloud-based workspace where they can collaborate.

Dataiku gives teams a shared cloud-based workspace where they can collaborate.

💡By making process mining in Dataiku a regular part of their audit workflow, Aviva was able to make collaboration across the business easier and clearer. With hard data and compelling visualizations, auditors can keep their colleagues on the claims teams informed about the exact pitfalls within the processes they’ve designed. On the analyst side, the greatest benefit of the process mining was in terms of time saved, cutting their time spent by about 50%, whereas for the auditors it was in terms of the quality of the output, allowing them to quickly focus on what matters.

7. Enterprise-Grade, Future-Proof Generative AI

Generative AI, specifically Large Language Models (LLMs), has revolutionized the work environment, leading executives to explore its integration while facing incompatibility with legacy analytics platforms. In fact, in a custom study conducted by Forrester Consulting on behalf of Dataiku, key adoption risks of Generative AI include items like integration difficulties (35%) and governance and risk (35%), both of which can be significantly mitigated by adopting a platform approach. Dataiku is a technology-agnostic analytics and AI platform with deep integration into leading cloud and Generative AI systems. 

Dataiku includes visual tools like pre-built NLP recipes and a prompt engineering studio built on Dataiku's LLM Mesh so teams can safely harness the power of LLMs and create real business applications at scale without needing to code.

Dataiku provides pre-built recipes so anyone can use LLMs in analytics projects.

Dataiku provides pre-built recipes so anyone can use LLMs in analytics projects.

💡Dataiku customer LG Chem (chemical manufacturing company) used LLMs to create an AI service for searching internal knowledge, which enabled new employees to swiftly execute tasks, resulting in higher productivity levels.

Putting It All Together: Dataiku Is the Platform of Choice

Last year, Dataiku celebrated its tenth anniversary and, over that time, solidified our legacy as the standard for analytics and AI in the world’s largest and most successful organizations. In fact, Dataiku has now been chosen by more than 10% of Forbes Global 2000 companies. Dataiku is the cloud-native modern analytics platform, built with the capacity to support any type of migration. Plus, it doesn’t hurt that, over the last few months, we received no less than three partner of the year awards from some of the biggest names in data and AI as well as recognition from prominent industry analysts. Modernize your analytics today with Dataiku.

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