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Alteryx pour Databricks : l'espace de travail pour exploiter tout le potentiel de l'entrepôt de données cloud

Technology   |   Peter Martinez   |   Mar 14, 2025 TIME TO READ: 6 MINS
TIME TO READ: 6 MINS

The Importance of Data Analytics and AI in 2025 

Achieving success with data analytics and AI is top of mind for organizations across the world.  A recent Gartner prediction suggested that by 2025, 70% of public companies that outperform competitors on key financial metrics will also report being data-and-analytics-centric.  As the old saying goes, companies are considering “betting the farm” on analytics – and they expect to see major ROI as a result.    

This strategic importance of data analytics and AI has prompted organizations to invest heavily into cloud data warehouse and adjacent technology – like Databricks. 

As organizations have invested more and more into the space of data and analytics, Databricks has become a household name in IT shops all over the world.  With the Databricks Data Intelligence Platform, the entire organization can use data and AI to drive better business outcomes.  Built on the Databricks Lakehouse architecture, Databricks provides an open, unified foundation for all data and governance. 

Preparing insights, or preparing dinner? 

Cooking is one of my favorite pastimes.  I love spending time in the kitchen preparing a savory meal.  But in order to execute my process flawlessly, I need access to high quality ingredients.  And living in an urban area, accessing farm fresh ingredients would be near impossible without Whole Foods acting as the intermediary on my behalf. Whole Foods takes on the enormous lift of sourcing a variety of ingredients from farms all over the world – providing a centralized and accessible space for people like me to access, acquire, and use those ingredients.  Furthermore, those ingredients are available in various states of processing – from raw vegetables to fully prepared meals, I can access ingredients in various states of preparation to meet my needs.   

But to get to my savory meal, I need more than access – I need the workspace (my kitchen) complete with all the right tools (knives, pans, cutting boards, etc.) to enable me to complete the next tranche of work – moving from ingredients to a home cooked meal.   

This experience is a great analogy for business knowledge workers, who need to prepare insights for better business outcomes on a regular basis.  Having the ingredients isn’t enough, they need the right tools and workspace to make the last mile of magic happen – and that’s where Alteryx comes into the picture. 

The Challenge 

While investment in cloud data warehouses has exploded over the years, only 32% of organizations have realized tangible and measurable value from it, according to an Accenture study.  Data Accessibility lies at the crux of the challenge – To maximize ROI and usage of cloud data warehouses, both technical and non-technical resources need to be able to access that data.  Accessing data can be challenging for non-technical knowledge workers that aren’t comfortable in coding languages such as SQL or Python.  This is a whole tranche of data hungry individuals that yearn for the opportunity to see what kind of insights are hidden within their organizations’ cloud data warehouse, just waiting to be discovered.  

A Self-Service Data Analytics Workspace: The Knowledge Worker’s Kitchen  

Let’s go back to my cooking analogy.  There are some tools and methods that only expert and professional chefs are comfortable with – for example, a professional mandoline, carbon steel knives, and a large deep fryer.  Each of these tools require expert training and or familiarity with expert methods of cooking.  But there are also tools that are intended for use by home chefs and professionals alike –for example,  a chef’s knife, mixing bowls, pots and pans.  These tools can be used by experts, but also make cooking accessible to non-experts. 

Much in the same way, low-code and no-code analytics tooling provide that same value proposition in an analytics environment.  Once I’ve got my grocery ingredients (data) from Whole Foods (Databricks Lakehouse) I can use my home kitchen (Alteryx workspace) complete with all the tooling I need (low-code / no-code tooling) to cook up insights for my business!  And the best part? This kitchen caters to both technical professionals and non-technical professionals alike, with code-free tooling as well as code-friendly alternatives.   

The Tools in the Kitchen: Maximizing Databricks value with Alteryx 

Unity Catalog Access 

With Databricks Unity Catalog support, business teams can collaborate with data engineers and data scientists on trusted data and AI assets, leveraging AI-powered monitoring and observability. 

Together, Databricks Unity Catalog & Alteryx help organizations simplify governance, enhance security, and scale analytics while enabling self-service data prep and AI-driven insights – an ideal combination for companies that want  to balance data democratization with enterprise-grade governance and performance. 

Unity Catalog provides Centralized Access Management for data management teams to enable Alteryx business users with a single layer for managing data access across Databricks workspaces, ensuring that Alteryx users can securely access and work with data while maintaining compliance.  As a complement, Alteryx provides code-free data preparation & transformation capabilities for business knowledge workers. 

LiveQuery 

LiveQuery operates as a “window” into your cloud data warehouse while you work in a code-free Alteryx environment – removing the need to move or replicate any data. Any business user can access and transform their dataset – and there are no egress costs!    

In situations where all workflow inputs and outputs reside in Databricks, Designer Cloud  will generate the transformation logic into native Databricks SQL, which is pushed down and executed in Databricks. 

LiveQuery is a great execution method for business analytics.  Instead of moving data into Alteryx, Live Query pushes SQL queries directly to Databricks to execute transformations at scale. In turn, this minimizes data movement, reducing data transfers to improve latency, security, and overall performance. 

Playbooks 

With Alteryx Playbooks, business teams can explore Databricks data and generate insights without waiting on analysts or writing complex SQL queries. 

Playbooks is an AI assisted use case generator that generates reports and automated insights based on samples from a dataset’s structure & topics.  Playbooks automates the identification of high-value use cases and creates an understanding of how to apply analytics in any organization.  Business users can simply access their data through the Unity Catalog, and with 1-2 clicks connect it to Playbooks to generate reports and dynamic data stories in minutes. 

Using Alteryx Playbooks with Databricks enables organizations to automate insights, scale analytics, and drive faster decision-making—without the complexity of manual data analysis. It’s the perfect solution for business teams looking to unlock the full potential of Databricks data. 

Magic Reports  

With Magic Reports, business teams can develop automated reports with Databricks data.  Magic Reports uses AI-driven automation to instantly transform Databricks data into rich, dynamic reports—without requiring SQL, Python, or BI tool expertise. 

Unlike static dashboards, Magic Reports provide auto-generated summaries, trends, and key takeaways, making it easy for business users to understand data without deep analytics skills. 

Conclusion 

Organizations are heavily investing in cloud data warehouses like Databricks to enhance analytics and AI capabilities. However, realizing measurable value from that investment requires more than just data storage—it demands usability, accessibility, and efficiency for both technical and non-technical teams. Alteryx for Databricks bridges this gap by providing an intuitive, self-service data analytics workspace where business users can explore and analyze data without relying on complex coding. 

Tags
  • Architecture
  • BI/Analytics/Data Science
  • IT
  • Designer
  • Designer Cloud
  • Analytics Leader
  • IT Leader