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A Drivable Data Stack: How Self-Service Analytics Extracts Higher ROI with AWS 

Strategy   |   Alex Gnibus   |   Nov 29, 2023

During a Formula 1 race, you sometimes hear the driver say over the team radio that “the car is undriveable.” The wheel isn’t steering; the brakes aren’t braking. A car can have the most powerful engine on the track, but it doesn’t matter if the car is hard to drive.  

The same thing goes for your data stack. As companies start the modernization journey, they adopt powerful solutions, like the cloud data warehouse or data lake. It’s an important step toward winning the race. 

But without a car that’s easy to drive, it’s just an engine. 

So organizations invest in modern technology solutions, only to see lower ROI than expected. Companies fall below 30% on cloud utilization, and according to McKinsey, between 30-40% of business reports add little to no value. 

If your data stack is undriveable, your car is stuck in the pit lane. You’re watching the other cars break away and lap you. Other businesses are maximizing their engines, and your drivers can’t do enough with yours. 

This week, Alteryx is at AWS re:Invent as a Gold-level sponsor to help businesses maximize their data stacks. We’re educating on how Alteryx provides a user-friendly interface to solve data problems while getting value from cloud technology like AWS. Coming just two weeks after the Las Vegas Grand Prix, it’s fun to see the parallels between Formula 1 and business and think about how extracting value from a data stack is much like extracting performance from a car. 

In case you couldn’t catch us at the event, here are some takeaways for anyone hoping to build a stack that drives higher ROI. 

1. Evaluate whether your data stack is drivable. 

What makes a data stack undriveable? How can you tell if you’re choosing technology that truly serves your users?  

Most companies understand the importance of empowering the business and building an enterprise-wide data culture. The common pitfall that lands you in the pit lane? Assuming business users can accomplish their data needs using code-based data services that weren’t designed for business users. 

To evaluate whether your data stack is serving the business, take a look at your current data process:  

  • What does user adoption look like for your data services? How many people across the organization are leveraging data? How many more people could you scale to? 
  • Can business domain experts realistically get the data they need? 
  • Are they taking advantage of your investment in services like Amazon S3 and Redshift, or are those limited to technical users with coding skills? 
  • Can business decision-makers own the analytical journey from start to finish, or do they need to rely on back-and-forth with a data team to get questions answered? 

2. Find ways for more users to maximize your engine.

Formula 1 drivers talk about extracting the maximum performance from a car. That’s because you need both a powerful engine and a driver that can get the most out of it.  

The good news is that your company already has talented drivers – your functional business experts, like a financial analyst or marketing analyst. And as you modernize, you’ve got the engine – like Amazon EC2 instances for compute and Amazon Redshift for data warehousing. 

But you still need a way to connect all your drivers with your engine. That’s the UI — the steering wheel of the car. Without that steering wheel, it doesn’t matter how scalable or efficient your compute engine is. It’ll just sit there unused. 

Alteryx connects your users with your AWS storage and compute resources with a business-friendly UI. This way, you can scale the number of users leveraging AWS, even without specialized technical skills. 

Here are a few ways to get more of your AWS investment with Alteryx: 

  • Leverage pushdown processing with AWS: Alteryx supports in-database processing with AWS data sources like Redshift. Using visual, drag-and-drop tools, execute transformations directly in AWS – minimizing data movement and speeding up runtimes. 
  • Deploy Alteryx Server on AWS: Alteryx Server on AWS is a cost-effective and flexible way to manage and deploy various configurations of Alteryx Server. 
  • Set up private data storage with AWS: Private Data Storage in the Alteryx Analytics Cloud Platform allows organizations to keep all data assets stored in their own AWS cloud account, maintaining centralized data governance as you scale to more users. 

3. Demonstrate value in record time.

IT and data leaders are under pressure to show value sooner than later. Organizations can’t afford to wait months before an investment demonstrates business impact. You want your data stack to live up to the hype. 

So, how do you deliver early wins? By building self-service into your analytics process from the start. When you include business decision-makers in the analytics journey, you can stay focused on the use cases that create business value. If you’re in IT or in charge of selecting tools for the data stack, ensure business stakeholders have a voice in the process. 

Self-service learning is also critical for fast upskilling. Choose an analytics solution that can parlay existing business understanding and spreadsheet skills into advanced analytics use cases. Make sure there’s a robust user community and educational resources for support. 

Alteryx was recently recognized for delivering faster time-to-ROI and faster implementation. These are the things you should be looking for when building a data stack that supports business results right away – like Oscar Piastri showing early success in McLaren instead of spending years getting up to speed. 

Here’s a literal example of time to value: Alteryx helped McLaren set a world record for the fastest-ever F1 pit stop at 1.8 seconds. Talk about a stack built for speed! 

4. Deliver a consistent UI as your stack evolves.

Data infrastructure evolves about as fast as race conditions do. Today’s warehouse could be tomorrow’s lakehouse. How will you ensure your business users still deliver value whether your data is processed on-prem, hybrid, or in the cloud? 

As IT and engineering work hard at modernizing the underlying technology infrastructure, end business users should still be able to continue delivering analytics value with one consistent experience, instead of starting from scratch and learning a new tool with each change. 

That means allowing users to choose where they build their workflows, even as the execution engine changes. For instance, Alteryx Cloud Execution for Desktop enables customers to build a workflow on Designer desktop, then save it to the Alteryx Analytics Cloud Platform to schedule and run in the cloud. Execution takes place in the Private Data Plane, so with an AWS account, you can keep data workloads in your own network. 

Alteryx allows your drivers – the humans, the business users – to extract performance from your engine with a car that’s easy to drive at any stage of cloud modernization. Even as your data needs evolve and your tech stack changes, you won’t hear people saying “It’s undriveable.”  

Alteryx makes it more accessible for all users to take advantage of powerful services like AWS. To learn more, visit our AWS Marketplace listing to get started. 

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