Analytic Process Automation (APA): Here to Stay, and Why This Matters to You

Warning: hyperlinks and references to space travel await you…

Since you’re reading this, it’s very likely you saw Alteryx’s huge announcement in May 2020 about their launch of the Analytic Process Automation platform.

But I’m not here to explain why it is or isn’t marketing hype; the awesome Chris Love did a great job of unpacking that already. We’ll dig into what APA is by accepting that it’s the engine needed for non-programmers to make the most out of their data.

Let’s answer why that matters to the “rest of us” data people.

It's the everything in between

COVID19 has ensured I will never again have to explain how I earn a living off of building charts and vizzes to my family and friends. If they didn’t get it before, they do now. Every day, in business and life, decisions are fueled by data. 

If we collect, understand, and use more data to guide our decisions, we have a better chance at landing on more optimal outcomes. How we accomplish this more quickly, accurately, and easily is truly the most important part. 

Wait, but what about…

  • Data viz
  • Reporting
  • Meetings

None of these decision worlds are sustainable without good data. 

That’s why “the everything in between” matters most. 

Everything else

Worlds of decisions

Before we get into the people, process, and data that goes into an APA platform, let’s break down how we got here, and the parts that make up APA.

Over the last few years, we have witnessed the worlds of analytics (business intelligence, data science, and machine learning) converging as organizations in every industry have truly struggled to leverage data for business and societal benefit. As a result, a new era of data analytics software is emerging — marked by a transformative category called Analytic Process Automation.

DEAN STOECKER, CHAIRMAN, CEO & FOUNDING PARTNER OF ALTERYX

Dean summarizes it perfectly. Every data person knows that the struggle is real to wrangle data and get to these valuable worlds of analytics. That could be:

  • A month-end-close report
  • An ad-hoc visualization
  • An analytical application to empower users to grab their own data

There’s plenty of fuel (data) these days to power us to these worlds of analytics, but that means nothing without a means to harness it. 

To get to (and navigate) these worlds, we first need to be able to build a rocketship.

Analytic space in 3 steps

If you’re in this part of the data world already, you know what it takes to build a vessel to get to the point of compiling usable data AND distributing it for decision-making. 

But this post is for every data person, so let’s dig in, with some help from Alteryx.

Inputs

“APA platforms automate data access and data prep from dozens of data sources, cloud platforms, PDFs, text files, and application assets. 

The purpose of integrated data access and prep in an APA platform is to streamline and automate the pipeline of data into an analytic business process while maintaining governance, security, and granular visibility to data lineage.”

The integrity, quality, accuracy, and governance around these source systems are of the utmost importance. But this data is not yet ready for scalable decision-making.

Data fuel

Outputs

“To impact organizational change and enable fast action and smarter decisions, the APA platform must automate business outcomes directly into applications and stakeholders via a variety of output formats, including visual BI dashboards, enterprise applications, bots that take action, AI systems, business-ready documents, mobile apps, email systems, and more…”

The reusability, UX, value, and governance around these output systems are of the utmost importance. But these mediums need data for decision-making.

Decision worlds

APA

A unified platform for self-service data analytics that makes data easily available and accessible to everyone in your organization, optimizes and automates data analytics and data science processes, and empowers your entire organization to develop skills and make informed decisions using machine learning (ML), artificial intelligence (AI), and predictive and prescriptive analytics.

ALAN JACOBSON, CHIEF DATA AND ANALYTICS OFFICER, ALTERYX

The engine

You can have all the fuel on this planet, but without a means to build the vessel to travel to the analytic worlds you’re looking to go, you’ll be stuck on the launchpad with people asking why you’re not using all the fuel.

The next question will be who to give that fuel to instead. 

The APA category (OK, let's wrap this up)

Now, let’s address an obvious question with an actual quote in assumingly many people’s minds during last week’s announcement(s) of the launch of the APA category: 

“If there’s this newly-defined (but has existed for a while) APA category…that indicates there are others in this space, no?”

Of course there are. There are few things in a category of their own in this world.

Do I think Alteryx is the best in the APA category today? Yes I do. In fact, I just might say they are in a class of their own!

But this is a category, and that almost always indicates that there are others in it. So let’s explore that briefly.

To begin, we need to agree on the “must-haves” and “deal-breakers” to be considered an APA platform (and this must have sign-off from business and IT). For me, this is:

Must-haves

  • Security
  • Code-free (easy to learn eg: drag-and-drop)
  • Community (community.alteryx.com)
  • Input/Output agnostic
  • Scheduling/Automation
  • Unified experience
  • Scalability
  • BI visuals
  • Data Science
  • Code-friendly (SDKs)

Deal-breakers

  • Code-only

Nice-to-haves

  • Advanced Visualization
  • RPA
  • Spatial Processing
  • Workflow Templates
  • App Marketplace

So, what other “players” are out there in this APA category? 

Well, because there’s no rank yet out there from GartnerForresterIDC, etc. to tell us what’s good, here is who I expect to remain APA players in the next 2 years.

In alphabetical order:

  • Alteryx
  • AWS
  • Dataiku
  • Google
  • Microsoft
  • Salesforce

And yes, of course we can and should compare head-to-head each of the “must-haves” listed above, and take another look at how the “nice-to-haves” evolve into “must-haves” year-over-year. But, these galaxies of the APA universe are ever-expanding, so I tend to focus my attention on the platform that offers the full end-to-end offering for analytics today, the best APA platform out there: Alteryx

Do you have more questions about Alteryx? Talk to our expert consultants today and have all your questions answered!

More to explore

Accelerate and automate your data projects with the phData Toolkit

Introducing
Data Coach is our premium analytics training program with one-on-one coaching from renowned experts.

Data Coach is our premium analytics training program with one-on-one coaching from renowned experts.