Alteryx is a really exciting blend of easy-to-use technology and powerful intelligent analytic automation that anyone can operate. We’re doing something that very few businesses are doing in any sector – we’re delivering an end-to-end analytic process automation service across the entire analytic journey. Our purpose – to paraphrase – is to enable everyone to deliver breakthroughs.
This can mean different things to different people, but the core of our purpose is that we help people and businesses take data and information they may not be doing anything with and help them turn that data into business-transforming insights. The magical differentiator in the marketplace is that anyone can use Alteryx, an Accountant, a Marketing professional, even my 13-year-old child (he’s Alteryx certified).
Alteryx – in its initial form – started in 1997 when data-work was beginning to rapidly pick up steam.
Today, as data complexity and volumes continue to rise, we unify analytics, data science and business process automation to help businesses accelerate their digital transformation. We help automate the process of achieving data quality, analytic insights, and advanced predictions across every analytics journey – from a small retail store, up to multinational conglomerates.
I have three different roles within Alteryx to help support that. First, I perform data science in the company. Second, I help build product with the team of engineers. Third, I help customers go on their own digital transformation journey. I really enjoy this last piece as we combine all three elements to help Alteryx through our own transformation at the same time.
We work extensively in the open-source community and are currently sitting at over a million downloads a year from some of our key Machine Learning libraries. Our AutoML library – Compose – lets businesses set up a machine learning process and prediction engineering, among other things.
We’re not just proselytising – we’re living and breathing full end-to-end data work, and it’s that experience and skillset which means we can deliver exactly what our customers need.
How has the company evolved during the pandemic?
The pandemic has been a brand-new challenge for businesses across the globe. Prior to this, data work was almost exclusively completed in-office. The ability to do good quality data work from home was almost unheard of.
Naturally, Alteryx was facing challenges that every other business in the world was facing. Many news outlets reported that digital transformation stalled in efforts to switch everyone over to remote working. What we saw, and what we evolved to meet, was an even greater number of people across all organisations who became aware of the fact that data analytics wasn’t a nice-to-have, but an essential driving force for transformation and company success.
For larger businesses, we’ve really seen the value that an end-to-end service can bring. Businesses have looked to drive efficiencies wherever they can and reduce waste. Ironically, the first step they’re taking in doing that is consolidating the software they run and using data analytics to make effective and informed decisions.
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What can we hope to see from Alteryx in the future?
What can we expect to see from Alteryx in future? While we remain focused on being the best at democratising analytics – so millions of people can take advantage of the power that data can bring – we’re also investing deeply in furthering our analytics and data science capabilities.
In a post-COVID world, companies are moving quickly in reaction to new market pressures; needing fast solutions to survive and thrive. There is, however, still a significant perception disconnect where people simultaneously believe that data science is both unattainable and yet supremely valuable.
One of the things I’m most excited about is putting data science tools in the hands of the people with problems to solve – not exclusively those with years of experience or a specific university degree. Today, the modern business reality is that organisations simply don’t need a whole team of qualified data scientists to pull good quality insights from data. In many cases, one qualified data scientist can lead entire teams of citizen data scientists. This lowered barrier to entry means the people closest to a problem can also be the ones to solve it. What we’ll see is a continuation of this ideal – a huge shift towards democratisation of data work through the Alteryx platform.
We’re doing some really good work at the moment in building out our automation and machine learning functions, too. We’ve always said that the next logical step once a problem is solved is to automate it. We want to make data work even easier, and help people deliver even more valuable outcomes.