Data analysis software promises a one-size-fits-all solution

Image credit: fotocelia

In recent years, data officers everywhere have had to deal with an unprecedented scale, complexity, and diversity of data. As everything gets more interconnected with the rollout of IoT, that data spike will only become a whole lot sharper.

How welcome then is a data software that promises a one-size-fits-all solution that is also self-service and code-free?

Getting rid of the analytics chokepoint

The US-based Alteryx offers one. Its end-to-end data analytics platform empowers data analysts and scientists alike, promising to break data barriers to deliver actionable insights.

Alteryx chief executive officer and co-founder, Dean Stoecker, explained that Alteryx was built to be “data agnostic and analytic agnostic and would solve pretty much any business problem you could throw at it.”

“Data companies try to figure out how to monetize content, and the only way to do that is to wrap data in easy-to-use software,” explained Stoecker. “Then you’ve got to inject an entire continuum of analytics to make the data ‘dance’.”

With a plethora of data sources and multiple environments where people want to consume data and analytics, Alteryx decided to modernize its technology from the middle of the technology stack, “where the entire chokepoint of analytics exists.” This goes against the common perception that the stack is linear and every component has equal weight — a model Stoecker called “broken” when it came to analytics.

To get analytic processing done, Alteryx modernizes in the “chokepoint,” touching disparate tools. In traditional IT, this would involve a few different tools/teams for extraction, organization, integration, predictive analysis, etc. Alteryx unifies the entire analytic experience and combines an end-to-end process that takes out the “middlemen”, putting all these capabilities back in the hands of the organizations who “have the context around questions that are being asked”.

“We modernized from the inside-out, allowed the chokepoint to no longer be a chokepoint, and there’s been nobody to date who’s actually done this,” said a beaming Stoecker.

Assisted modeling

Using the same platform (“what I sell to the banks, I sell to the airlines and football teams,” said Stoecker) which is itself a canvas with a series of at least 14 different categories of tools built-in, the Alteryx Designer Interface claims that you can tap into any kind of data that exists.

“Analytics is a continuum with the highest order being machine-learning algorithms,” said Stoecker. “We’re talking about a world where machine learning will deal with all day-to-day challenges businesses have. So, this continuum continues through spatial analytics, predictive analytics, cognitive services, and machine learning, but it is predicated on providing a platform that allows you to deal with all the data issues.”

While data-driven companies recognize the need for machine learning to succeed in business transformation, they struggle to advance analytic journeys as they continue to rely on data scientists and trained statisticians to build and apply advanced models. Alteryx’s Assisted Modeling closes the pervasive talent gap that exists between data scientists and data workers. It helps teach data science with a guided walk-through that aims to help all data workers, regardless of technical acumen, advance their skill sets in the process of building machine learning models.

As an output of the application, users can understand how and why their models work, capture modeling decisions, and turn raw data into informed business decisions with unprecedented speed and confidence.

From whiskey preferences to Rugby World Cup results

In an interesting demonstration of the Alteryx Platform in harnessing the power of machine learning in predictive analytics, media in Singapore were invited to a Whiskey Analytics session.

Celine Siow, regional vice president for Asia and Japan and Vincent Toh, team lead, Sales Engineering, showed how the typically error-prone and labor-intensive process (“which could take weeks and months,” said Celine Siow) of deploying predictive models has been dramatically simplified.

In essentially what was a drag-and-drop, click-and-run operation to automate routine processes with zero coding, the attending media’s whiskey preferences were predicted.

In that same vein, Alteryx also recently made Rugby World Cup 2019 Finals predictions. Building a predictive model to analyze every kick, tackle and try from over 1,000 matches worth of international test match data from the last 12 years, Alteryx predicted that New Zealand will beat Wales in the final. It even forecast the winning margin.

One for all and all for one

Recognizing that the ultimate value in data is when it becomes ubiquitous to all data workers in an organization, Stoecker began building the next generation self-service data analytics platform in 1997. That platform became Alteryx. It was in line with Gartner’s 2018 prediction that by the end of 2019, the analytics output of business users with self-service capabilities would surpass that of professional data scientists.

And Stoecker predicted this without Alteryx, a seemingly ironic twist that belied the long journey that Stoecker termed a “20-year-old overnight success.” In 2017, he took the company public.

Presently seeing a 59% revenue growth as a public company, Alteryx services 33% of the global 2,000 organizations which “use [our] software in almost every domain and vertical industry, every functional use case in 80 countries around the world.”

The Alteryx Designer is available at an annual subscription fee of USD 5,150 per user. New users can trial it for free.

“We’ve built a platform that allows our users to innovate, solving almost any problem in their business. It’s the perfect platform for CDOs because it gives a common platform in every functional area for the 3 or 4 most important personas within an organization. And so, we see a world where the citizen data scientist and the trained statistician are converging. And when it’s a common platform that both use, that creates a sustaining powerful culture where data is seen as an asset and analytics drive business value. And that’s exactly what CDO’s are telling us around the world.”

Written by Ceecee Wong and first published at CDO Trends

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