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How Self-Service BI Is Going to Revolutionise the Enterprise

byEileen McNulty
January 7, 2015
in Uncategorized

chris neumann dataheroChris Neumann stands at the forefront of the fastest moving technology industry trend: Cloud BI. He’s spent the past three years evangelizing an industry-wide shift to the cloud and has helped position DataHero as the first truly freemium BI platform in the cloud space.

A calculated risk-taker with deep tech industry knowledge, Chris took his lessons learned from Aster Data and started DataHero with a new vision-giving the market a cloud based visualization product servicing the enterprise and consumer customers. We recently spoke to Chris about DataHero’s journey, the importance of UX and how self-service BI is going to change the game for enterprises big and small.


Could you give us a brief background on DataHero’s mission?

DataHero’s mission is to create a self-service, cloud BI tool, for an end user, that helps make sense of the data you work with everyday. By connecting to the services you use daily, DataHero’s vision is to take the intimidation and clutter out of analytics by simplifying and organizing the data you need to power your business forward.

You have a strong focus on UX, which makes sense given your target market. What key lessons have you learned about providing value there?

Data products have traditionally always been designed for data people – so they’re filled with assumptions about the users’ background knowledge. For example, when you try to add an attribute to a chart in any traditional BI products, the first question you’re asked is: “Is this a dimension or a measure?” If you don’t have a background in data analysis, you have no idea what that means and end up spending more time trying to figure out the interface then getting your business question answered. We learned early on that the most important thing to making data analysis accessible was to remove all assumptions about our users’ past experiences with data products and instead focus on helping them achieve their goal: answering business questions. By coming machine learning and recommendation engines with consumer-centric UI/UX, we’ve been able to build a product that lets any user answer business questions, without first having to learn the process and terminology of data analysis.

Does DataHero’s service aim to reduce the need for in-house data science capability?

Absolutely not. For many companies, in-house data analysis capabilities are essential to their success. The problem today is that many analysts and data scientists are spending their time creating charts and dashboards for business users who would gladly do it themselves if they had products that were easy-to-use and gave them access to the data they needed to work with.

Our goal at DataHero is to empower business users to be able to answer business questions without always having to rely on data analysts and, in doing so, free up the data analysts and data scientists to work on the high-value data problems they were originally hired to solve. This is why we were named best startup at O’Reilly Strata 2014, the leading conference for enterprise data analysts.

Do you have any estimate on what kind of reduction in cost that may result in for one of your clients?

One of our clients has used DataHero along with excel spreadsheets and Salesforce.com. He has seen a 75% in reduction of time after buying our tool. This along with ease of use is the reason we seen people buying the most.

Could this become an industry trend? There’s a hiring binge for data science talent, but is it filling a gap that you’re aiming to bridge?

We predict that in 2015, Self-service BI will become a key focus of many companies. Data teams have become bottlenecks in most companies because they can’t possibly keep up with all of the data problems business users are trying to solve. By enabling business users to be more self-sufficient, the entire organization becomes more effective and efficient.

Could you describe the technology you use to operate DataHero?

DataHero is built on Amazon Web Services using Node.js. We use a variety of databases and data platforms to deliver our data analysis, classification and recommendation engines, and leading web technologies like Backbone.js and React.js for our intuitive user interface.

How do you differentiate yourself from other competitors on the market who are aiming to make data more accessible to business users (Zoomdata, Tableau, etc.)?

There are many great companies out there, but we find that their products are still geared towards the technical person. We really try to provide a service that is easy for the non-technical person and the services they use everyday. In companies like a Good Data, you still have to have them provide custom connectors to the data center. Once done, this allows the user to gain access to data that solves their problems. We feel that DataHero is not so much of a competitor, but complementary. Some business users may not need to look at the complex data. Instead they want to analyze the data that is specific to this department and the tools they use.

Could you describe your business model, and main revenue streams?

DataHero is the first truly, freemium data analytics platform. Anyone can create a free DataHero account and get started right away. Our revenue stream is subscription based, per user pricing and enterprise pricing is available.

What is your target market in terms of industry and geography?

We see many users in marketing, sales, and customer Management. We also see users in data payment processing roles, and developer roles.

As a web based product, DataHero has users around the world. The top countries are: United States, Canada, UK, India, Germany, China.

Are you currently looking for funding, or aiming to hire any particular talent at the moment?

We’re constantly looking to add new talent to our team, which includes some of the best and brightest in data platform development, consumer UI/UX design and machine learning. DataHero has raised $4.2 million in seed funding to-date, and we anticipate raising a Series A sometime in 2015.

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(Image credit: JD Hancock, via Flickr)

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