This is Stytch

Today we are launching a new kind of analytics platform. One that combines powerful, self-service data preparation tools with data discovery for everyone in your business. One that gives you a single, seamless user experience from initial data connection to collaborative dashboards. One that connects you to the world’s largest business database from Dun & Bradstreet directly from your analytics environment.

It’s called Stytch, and I’d like to tell you about how we got here.

In the Beginning…

“It’s the key to connecting everything together. There’s nothing else like it!”

That was Graham Ross, our VP of Product Management, effusing about the D-U-N-S number roughly a year ago.

If you haven’t heard of the D-U-N-S number, let me explain. D-U-N-S stands for Data Universal Numbering System. It’s the system by which Dun & Bradstreet assigns a unique nine-digit identification number to businesses around the world in order to establish a business credit file. Think of it like a social security number for businesses; used to uniquely identify and maintain firmographic information on more than 250 million global companies. If you’re a data geek like Graham and the rest of my team, the D-U-N-S number is pretty cool.

At the time of this conversation, we were building risk management solutions at the Dun & Bradstreet Cloud Innovation Center. Many of the Cloud Innovation Center team came with long histories of building business intelligence (BI) and analytics solutions at companies such as Crystal, SAP, Business Objects and Indicee. In working with the D-U-N-S number, an idea was forming. What if we could use this unique business identification system to help companies rapidly match, cleanse and blend together different datasets for better data analysis?

One of the biggest challenges businesses face today is that their data is inherently messy. Snippets of information about each customer, prospect and supplier are being continuously generated and stored in multiple disparate places, from CRM systems, to ERP systems, to financial applications, supply chain systems, and so on. Accurately matching up all of these partial records of information to get a single view of the business or a complete set of customer records for accurate analysis has always been a difficult and manual process. Often, it ends up being done in a spreadsheet. But even with purpose-built tools it’s a complex, time-consuming process that is easy to do badly, particularly if the underlying data quality is poor.

Our thinking was that if we could find a way to complete the data blending process in a more automated way, it could be game-changing for the BI industry and for those who have to do this stuff every day in order to effectively analyze their data.

And so, the concept for Stytch was born.

Yet Another BI Company?

My team likes to joke about being Yet Another BI Company (or ‘YABIC’ for short). The BI market is definitely crowded. New analytics companies seem to pop up every week. But the very fact that there are so many new companies emerging in the space speaks volumes. No single analytics company has yet to adequately address the needs of business teams that have to consolidate, blend, model, report and visualize data from all over the place to get timely, useful insights. This is because the end-to-end BI process—which covers everything from initial data consolidation through to shared dashboards—is fraught with technical challenges.

Most analytics companies have focused on improving the front-end bit of the BI process—the bit where you can build attractive dashboards with clickable pie segments and effervescent bubble charts. The stuff that makes for a great demo. As a result, there are now many BI tools that provide slick, easy-design dashboarding tools and ‘no-code’ report builders. That’s no bad thing. In fact, my previous company Indicee was a great early example of a BI platform with simplified point-and-click reporting tools. It was platforms such as Indicee that began to move BI initiatives out of the hands of the IT team and into line-of-business teams where there are those who can actually put the insights gleaned from their BI tools into practice.

However, the reality is that much of the BI process still lives in technical teams. While there has been a lot of focus on making reports and dashboards more user-friendly, all the steps needed to prepare data for analysis (gathering data, blending it, modeling it) currently require deep technical expertise. Analysts and business teams are still reliant, typically, on the IT team to get data out of their source systems, and prepared, before they can start exploring it. Any changes to the model or new data sources to be added require another go-round through the IT middleman and a whole new data model must be built. Those changes then break the previously-built reports and dashboards requiring a redo from scratch. Each line-of-business team—sales, marketing, operations, finance—works on their own analytics solutions, fighting to get the data they need, and not collaborating until right at the end when each team shares their hard-earned findings; usually via email attachments. The whole thing is inefficient, slow, rigid and siloed. All the characteristics of old-fashioned, enterprise software.

When the idea for Stytch began to take shape we knew that leveraging the D-U-N-S number and Dun & Bradstreet’s data matching services, would help in making data blending easier and more accurate. But we also wanted to make data preparation as a whole, faster and more agile.

We wanted to make Stytch a game-changer for business analysts and wider business teams alike.

Just Stytch It

In building Stytch, we set out to make it different from other data analytics platforms in four key ways:

  1. Data preparation tools for business analysts: Data preparation tools should not require technical expertise to use. With Stytch, anyone with the understanding of the data can blend it from anywhere and create models, regardless of the complexity of the data relationships.
  2. A single, cohesive analytics experience: Quality data preparation is integral to building effective analytics solutions and should not be divorced from the reports and dashboards built from it. Stytch provides an end-to-end solution for business teams, from initial data consolidation to discovery to shareable dashboards.
  3. Rapid data blending: Matching up records from different areas of the business should be frictionless and always accurate. We built the Stytch Connector for Dun & Bradstreet so that as new records get added to your business systems, they get automatically matched to a D-U-N-S number and blended. By connecting to the world’s largest business database directly from your data preparation tools, you can ensure better underlying data quality too.
  4. Flexible, reusable analytic components: As much of the analytics process as possible should be reusable, to allow for fast solution builds, incremental improvement, and collaboration between business teams. Stytch data models can be shared and reused across business teams, supporting an agile, incremental approach to building analytics solutions.

We’re couldn’t be more excited to be officially launching Stytch today. Everyone that works here is deeply passionate about helping you do better things with your data. Those things that make a difference to the way you work, the way your business operates, the decisions you make, and the results you achieve. We hope Stytch is a game-changer for you and your business. Welcome.

By on April 19, 2016

One response to “This is Stytch”

  1. Jason Smith says:

    Congrats on the launch Mark and team. Love the seamless connection to D&B. To infinity and beyond.

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