Decision maker/investor perspective

Most commonly, companies approach us because they have heard about Ellie from a colleague or a peer. The users of Ellie who spread the good word around are generally data professionals, with job titles such as Data Architect very common among them.

These people, however, are not often the managers or decision-makers. What usually happens is that the Data Architect asks for a demo, after which they tell their bosses (perhaps the CIO, CDO, or CFO): “Look, this Ellie tool would help us a great deal by saving us time and money. Perhaps we could add it to our tech stack?”

The CxO’s, like most external investors, are not experts in all of the new data management software and tech in the market. They look at the bigger picture; their line of thinking is “get us whatever would help us to become data-driven”.

Investors and decision-makers usually want us to label ourselves in a category. What existing (legacy) tool Ellie replaces, they might ask? In which Gartner Magic Quadrant it fits?

The answer to such questions is that Ellie can be best positioned as a metadata tool:  It helps you to understand your data landscape and unlock the value of the data.

However, our way of doing this via fast and easy, business-friendly data modeling is different from many others. We’re not necessarily directly replacing any existing tool, we are introducing a new and better way to do things!

Consider, for example, Snowflake: it would be silly to call it just a “database tool”. They have come up with something that transforms many aspects of the technical side of things. This is what we also aim to achieve with Ellie.

This brings us to the last perspective, which is our own vision of what the future would look like.

Internal vision – Part 1. How does Ellie envision becoming “Google Maps of Data Management”?

From day one, we identified one major problem that, in many cases, prevents data projects from delivering real value to the business stakeholders.

Fancy data management technologies don’t really add much value if you don’t understand the connection between data and business. This connection is often lost in the details of technical solutions. So how could we see the forest from the trees?

Let’s use an analogy of geographical maps such as Google Maps. When you zoom out, you see a bigger area, but at the same time, smaller details disappear – only districts or bigger roads are visible. If all the small alleys and everything would still be kept on the map, it would become basically unreadable.

This is how zooming in and out works. Sometimes you are interested in seeing a larger portion of the map, in other use cases you need to see the exact building where you’re heading to.

This is exactly the case with your data landscape, too. Corporations have hundreds of IT systems, applications, databases, and files where their data resides. If you were to draw an architectural diagram or some kind of visualization of it all, containing all the possible details, it would be a complete mess that nobody can understand.

Ellie aims to be the “Google Maps of data management”: we want to give the user different “levels of zoom” into their data so that a suitable level of abstraction can be found for every user and every situation.

On the highest level, we have business entities and their definitions; on the lowest level, we will have detailed models of technical solutions.

These levels will be linked together, giving the user the ability to navigate back and forth between different levels of models. In the modern enterprise with huge amounts of data and technology everywhere, this kind of ability to understand the big picture is sorely lacking in many cases.