What on Earth?

Written By:
Content Copyright © 2016 Bloor. All Rights Reserved.
Also posted on: The IM Blog

Uneartha is an unusual name for a product. Once you know what it does – be patient – it’s one of those “why didn’t I think of that” offerings.

Consider application development for a moment (and, no, Uneartha is not in this space). One of the major things you want is requirements traceability and, if we consider testing, then you would like to generate test cases directly from requirements also. Tools that support cause and effect modelling as well as products like SpecFlow and CA’s Test Case Optimizer (previously Grid-Tools’ Agile Designer), all do this.

The great thing about starting with requirements is that anything generated from those requirements should directly reflect whatever it is that the business wants you to do. At least, provided the requirements gathering and definition process is sufficiently rigorous, and sufficiently collaborative – which means user-friendly as well as IT-friendly – that the resulting requirements specification accurately reflects what the user wants.

So, to the point. What Uneartha does is, ultimately, to generate ETL (extract, transform and load) code from requirements. I am not sure that I know of any other data integration vendor that does this, yet it seems like an obvious thing to do: if development, ETL or otherwise, is isolated from requirements definition then there is always the danger that what you deliver is not what the user wanted or expected. Tying everything back to requirements is one way to avoid this.

Anyway, how does Uneartha do this? Well, actually, there’s a lot more to it than that. The Uneartha Framework starts with the Requirements Tool, which has historically generated an SQL-based data model but which now also supports Hadoop support and which also feeds Data Governance processes for reporting, rules and metrics that help to drive the model. Then there is a Data Capture module, which allows the Framework to support non-normalised data, including unstructured data. Then you get the ETL module as well as a sematic layer, which is also generated from the data model, which you can report against. There is also a module called Explora, which provides data preparation capabilities. That’s a pretty brief overview but you should get the general idea.

You almost certainly won’t have heard of Uneartha. And you probably haven’t heard of the company behind it: TICS Services. This is a UK-based, privately owned company that was originally founded as a consulting house. As is often the case, the company developed what has become Uneartha because it repeatedly came across the same problems in its consulting engagements, and decided to develop its own software so that it wouldn’t have to keep reinventing the wheel. This is what has eventually become Uneartha, for which there are users, not just in the UK but also France, the Netherlands, and the United States. This is quite impressive given that this is a relatively small company, with no salesforce, and only consulting engagements and word of mouth to take the product forward. Worth a look I think.