Some industry pundits would have us believe that modelling data is an old fashioned and outdated practice, and we at Datametrics know this sentiment is incorrect. While we agree that unstructured data systems can be a valuable and worthwhile apparatus for certain types of data, Datametrics have tens of thousands of hours experience delivering fit for purpose dimensional data models to dozens of enterprise organisations’ business data. These organisations can now realise the power and utility data modelling brings to information systems, allowing unparalleled ease of use, business relevance and end-user adoption, all while removing technical burden and high ‘barrier-to-entry’ for developers.
Datametrics are not beholden to one methodology for delivering fit for purpose data structures, but through experience we find the Kimball Data Warehouse methods relevant for most organisational data. This does not exclude unstructured data stores from our expertise, but we find that most organisations require the same answer from their data regardless of who developed the report, what tools were used to create the output, and how much subject matter expertise and business knowledge was available while the information was being developed.
Dimensional data modelling replicates business processes as an organisation understands them, reflects business entities, assists with increased information productivity, and reduces data silos - while aiming to store a single-source-of-truth for an organisation. The information held within these curated data structures are held to the utmost quality controls and stage gates, ensuring the end outputs are accurate, reliable & consolidated.
Our approach to modelling an organisation’s data relies heavily on the organisation’s strategic goals, data governance & stewardship, data sovereignty / legal considerations, and business process subject matter expertise.
Dimensional modelling, data warehousing and data integrations all combine to give organisational information a high level of certainty and confidence for data consumers. All of which is extremely difficult without the invested time and efforts into correctly modelling the data.
Datametrics work with data every single day
We utilise industry standard toolsets & methodologies, and operate within the paradigm of the organisation for whom we work.