Master data

In an enterprise application environment, Master Data Management (MDM) used to refer to the desire to achieve a ‘golden record’ within a data domain. It was the holy grail of enterprise computing – a single version of the truth in a single repository, indicating mastery of organisational data – but then reality set in. MDM…

Data modelling

Modelling techniques are vital in digital, where the distinction between logical and physical dataflows has been overtaken by the need to ensure the business has the data to deliver on its intentions – from the centre to the edge and all points in between. This is such a complex environment that visual presentation is essential.…

Data engineering

If you have massive amounts of data which needs to be available across the extent of your organisation, even your ecosystem, you will need data engineering. Data engineering could be regarded as the antidote to (prevalent) organic (as opposed to purposefully architected) information flows in application-centric organisations. You need to design & deliver optimal circulation…

Data transformation

It seems obvious, but migrating to cloud can be a frustrating process if your data is not suitably transformed before you try the ETL process. As data volumes get bigger; formats more varied and growth, exponential, data transformation techniques are vital. Routine transformations ensure harmony of data format and target destination. But more importantly, data…

Data quality

Poor data quality, taking a reactive, rather than proactive, stance to data errors is a massive own goal. DQ negatively impacts the business so that: Financial data, trades & transactions, are highly regulated and subject to time stamping. Delays and mistakes are not only corrosive, they have much more immediate and damaging implications. The European…