I have been using the phrase “Perfect is the enemy of good enough” very often relating to current projects. I cannot claim to be the originator of the phrase – it seems to have been in use in various forms
Improving organisational data quality is like house renovation
Imagine the scene, you are a newly appointed/ promoted Data Governance Manager or Data Manager with a remit of ‘sorting out the data mess‘. Colleagues are impatient for results and some are starting to blame you for the poor quality
Coordinate data activities as a ‘data convoy’
I frequently use an analogy of comparing how your organisation ‘does data’ as a machine, but have recently started using a nautical analogy as an extension of this. Which of the following typifies how your organisation delivers data related activities?
Understanding data quality across organisations
An organisation that works in isolation and does not share data with other organisations is probably rare. Most organisations will collaborate with other organisations to some degree and will be providing data as part of this collaboration. So, what factors
Deliver winning performance by tuning your data machine
A good way to understand the impact of poor data practices on your organisation is to imagine the approach to data gathering, storage and exploitation as a machine – a data machine. What does your data machine look like? How
Managing assets? Your team need AD4s!
If you are responsible for managing a portfolio of assets, then your team need AD4s to help them. What does the acronym AD4 mean? Well, it stands for Asset Data Dictionary Definition Document – quite a mouthful, hence the shorter
Julian Schwarzenbach guests on the 30th episode of The Data Strategy Show
Julian Schwarzenbach recently appeared on the 30th episode of The Data Strategy Show. The conversation with Samir Sharma covered a wide range of topics including: Julian’s background in engineering and data The strapline “Data Doesn’t have to be difficult” Why
Why asset data is more challenging than ‘normal data’?
Increasingly, organisations are recognising the importance of good data management and how it can improve organisational performance. Managing data across large (and small) enterprises can be challenging, there are a range of standards and approaches that provide guidance applicable to
Is ‘IT’ or ‘the business’ responsible for data quality?
Most organisations have problems with their data – not enough, too much, not good enough, missing, duplicated, inconsistent etc. Many managers and employees just want someone to ‘sort it all out’, but who is responsible? Often there is a view
Data quality assessment from an organisational perspective
Data quality assessments can provide large amounts of useful information. However, to gain a complete perspective on organisational data quality, it is essential to consider three key perspectives: The data itself – entries in databases and spreadsheets The requirements for