A recent conversation about a large organisation highlighted an interesting question – How do you quickly and easily know that you have got a data quality problem? Clearly, you may have a data manager/ data team who are stating that data quality
Two new data standards for all organisations
In February 2020, BSI released two new data related standards that should be considered by all organisations: BS 10102-1:2020 – Big data. Guidance on data-driven organizations BS 10102-2:2020 – Big data. Guidance on data-intensive projects Although the titles state ‘Big data’, this only
Start well….
There are two sayings that we will all have heard at some time: Start with the end in mind Start like you mean to go on A client of ours demonstrates why these two sayings are important from a data
Has lockdown exposed your data weaknesses?
Staff can often be very resourceful in making poor systems and processes work and to overcome data problems within an organisation. If people are based in a single office then they can call out questions like: “Do you remember who
ISO 8000-61 – the data quality management standard
A few years ago we did a series of blog posts on ISO 8000-150 which have been perennially popular. Well, since those posts were created ISO 8000-61 has been published which provides a richer and more comprehensive approach to data
Your data needs YOU!……(to specify what it should look like)
It has been stated that the most common failure of a software project is caused by not capturing or understanding what the system is required to achieve. This is equally true of your information needs; have you truly captured your
Data quality is free
You may be wondering why you should bother improving your data quality or what the benefits of this activity may be. You may be wondering how to secure suitable resources and funding to deliver improvements to data quality. Read on
Human data errors
Data quality problems all, at their root, involve some form of human error. Whilst this is easy to say, it is perhaps harder to identify and resolve the causes of these human errors. In this blog post, I will explore
Continuity – the new data quality dimension
When talking about data quality, it is usual to consider different aspects or ‘dimensions’ of data quality – validity, completeness, uniqueness, consistency, timeliness and accuracy. These six dimensions were agreed as the most relevant and representative of data quality as
Changing your data requirements
The world is changing, people are changing, organisations are changing, and this is no different for data requirements. An organisation needs to accept this and makes sure that change requirements are captured, impact assessed, acted upon and communicated. During my