It is time to consider ‘the value of data’ – a number of recent conversations (such as with Stuart Ravens and Martin Paver), an excellent recent article on Highways England’s data valuation and related events such as the emergence of a proposed international standard to develop a ‘data value index’ show that this is a timely subject.
Do you have a data quality problem?
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 is poor/declining etc. But are they just obsessive-compulsive types who want everything perfect?(more…)
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 reflects the committee that created them. They are in fact applicable to virtually all organisations.
Read on to get an overview of what they contain(more…)
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 perspective.(more…)
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 did…”
- “How did we solve….”
- “Where is the information on….”
- And so on
I used to give a similar answer about why many smaller organisations were less affected by poor data quality than they would be if they were larger – namely, being close to colleagues and able to verbally resolve issues acts as a ‘sticking plaster’ to overcome data problems.(more…)
To enable us to continue to support our clients during the changes arising from the COVID-19 pandemic, we are now offering online training at https://courses.dpadvantage.co.uk/.
Our popular ‘Managing Data Quality‘ course has been set up as four individual courses within an overall ‘bundle’:
- The enterprise data asset – explanations of the basics of data quality, characteristics of enterprise data and the ways organisations tend to exploit this data
- People and data – explanations about the generic behaviours people exhibit towards data using the Data Zoo concept, what drives these behaviours and how to improve data behaviours
- ISO 8000-61 – A framework for data quality management – An explanation of the ISO 8000-61 process model and the individual processes within the model
- Implementing data quality management – Steps to follow in order to develop a strategy to improve the approaches to data quality management in your organisation
All four courses are pragmatic and accessible with a clear focus on the people, behavioural and organisational aspects of data quality management. A free taster course is available here.
Further courses are being developed covering a range of business subjects.
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 quality management.(more…)
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 requirements to meet your information needs and organisational objectives?
Is your data over or under specified?(more…)
You may wonder why you should bother improving your data quality or what the benefits of this activity may be. You may wonder how to secure suitable resources and funding to deliver improvements to data quality. Read on to discover why ‘data quality is free’.(more…)
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 ways to categorise human data errors and propose strategies to reduce the severity of these errors. (more…)