What is data quality management?
Data quality essentially ensures your data is fit for purpose. For any digital initiative to work, the data fuelling it needs to be clean, consistent, accessible, reliable and in the right format.
That means no duplicate entries, no missing fields, no invalid terminology and no corrupted or inaccessible data. In other words, no bad data.
But there is more to data quality than just ‘good’ and ‘bad’ data. Data quality also identifies what data your business really needs to get the outcomes it wants. Any data project should be driven by a wider business vision: to achieve your objectives, you need to first address what information is relevant and useful to your goals.
Who needs data quality management?
If you have data, you need data quality. A poor quality data strategy will corrupt any data project, regardless of what digital journey you are taking or the technology you intend to use.
What you put in will always influence what you get out of any data project. There is a saying in the data industry: Artificial Intelligence fuelled by bad data isn’t intelligence. You’ll still make bad decisions, but you’ll be able to make them a lot faster.
So, whether you’re implementing MDM, exploring data virtualisation or ramping up your data analytics, data quality is a fundamental part of that process.
What are the business benefits of data quality management?
- Strengthen your digital transformation
- Learn what data you need to achieve your goals
- Have confidence that all of your data is consistent, clean and usable
- Identify processes and procedures to maintain data quality
- Get better, more accurate outcomes from your data
Overcoming your data quality challenges
The biggest challenges in data quality management are knowing what good quality data should look like for your business and maintaining that quality after the initial data quality exercise.
At Amplifi, we see good data as the result of technology, people and processes working together to deliver a business vision. That’s why our data quality management services provide a practical step-by-step process to help you to identify your organisation’s digital objective and establish the data you need to drive it.
We can then help you to create the processes and protocols you need to maintain quality and consistency across the board.
3 Week Data Quality Assessment
By the end of this three-week exercise, we will provide you with data quality reports and dashboards that detail the extent of your data quality issues. Following this, you will receive ongoing guidance and advice on data quality remediation.
10 Week Data Quality Assessment
As part of the 10-week DQ capability build, we begin with a thorough assessment of your vision, and your desired outcomes for data quality management. We aim to understand your existing capabilities (so that we can leverage as many of your existing strengths as possible) and then work towards achieving the best possible operating model design.
Do you need a pragmatic approach to data quality? Get in touch with our experts.