What is a Data Management Health Check?

Many people assume that healthy data is data that is clean, complete and compliant with legal and regulatory requirements. Whilst this is true, these factors alone cannot guarantee that your data can be utilised for business operations.  

 An organisation that merely collects data cannot make rational business decisions, nor can it transform from being data rich into being data driven. Furthermore, the more data a business manages, the more challenging it is to keep on top of that data.  

 In order to meet your organisational goals, you should be making business decisions based on high quality, trusted data; data that is healthy. But what does it mean to have healthy data and how do you measure how healthy your data is? 

The Meaning of Data Health 

Data health is how effectively your data supports business goals and objectives. Data is healthy if it is: 

• Discoverable 
• Understandable 

• Valuable to those using it 

In order for it to remain healthy, these characteristics need to be sustained throughout its lifecycle. If your organisation’s data is healthy, you should be able to prove that it is: 

• Valid 

• Complete 
• Quality 

If it is healthy, you will be able to produce the analytics that enables decision-makers to rely on in order to make suitable business decisions.  

Data health requires monitoring and intervention across the full life-cycle and it will only work across your organisation when you combine the following three elements: 

1. Data agility: a flexible and scalable environment with end-to-end lifecycle management 
2. Data culture: a mutual employee understanding of the origin, meaning and value of the various data points, sets and sources 
3. Data trust: which is derived from data that is visible and verified, giving those that need to use it confidence in their decision making.  

Maintaining Healthy Data 

Most organisations find maintaining good data health a challenge. Data management is constantly evolving so it is important to adapt to the continually shifting landscape. This involves ensuring that your organisation has: 

• an infrastructure in place that is nimble and can sufficiently respond to increasingly complex data environments and faster data flows to allow speedy responses to opportunities and threats 

• a robust data architecture which is supported by a culture whereby every employee is supported to understand and utilise the data available to them 

• a data management strategy that is well-defined and flexible so it is responsive to shifting data environments, such as cloud, hybrid and multi-cloud 

• a comprehensive and consistent approach to data governance and quality to ensure that risk exposure and slow processes in response to privacy concerns and regulations (GDPR and CCPA for example) are reduced and to give data and IT professionals increased control over the health of their enterprise data. 

A healthy organisation is one that has implemented centralised standards, processes and programmes to ensure that data is secure, compliant, accessible and understandable, as well as balancing IT priorities. 

You can improve nearly any aspect of your operations with data health metrics, which proves the value of data to the business. But this is skewed with the absence of healthy data. Inaccurate, uncontrolled or out of date data will not enable you to address the right customers, shorten your sales cycle or improve your processes.  

Unhealthy data will cost you time and quality in your decision making, which in turn adds costs and can negatively affect your revenue. If you are scaling up to work with big data, it is vital that you implement health metrics. 

Measuring the Health of your Data 

Data quality is vital to data health. There are six dimensions for measuring data quality, as outlined by The Data Management Association of the UK: 

1. Accuracy: The degree to which data correctly describes the real-world object or event being described 
2. Completeness: The proportion of data stored in a dataset against the potential for 100% 
3. Consistency: The absence of difference, when comparing two or more representations of a thing against a definition 
4. Timeliness: The degree to which data represents reality from the required point in time 
5. Uniqueness: No item, or entity instance, is recorded more than once based upon how that thing is identified 
6. Validity or conformity: The degree to which data conforms to the syntax (format, type, or range) of its definition 

Your data should be useful and reliable across your organisation. Given that data health is a measure of your data’s value, its transparency and accessibility are as important as its quality. A robust data governance technology platform can help to improve both data accuracy and security.  

Data Health Assessment 

To ensure that your organisation’s data is healthy, you must be able to prove that it is valid, complete, and of sufficient quality to produce analytics that decision-makers can feel comfortable relying on for business decisions. But how do you approach assessing the health of your data?  

It is recommended that you utilise a data platform which incorporates both data integration and governance capabilities. This will provide both a reading on the health of your data and how to cure unhealthy data, with insight into the data you can trust and the tools you should utilise to correct the data that you can’t. The Enterprise Data Management Health Check provided by Catalyst BI, combines both technologies and behaviours to measure and manage data and processes for better discovery, transparency and value. It scores your data management on the following key pillars: 

• Data Sourcing and Quality 
• Data Integration 
• Data Warehouse 
• Data Governance 

The health check reviews the condition of your company's data and how well it supports effective, timely decisions and business objectives. It ensures that your data, technologies, processes and governance are fit for purpose. 

From wanting to prove your current data landscape requires investment to propel your organisations data to the next level, to just being unsure which technologies are required to solve your data management challenges, the EDM Health Check ensures that you are leveraging the best technologies available.