Managing digital data in large organisations is highly demanding, requiring the active administration of a broad range of tasks, policies, procedures, and practices. This is referred to as data management, and is the practice of collecting, keeping, and using user and company data securely, efficiently, and – importantly for many companies – cost-effectively. Good data management practices are designed to help people and businesses optimise data that flows through an organisation related to established policy and regulation procedures. Through this, it is then possible to make choices that positively affect the organisation as a whole. There’s still much more to data management, so in this article we demonstrate how data management-related difficulties arise.

Where data management needs stem from

It’s not difficult to see how data management can have subjective implications depending on the industry body or organisation involved. With the obvious need to exercise precise data management protocols, regulations have been introduced around the world to ensure compliance. One example of this is the European Union’s General Data Protection Regulation (GDPR), a set of guidelines that includes seven key principles for the management and processing of personal data. These include lawfulness, fairness, and transparency; purpose limitation; accuracy; storage limitation; integrity and confidentiality; and more. Data management in Australia is quite similar, and the GDPR and the Australian Privacy Act share many common requirements, including implementing a privacy by design approach to compliance, demonstrating compliance with privacy principles and obligations and adopting transparent information handling practices. The difficulty in enacting and enforcing these laws quickly becomes apparent due to the incredibly fast pace of business and the related creation and maintenance of user data. With this influx comes a need from organisations to actively develop new ways to store and keep data safe, and this is where problems start to grow for these entities.

Problems organisations experience when managing data

Although data management might seem easy on paper, it’s far from the case. For a start, with information coming in constantly from so many sources – think smart devices, social media and pieces of tech that rely on the cloud – organisations might not even know what data that have, how to use it or where it’s even stored. Even with this being the case, these entities need to ensure that performance is at no point being impacted. This requires the constant monitoring of information to ensure indexes change when queries change to ensure that the right questions are being answered. Data needs to be stored somewhere, and tech storage does not come cheap – especially when more and more of it is constantly being saved and utilised. Entire warehouses dedicated to data are not uncommon, and with this increase in capacity data scientists are required to find ways to quickly and easily transform data from its original format into a variety of forms that make it easier to analyse.

The changing face of data management

It’s not too difficult to see how complex data management really is – there’s far more to think about, such as how data is to actually be repurposed for new uses (simply collecting data doesn’t provide tangible results, after all), but even this will change as the scope of data management evolves. This will force companies to stay on their toes when it comes to data management, which will in itself is likely to provide some interesting results.