Effective data management in a constantly evolving technology world
Thu 27 Feb 2020 | Mark Jow
Technology constantly evolves — so data management should too
The vast majority of businesses today acknowledge that their data is important, even critical to their operations. Despite this, however, many organisations fail to take adequate measures to safeguard this crucial asset.
With data breaches caused by cyber-attacks on the rise, protecting data has become paramount, and yet data management often remains an afterthought. It has become imperative to not only develop a data management strategy but harness appropriate technology in the form of a data management platform. This is essential to prevent data loss events from malicious attacks or disasters, as well as for compliance and business continuity purposes.
Success (and compliance) is in the preparation
A data management strategy needs to specify exactly how data is handled from the moment it is created, from the edge to the data centre. To ensure maximum effectiveness it is essential to firstly understand the value of data to the business: does it actually need to be retained, and if it does, how long does it need to be kept for? If it does not need to be retained, what happens to it? If it does, where should it be stored?
Retention needs to be based on business value as well as compliance with applicable legislation, and the correct levels of accessibility and management of data need to be ensured. Data retention rules and principles should facilitate the creation of appropriate processes to identify important data and then manage it in the most efficient and cost-effective way in the long-term.
The data management platform in turn needs to support the data management strategy. Organisations should actively engage with data management and storage service providers in order to improve their data management, data quality and data governance. This underpins compliance and lays a solid foundation for organisations to leverage value from their data through analytics and intelligence.
Data quality is key to leveraging value
Data analytics is essential for enterprises looking to increase efficiency, improve business decision-making and attain that important competitive edge. However, while big data can add significant value to the decision-making process, supporting large volumes of unstructured data can be complex. Inadequate data management and data protection introduce unacceptable levels of risk. In addition, performing analytics on poor quality data inevitably leads to poor quality insight and can negatively affect decision-making ability.
The emergence of DataOps, which is an automated and process-oriented methodology aimed at improving the quality of data analytics, further supports the requirement for enhanced data management. Driving faster and more comprehensive analytics is key to leveraging value from data, but this can only be done if data is managed correctly, the right governance protocols are in place, and data quality is kept to the highest standard.
Dark data, essentially any data owned by an organisation that it has not categorised or is unaware of, is the enemy of data intelligence. If an organisation does not know what data it has or what it means to its business, the data is worthless. This lack of awareness could also result in a breach of data privacy legislation such as the Protection of Personal Information (PoPI) Act or the General Data Protection Regulation (GDPR).
A centralised, compliant data management platform with proper checks in place can ensure that data is correctly captured and categorised. A sophisticated solution is also able to analyse data and determine its value to the business, identifying what to keep and what can be overwritten. This translates into cost savings as businesses do not need to purchase unnecessary storage space for unneeded data.
Gearing for the future
As data volumes continue to grow and technology changes, the challenges for data management are evolving too. One upcoming challenge is how to protect serverless applications. This needs to be handled via Application Programming Interfaces (APIs) across API vendors, irrespective of where the data resides.
Edge computing is also changing the way data needs to be handled by taking data creation and processing to the edge of networks. Security is a growing challenge and managing the velocity and volume of data creation means data management is increasingly important. Protecting data in the multi-cloud is another growing requirement. Hybrid environments have many benefits, however, ensuring data security in such a complex environment means that finding the right data management partner is more important than ever.
Technology is constantly evolving, and data management should be too. Organisations need to become more aware of their data and its value, so that they can make better decisions to protect it and use it for maximum business benefit. They also need to ensure they connect with the right data management partner to support business imperatives and compliance requirements.