14 December 2022 | Noor Khan

Data continues to grow substantially, and many organisations are overwhelmed with the amount of data. Every organisation that deals with large data sets need to have a robust, efficient infrastructure in place to effectively manage the data and ensure that it provides the maximum benefits, whether that is monetisation opportunities or powerful insights.
Data administration can be a complex and challenging role when dealing with big data. Here we will look at typical data administration challenges that organisations are facing today and how you can overcome them.
Data is always growing and will continue to increase. Ensuring data is clean, validated and organised is key to ensuring that you can maximise the use and benefit of it. Growing data sets can be increase complecxity when it comes to administration. If your existing data architecture is not scalable, then this can cause numerous issues with poor performance, slower query response and gaps in the data. This can also pose a challenge in ensuring good data quality, therefore data should be cleansed, validated and enriched in order to uncover meaningful, useful insights.
Developing data pipelines that are robust, secure and scalable is key.
Data with its constant growth is also evolving and traditional infrastructure which is outdated can present many problems such as increasing costs, the requirement of more resources and slower data performance. From traditional data warehouses to on-site data storage servers, businesses are still hesitant to move away from what they know. However, the adoption of the cloud is paramount for the longevity and success of most organisations. The cloud can provide invaluable benefits ranging from efficiency in data administration, a significant saving in cost and the ability to scale with data.
You do not have to completely move away from the traditional. For example, many businesses are employing hybrid and multi-cloud solutions to reap the benefits of both traditional and modern. Sensitive data can be stored on private clouds or traditional on-site servers and non-sensitive data can be stored on the public cloud, offering flexibility, security and reduced costs.
With increasing data, there will be a significant increase in the workload for data administration teams. If your data administrator or data administration teams are finding dealing with increasing data sets a challenge, then you may consider getting third-party help as an addition to your in-house resource. This can relieve your teams from burdensome tasks so you can focus your team efforts on optimising your data infrastructure to ensure you are gaining value from it.
Data security is a concern for most businesses. Keeping data secure whilst ensuring that is accessible to the right people can be challenging. As data grows in sources, volume and varying velocity, ensuring data security can become complex. To ensure that your data is secure, you must follow industry best practices. If all your data administration is carried out in-house, you might want to invest in accreditation such as ISO 27001 or Cyber Security Essentials to conform to industry best practices. Alternatively, if you are outsourcing your data administration then consider working with a data engineering company that can provides you with robust security of your data with the right measures in place to mitigate any risk.
Ardent provides thorough, around-the-clock data support services to ensure that your data is secure, accessible and streamlined. Our engineers can come on board to create and maintain databases, data warehouses, and data pipelines and provide assistance in migration data. If you do not have the skills and resources in-house, are dealing with growing sets of data or are facing challenges with outdated data infrastructure, Ardent can help. Get in touch to find out more or set up a discovery call where we help establish your challenges to find you the right solution.
At Ardent, we have spent years helping organisations design, modernise and operate the data foundations behind critical reporting, analytics and decision-making. That experience gives us a clear view of what now separates AI-ready businesses from those still struggling to get value from their data. It is not the amount of data they hold, or even [...]
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