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How Public Sector Database Teams Can Become ‘Data Centric’

By Sascha Giese, Head Geek at SolarWinds

Public sector organisations across the country are looking closely at the way they can improve services and performance by optimising their use of data. Indeed, many are focusing on it as a key asset and a driving force behind their wider technology strategy to build a ‘data-centric’ approach.

What The Research Tells Us

Database professionals play a vital role in this process, and their role as data custodians—often for private and sensitive information—is pivotal if organisations are to maximise the value of data and turn more of it into useful insight. For instance, research has shown 41% of database professionals consider half or more of their databases to be a critical success factor for their organisation—an important perspective that illustrates the reliance organisations place on data.

Data is also on the move, and workloads are expected to shift rapidly to the cloud, with Cloud Database-as-a-Service (DBaaS) viewed as one of the top three highest priority database platforms to adopt in the next three years. What’s more, nearly two-fifths (38%) of tech pros anticipate bigger budget allocations in 2021 (compared to 2020) to help manage the increased complexity surrounding databases.

This complexity is also characterised by the sheer volume of data collected and held across every organisation, and while much of this is vital, the databases used across the public sector are also populated by information which is redundant, outdated and trivial (ROT). Yet, collecting and keeping the right data is crucial if organisations are to maximise efficiency and use the valuable information they hold to make informed decisions.

The Path to ‘Data Centricity’

So, how can those responsible for building, running, and maintaining databases balance these opportunities and challenges to focus on becoming data centric? A key question to answer is what each dataset is going to be used for. There are a huge variety of requirements, from preparing a slide deck or a dashboard in their monitoring environment to collecting metrics to show the dev manager how often their team is logging in to the system to perform key tasks. But by understanding these needs, database professionals can collect data in the way that makes the most sense.

In addition, the information derived from data should help uncover facts, not confirm biases. For example, if the objective is to determine if server reboots are being caused by patches being applied too often, instead of asking “How often are patches applied?” focus on “How many patches need a reboot?” By comparing this number to the total number of server reboots, it becomes much easier to conclude how often these reboots are affected by patching. The data gained over a longer time frame can also verify the reliability of the vendor information on whether rebooting is required.

With data being easy to come by, it can be difficult to focus on collecting only the worthwhile details. But by becoming more data centric and more data driven themselves, IT teams can reduce the amount of ROT in their environment and prevent data hoarding. In turn, they can help create more efficient, technology-led processes that can help public sector organisations deliver more effective services and maximise value for money.

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