Why government needs to consider real-time data management trends

Real-time data is the backbone of any progressive government, enabling it to improve efficiency, improve operations and communications, deliver improved services to citizens, uncover fraud, and reduce the risk of cyberattacks.

The impact of data usage during the COVID-19 pandemic has been so significant that the UK government has established a National Data Strategy in 2020, whose goal was to use data to innovate, experiment and drive a new era of growth.

In June of this year, however, a new initiative called Roadmap for digital and data, Transforming for a digital future set more ambitious plans to transform digital public services and deliver world-class digital technology and systems.

With the goal of delivering services faster, better and more efficiently, the new plan builds on the original data strategy by improving the flow of data to generate intelligent digital services.

However, as data grows exponentially, four key trends will inform and impact government control and use of their data:

Government data is exploding, forcing better data management

In all departments, data is growing so rapidly and is stored in so many disparate and often siled repositories that it can be difficult to keep up. It is therefore essential to develop mechanisms capable of improving the way data is collected, stored and analyzed, and above all, to develop the capacity to do so in real time to maximize its value.

Government benefits from receiving and processing data in real time

In the event of an emergency, for example, during destructive floods or even during heat waves this summer, the government benefits from receiving and processing data in real time so that action can be taken immediately to ensure the public security.

A major contributor to data expansion is the number of digital sensors and IoT devices that are standard across government departments. IoT devices and embedded sensors are used on UK motorways to control traffic flows, on rail networks to monitor train speeds and to check the air quality in our cities. But they are also used to control access to buildings, facilities and to track physical assets.

Gradually, data expansion is happening in applications at the edge of our global networks – in self-driving cars or through multi-camera video analytics, for example – where data can be processed quickly and stored close to devices. from which they are collected. A report from IDC found that data creation at the edge is expected to increase by 33% by 2025, representing 22% of all digital data created, captured, and replicated.

It’s not just the growth of data that’s a challenge for the UK government, but the fact that it’s mostly unstructured. In other words, it comes in various forms such as emails, video and audio files, surveillance images and text files, all of which are non-standard which makes them more difficult to scan.

Investments in machine learning and AI are prioritized and dependent on usable data

In the UK, the government has implemented a national AI strategy with a roadmap of recommendations that would help ‘energize’ innovation and harness the power of responsible use of data for productivity and job creation, to improve public services and stimulate scientific discovery.

In this context, he has invested over £2.3 billion in AI across numerous initiatives over the past eight years. These include new AI centers for doctoral training in universities, funding for connected and autonomous mobility, and funds to accelerate the adoption of AI in healthcare. AI and machine learning are key to providing insights into risks, opportunities, behaviors and efficiency.

However, AI and machine learning tools can only be fully utilized if they have real-time data to work with. This means merging AI and ML resources with a data platform capable of ingesting massive amounts of real-time data from a variety of sources.

Data security

Government data is safeguarded through protective security policies and centralized and local risk management. A framework is used to determine how departments, agencies and independent bodies that oversee data can do so securely so that government can operate effectively and securely. An important element is the protection of data against unauthorized access, damage and misuse.

This is essential, as stated in the document describing the National Cybersecurity Strategy 2022-2030who said that of the 777 incidents handled by the UK’s National Cyber ​​Security Center between September 2020 and August 2021, around 40% were in the public sector, with no signs of this trend abating.

The dynamic data of the future

As a lifeblood of our digital lives, data is set to grow and change in ways we couldn’t imagine before. This means that to be useful to government departments, analysis of static data will need to be done in real time, not on a monthly, weekly, or even daily basis. It is a challenge that the government must take up that will enable it to adapt to the changing environment and to act on the ideas it draws from it.

By paying attention to these trends, the government will be in a better position to leverage its data in the future.

To do this effectively, real-time data platforms must be put in place that can ingest large volumes of streaming data and combine it with recording systems, data lakes or third parties in real time. By paying attention to these trends, the government will be in a better position to take advantage of its data in the future.

Written by Martin James, Vice President EMEA at Aerospike

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