One of the biggest challenges public sector organisations face in effectively leveraging their data resources is the complex data management process that holds sway in many such organisations today. Historically, those organisations have turned to the major systems integrators to handle this for them. Teams of developers have had to be employed to carry out complex coding from intricate legacy systems.
Public sector departments incurred significant bills for the software and a large premium for the services required to drive it. And they face an opportunity cost because of the slow rate at which this typically happens today. There has to be a better approach.
Ensure Data Responsibility
According to a recent study, the digital skills gap costs Australian businesses $3.1 billion annually. And this issue stands on both sides – within the public sector organisations and among the citizens. Since COVID-19, data transformation projects in the public sector have exploded as everyone realised the need for greater and most accessible access to trusted data.
To share a local success story, the NSW Government, through its Data Analytics Centre (DAC), has been recognized for its rapid response to the COVID-19 pandemic by providing current and accurate data to the public. all NSW COVID-19 statistics were underpinned by Talend’s data integration platform, ensuring statistics are available in a timely fashion and can be trusted.
However, the complexity of the architectures, the need for more flexibility and scalability and resources have made it more difficult for public sector organisations to build modern systems that foster greater adoption by the citizens.
For these organisations to succeed before starting a solution selection process, the first and required step is about creating a data and digital culture which will gain momentum through the education of every stakeholder. And any data literacy program must first be sponsored at the organisation’s highest level and involve the data experts, human resources and other management.
Data literacy is even more crucial in the public sector due to the very sensitive nature of the data being processed. When a strong data culture is in place, data citizens can answer the following: what is the data being processed, where is it coming from, where is it stored, and why is it being used? This will automatically ensure a greater sense of data responsibility and consciousness.
Faster access to trusted data
The complexity of the infrastructures and solutions inherited from different approaches and managements prevent public sector organisations from achieving greater efficiency and providing the level of services that the digital native citizens are looking for.
The need for more skilled resources in the public sector builds another barrier to data and digital excellence. To ensure quality, accuracy, and compliance and establish data trust throughout the organisation, applications must be smarter than ever, providing intelligence and automation from data ingestion to data delivery and at all steps in between.
Augmentation and automation through AI, machine learning, and other technologies drive business efficiency and help organisations overcome resource constraints and other limitations in the modern data workforce.
Data integration and management solutions should provide the ability to track and visualise the entire history of data quality, rather than simply a single point in time, to help users identify data drifting or issues that may impact the usability of data. Then, this history can be applied to the micro or macro level by creating logical groups of datasets per your business needs.
Ideally, users should have a console view that not only surfaces issues with data quality and data drift but also provides a self-service launchpad to take action on problem data.
Governance as a backbone of data management
Data governance is a critical component of business agility, productivity, privacy, and regulatory initiatives. Ever-increasing data privacy regulations, coupled with increasingly complex AI and ML models that rely on contextually accurate and complete datasets, will create new governance use cases to eliminate risk and support data-sharing initiatives.
Governance is not only foundational to compliance and data privacy efforts; it also allows companies to understand all data assets holistically, emphasising their accuracy and relevance to each organisation’s business needs.
Public sector organisations should look at platforms able to manage the entire data life cycle while providing data cataloguing solutions, including metadata capabilities with complete visualisation of data lineage, allowing users to see the full lifecycle of the data and address issues at the root cause.
Through the Australian Data Strategy, the federal government sets the vision to become a modern data-driven society by 2030. It outlines the national approach to data as a key driver of the future economy. The strategy ensures data can be leveraged to deliver services, promote competition, and generate better choices for Australians as individuals, business owners, and community groups.
To be able to achieve this data excellence and provide a greater digital experience to the citizens, organisations must look at unified and scalable modern data management platforms which can guarantee data trust, access and monitoring to make sure data becomes an always-on, always accessible multiplier for organisations and not only something that certain people use at certain times.