Building public trust is essential for creating a stable society and a thriving economy. When governments gather, keep and use data, there are significant real and perceived risks.
Singapore’s ability to accelerate its public sector transformation programmes and maintain its competitive edge as one of the top smart nations in the world is due, in large part, to the high degree of public confidence that its government enjoys.
Data that has been given to the public must be processed in a way that is trustworthy, secure, and ultimately serves the common good. Public sector data executives are constantly considering how to uphold data trust throughout the full data lifecycle, including data consent and collection, data utilisation and analysis, data sharing and access.
Current strategies must consider the realities of IT in the present day, including a fragmented data landscape, rising cloud adoption, and a diversifying range of data formats, standards and usage situations.
A trusted data environment may be quickly created by democratising data and promoting increased, albeit secure, data sharing. A reliable platform can increase public trust and provide flexibility for many forms of data exchange, including inter-agency, public-private, citizen-government and more. In the envisioned future, the government, and the people it serves may create a vibrant ecosystem of data-driven innovation.
The OpenGov Breakfast Insight on 18 August 2022 offered the latest information on the uses and benefits of cloud data management for Singapore’s public sector.
Data Trust Boosts Public Confidence
Kicking off the session, Mohit Sagar, CEO & Editor-in-Chief, OpenGov Asia, acknowledges that Singaporeans have a high level of confidence in their government, “Singapore focuses on creating and implementing policies and procedures for activities that serve its people and communities and garners confidence.”
He noted that keeping the public’s confidence in the government’s use of data will be a critical success factor in many future government efforts, as these activities and interactions have shifted more and more into the digital sphere.
The main goal of the data trust is to make it possible to collect and share data for public use. Respect for persons with legal rights to data, as demonstrated by the ethical management of information, is an essential component of data trust.
In addition, when done through the cloud platform, data management may democratise data while ensuring that it is reliable, private and safe. Additionally, the use of cloud technology increases public confidence and allows governments to innovate and enhance services and their delivery.
Mohit believes that economic growth that is sustained and inclusive can advance society, produce good jobs for all and raise standards of living. Likewise, a circular flow of value creation and confidence-building between the government and the people it serves is the end outcome of the entire process.
As digital disruption reframes the privacy debate, organisations must consider how and to what extent they evolve their information governance strategies and capabilities. They must ensure that the mechanisms chosen to balance competing interests generate trust and confidence among their stakeholders and the public.
Digitalisation is a key tactic for achieving inclusive and long-term economic growth. As countries like Singapore strive to reinforce their position as smart nations, government organisations continuously move toward a more robust data-driven strategy.
The public sector is under increased pressure to implement effective data governance processes to increase public trust.
Creating a trusted data environment can quickly democratise and encourage greater data sharing. A trusted platform can boost public trust and provide flexibility for different data sharing between constituents. Thus, it gives efficiencies that are critical to long-term economic development.
Government Data Management for the Digital Age
According to Jon Teo, Data Governance and Domain Expert at Informatica, a digital society provides every person with an equal opportunity to succeed, regardless of differences or circumstances. It encourages people to dream bigger as they become more connected to the rest of the world through technology.
Digital transformation utilises digital technology to develop or adapt new or existing company processes, culture and customer experiences to meet evolving business and market requirements. “This reimagining of business in the digital age is digital transformation.”
Jon offers Singapore as an illustration of how a country may adopt and use technology to reap the rewards of digitization, “Singapore is making good progress toward becoming a smart nation.”
He added that Singapore had set its sights on becoming a world-class, tech-driven city-state. It is transforming itself into a Smart Nation, harnessing technology to transform how its people and businesses live, work and play.
During their encounters with various data leaders and analytics managers, the phrase “data governance” is frequently used in addition to the initiatives for analytics and cloud data platforms.
The capacity to locate sensitive and personal data, safeguard the data and data access and frequently offer evidence of compliance with privacy regulations that have been passed or updated in the region during the past few years is the most frequently heard requirement for data governance in this context.
Additionally, data trust and how data processes may improve the consistency and dependability of the inputs and outputs of analytics and BI activities.
“These needs are certainly important, but ultimately, they are pieces of the overall data puzzle. Supporting these needs, and many more besides, can only begin with a dynamic, shared view of our data universe, that is useful to all constituents,” Jon points out.
Some analysts have called this Data Intelligence – an activity of employing artificial intelligence (AI) and machine learning (ML) techniques to evaluate and transform enormous databases into intelligent data insights, which may be used to enhance services and investments.
Jon shared the benefits of a governed, shared view of enterprise data assets with Informatica. “For an analytics data user, there are many issues that a one-stop view into our data universe could help to address.”
First is the search and discovery to quickly identify the best data sets for an analytics project across the entire available assets. Second is the understanding of the context of data; this is to ensure that analytics output is ultimately relevant. It is critical to thoroughly understand the business problem domain and surrounding context, as well as the dataset. The third is data preparation. Benefit from reusable, trustworthy data cleaning and quality functions that may be applied immediately to data assets with known data quality profiles.
A catalogue of catalogues that spans the environment will provide a powerful view of data assets across cloud and on-premises environments. On the other hand, upstream systems expedite smart data migration or ingestion. Jon added insights for the data engineering teams, data platform owners and more.
All the steps mentioned above are taken to ensure that the platform’s data usage adheres to security and classification policies and is safeguarded. Utilise the unified view of the data environments to automate and facilitate the transition from the analytics development environment to the production environment.
“This single view is made possible through the active use of metadata which represents our technical assets, business context, and people throughout the organisation,” Jon explains.
He added that the unified view combines this into the trusted metadata graph, which drives and underpins all these benefits. “This may sound like a data catalogue, but it is so much more.”
Jon differentiates the various forms metadata could take, “There’s technical metadata like schemas, there are business metadata like policies, there’s operational metadata, usage metadata, social metadata.”
Bringing all of these together delivers data understanding by leveraging all the sources of metadata within an enterprise from Business Intelligence platforms, Big Data, legacy ETL, tools, mainframes and applications, among others.
Fireside Chat: Data Governance Helps Public Organisations Gain Public Trust
Chris Ng, Group Chief Data Governance and Protection Officer, National University Health System feels that the way a company manages data throughout its life cycle determines how well it will be able to build, maintain and uphold the public’s trust.
The increased challenges in preserving data integrity have led to an increase in the demand for stronger data governance frameworks. Moreover, data governance strategies assist public organisations in enhancing public confidence.
Building, sustaining and upholding public trust depends on how an organisation handles data throughout its life cycle. Growth in the need for better data governance frameworks resulted from the growing difficulties in maintaining data integrity.
Although the ability to manage a huge amount of data has become critical to the success of businesses, most enterprises are grossly behind the curve. The current situation shows how data breaches are prevalent, rogue data sets spread in silos have become rampant and corporations’ data technologies have recently been falling short of expectations.
According to Chris, “each organisation has different frameworks.” Hence, there is no one framework for constructing a robust data strategy that is applicable across industries and maturity levels. What is sure, however, is that the chosen methodology will help managers determine whether their statistics are “defensive” or “offensive”.
Data defence minimises downside risk by maintaining regulatory compliance, employing analytics to detect and minimise fraud and constructing systems to prevent theft. Data offence aims to promote company objectives like revenue growth, profitability and customer happiness.
Chris furthered that optimising the “data value chain” is the same as making the data useful. This idea of a value chain refers to a process of turning data into information and then turning that information into business insights that aid decision-making and planning.
He emphasised that data is valuable because it has several qualities that make it worthwhile. “So, organisations need to know how the world of data has changed from a linear value chain to a complex ecosystem of information.”
High-value data, also known as data assets, can support strategy, insights and business decisions. Any internal or external sources can provide data that can be gathered, prioritised and sorted. It might be not easy to distinguish between useful data assets and those that are not.
But thanks to automated tools and procedures, big data has increasingly been easier to sort through. Incoming data can be organised according to its utility in addition to being sorted and prioritised generically.
A large body of data is a valuable resource. Any single piece of data is valuable in relation to other data or measurements.
Overarching data sets are divided into three categories based on their usefulness: business management, application and business integration and monitoring. In other words, value extends beyond the data pieces themselves. The entire value includes the reporting, analytics, insights and value people receive from having access to data.
Organisations have recognised that data is a core business asset. Teams oversee managing and analysing data in departments and roles based on data while managing, storing and making sure that data is safe and can be accessed correctly are important business challenges.
As a result, more application-based and Software As A Service (SaaS) solutions are being made to help deal with the vast amount of information that comes with big data.
Comparatively, data stewardship is the administration and control of an organisation’s data assets to offer business users conveniently accessible, high-quality data that is consistent. Data stewardship focuses on tactical coordination and implementation, whereas data governance often focuses on high-level policies and procedures.
A data steward is responsible for implementing data usage and security standards as specified by enterprise data governance initiatives. This serves as a link between an organisation’s IT department and its business side.
The position demands various technical and business-oriented abilities, such as data modelling and programming, as well as knowledge of data warehousing and storage ideas and enterprise strategy. Data stewards are also valued for their communication and cooperation skills.
Chris also shared that a data strategy is a comprehensive plan and policy for transforming an organisation’s culture into one that is more data-driven. Although a data strategy is frequently thought of as a technical exercise, a current and thorough data strategy is a road plan that outlines people, processes and technology.
It is necessary because the company’s many divisions will have varying perspectives on data-related skills without a unified vision and framework.
On the other hand, the execution and enforcement of authority over the administration of data and data-related assets are known as data governance. Data governance is concerned with how individuals behave when it comes to data-related activities and focuses on increasing the value of data and information.
Closing Remarks
“Different organisations are on different paths. We have determined that data governance and privacy are the foundation for all data,” says Steven Seah, Managing Director – ASEAN, India & Korea, Informatica.
The challenges that evolve around the organisations belong to the PPT framework or the people, processes, and technology.
The PPT framework focuses on the interactions between the three components. The task is done by individuals. Processes improve the effectiveness of this effort. People can complete their activities more easily and more efficiently thanks to technology.
Firms can attain organisational efficiency by striking a balance between the three and improving the interactions between people, processes, and technology.
The complete value stream of people, processes and technology should be mapped. This enables complete control and visibility over high-performing teams so that they may streamline operations and deliver products more quickly. Most businesses used it to raise the productivity of their workers and equipment.
“Informatica is attempting to collaborate with you in terms of your challenge. We can assist you with your people and processes and have the technology,” Steven reiterates to the delegates.
Mohit stressed the importance of digital collaborations as vital for expanding an enterprise. He added that before investing in a solution, strategic alliances with digital service providers or digital experience platforms might be an excellent method to learn about it.
“No organisation possesses all information, resources, or expertise. Many businesses still lack the internal capabilities required to drive digital transformation – this is true for both agencies and corporations,” Mohit concludes.