We are now living in the Zettabyte Era. Equivalent to a billion terabytes or a trillion gigabytes, it can be difficult to reconcile exactly what a zettabyte of data looks like, but this is very much the currency we are dealing with given the sheer volume
of information at our disposal these days.
The so-called datasphere only passed the one zettabyte in size towards the end of the 2000s – however, according to the IDC, by 2025 we are forecast to reach 163 zettabytes of data created, captured, copied, and consumed.
It is therefore fair to say that data has become the backbone of today’s businesses operating in the world of financial services, and as the datasphere has ballooned, so too have the opportunities for businesses to create value.
Indeed, those financial services organisations able to extract insights from this ever-growing pool of information are giving themselves a chance to gain a real competitive edge — whether that’s from delivering superior customer experiences, driving better
business decisions or enabling greater agility and resilience.
New technologies, tools and approaches — such as the Internet of Things (IoT), cloud native development, AI and machine learning, and the modern data fabric — are proving themselves as key enablers by offering a path to realising this intelligent business
The global data challenge
For many, however, taking advantage of these opportunities is proving challenging.
While many financial services companies have dedicated data and analytics teams, difficulties are still commonly faced when it comes to managing and leveraging the vast amount of data generated within the financial industry and generating meaningful analysis
For financial service organisations that have an international, multi-country presence, among the most urgent challenges are the diverse sources and applications of data, leading to variations in data formats and measurement methodologies. Data management
and data governance become more complex when different teams interpret and define data differently, affecting data literacy across the organisation. Additionally, data quality can vary significantly, necessitating a comprehensive approach to managing data
quality across the data management strategy and its teams.
How can financial services businesses and their D&A teams respond?
Overcoming challenges such as these will be critical to businesses and their data teams’ ability to unlock the actionable insights and value stored within global data pools.
Although each organisation will have their own nuances and circumstances impacting the nature of these issues, there are some broadly applicable initial steps and considerations that can help every enterprise face up to them.
At the operational and technical level, a critical step is to create an operational data lake that serves as a centralised repository, integrating valuable data from across the organisation. This "single source of truth" becomes the heart of the organisation,
providing accessible and practical information to all stakeholders.
From an organisational and cultural perspective, several considerations come into play. Designing a Data Office becomes crucial, defining an operational and relationship model between key organisational areas, specifying responsibilities, profiles, and objectives.
As does establishing a well-defined data strategy that aligns with the business strategy, identifying key actions and plans, and setting a clear roadmap.
Moreover, developing a robust data governance model with clearly defined organisational roles and functions ensures data consistency and accuracy. Creating a data quality manual that communicates data comprehensively to both technical and non-technical users
is key and includes measuring data quality against predefined metrics and implementing a plan for continuous improvement.
To enhance data literacy, implementing techniques that promote better understanding of data, like a data glossary, can also prove beneficial. Such initiatives empower employees and the organisation to grasp data concepts accurately, enabling smarter decision-making
and improved data-driven insights.
The world of data need not appear as daunting as the ‘Zettabyte Era’ might suggest. Although the datasphere is expanding at an exponential rate and delivering an unprecedented speed of change for financial services companies and their tech teams to navigate,
it is possible to overcome many of the associated challenges, including those which are intensified by doing business across borders. By aligning their efforts with a well-crafted data strategy, fostering data governance, and investing in data literacy, they
can unleash the true potential of their vast and diverse data landscape. Only then can they confidently navigate the complexities of the global financial landscape and secure their position as leaders in the industry.