Organisations in the banking and capital markets sector generate an astronomical amount of data across electronic trading, global business communications, third-party partnerships, collaborations, and other operations. And all this data is connected within what we like to call the ‘data spine’.
The data spine is a term we use to define the infrastructure that carries and connects all the structured and unstructured data within your organisation, and it controls how that data is used – regardless of where, when, or how it is generated.
When managed effectively, your data spine can inform and guide operations across all your teams, equipping them with the insights they need to innovate and perform at their best. This includes informing specific applications too, such as those in event-driven environments where timely access to insights is required if your teams are to respond proactively to an event or opportunity.
But too often, organisations continue operating with a broken, unconnected data spine that fails to take advantage of the data available within the organisation. And as data-driven competitors continue to set new bars for customer experiences and efficient operating models, many banks will need to fix their data spine problems to exploit the full potential of their data and stay ahead in the market.
It could be your data spine that’s holding you back from making more informed decisions, reducing your risks, allocating your resources more effectively, and automating more tasks across your organisation.
As a starting point, here’s how to identify and unpack what’s preventing your organisation from making the most of its data spine so you can mitigate risk and make smarter decisions, faster.
WHAT’S DAMAGING YOUR DATA SPINE?
One of the most common reasons banks operate with disconnected data spines is due to the data siloes across their organisations.
Many banks have years of fragmented data systems spread across their global teams, partners, and infrastructure – which can quickly limit teams’ visibility into the data sets they need. And the introduction of microservices can increase fragmentation further.
For example, managing so many disparate systems can make it difficult to know where your data is stored, how to access it, and who has permission to do so – and whether it’s of high enough quality to merit analysis. Time-sensitive data may also incur a limit breach if left unused, while failing to demonstrate good data governance may breach regulatory compliance.
Without a clear, connected, and real-time view of your global customers and operations, it can be more difficult to manage risk, personalise interactions, identify cross-selling opportunities, and make informed decisions.
Data siloes can also significantly affect how data is managed and used within the organisation. Different teams may use different semantics, which can easily lead to confusion when those data sets are needed by anyone else in the organisation. For example, just looking at the term ‘customers’, different teams may refer to them as “users”, “investors”, “people”, or “traders” depending on the context.
This becomes even more challenging when the people who manage those data sets leave your organisation, as your teams end up losing access to the niche database knowledge built up by individuals over the years.
When such challenges stack up, they can create dozens of gaps throughout your data spine and leave your team without access to the insights they need to perform at their best. It can also lead to:
- An inability to seize AI opportunities
- Difficulty staying compliant with increasingly tight data regulations due to poor-quality data and extraction delays when reporting
- Slow speed-to-insight and limited scalability as your data volumes grow
- Employees struggling to access the data they need to work effectively
And that’s on top of the huge volume of manual effort involved in validating, cleaning, and analysing data to turn it into actionable insights – ultimately diverting key talent away from more valuable tasks.
After identifying your data spine challenges, you’ll need to start making strategic changes to enable everyone to get the most from your data.
5 WAYS TO START FIXING YOUR DATA SPINE
Whether you fully understand your data challenges or have just started assessing your infrastructure, fixing your data spine can be a challenging journey. Follow these five strategic steps to make it as seamless and efficient as possible:
1. Build a multi-disciplinary team
Fixing your data spine requires a set of skills aligned around a single goal, the core of which should include data engineers, data analysts, data architects, and data scientists. Over time, you may also need to introduce additional talent, such as cloud architects to strategise migration, API design experts to unlock data access, and subject matter experts to clarify semantics, event-driven architectures, and more.
2. Leverage industry best practices and the latest technology opportunities
To help tie your data spine team together, you’ll need somebody with knowledge of industry best practices and principles. This will prove hugely beneficial when exploring new and emerging concepts, such as data mesh, where limited reference architectures exist and implementation can be complex. Partnerships with established third-party vendors can also help provide access to valuable resources.
3. Involve somebody who can adapt to your environment
It’s vital to account for your legacy systems and organisational processes when implementing new data solutions. For example, you may find that solutions like data mesh architectures are incompatible with your existing environment.
The right experts should be able to assess your existing business makeup – including your skills, regulatory obligations, and scalability requirements – and support you in adapting to and integrating an appropriate data solution.
4. Aim for self-service
Data visibility and ease of use are critical to encouraging engagement with data across your organisation, so you’ll need to ensure that whichever solutions you choose are easy for your teams to engage with. That includes educating them on how to get the most out of their new data platform.
I also recommend introducing self-service tools so your talent can access the data they need anytime, anywhere, in a single, easy-to-use digital environment. Introducing metadata and cataloguing will also go a long way to improving data accessibility.
5. Automate everything
Cut out the mundane data processes. Using AI-assisted tools, automate simple rules-based tasks, data analytics, insight generation, data cleansing, and other crucial data management responsibilities.
This will help you build a data spine that works for you rather than consumes your resources. Automation can also help improve security by removing the risk of human error and detecting and preventing breaches before they cause significant disruption. It can also complement digital innovation, such as enabling natural language processing (NLP) tools to extract data faster and scale to meet demand.
A TECHNOLOGY PARTNER YOU CAN TRUST
Fixing your data spine is a journey that you shouldn’t take alone. At Endava, we have decades of experience helping banks fix their data spines. We can help you gain the agility, scalability, and intelligent automation you need to empower your people to get more from your data so they can focus on what they do best – driving innovation and building lasting customer relationships.