Boost your data potential with a modern data strategy

18 July 2023 • 5 min read

Man presenting a modern data strategy

Historically, data has been stored and siloed within the department that created it. But over the last few years, there’s been a growing realisation that data can be an extremely valuable resource when harnessed correctly. The advent of cloud services has driven companies to scale data-related solutions at unprecedented rates and grow exponentially.

In today’s world, building a sustainable business requires constant reinvention to stay relevant to customers and stakeholders – which is a challenge. Less than 50% of businesses on the Fortune 500 in the year 2000 are still there today, and nearly 29% of businesses on the current list are less than 10 years old.

To stay competitive through reinvention, businesses need to be tenacious with the truth, make the right decisions, and take meaningful action to drive their business forward. Data-driven decision making is key to this approach.

The introduction of cloud technologies has significantly lowered the cost of data services and triggered the next wave of data-driven reinvention. In a journal published by Forrester, Richard Joyce stated that a typical Fortune 1000 company will see a $65 million increase in net income, just by making 10% of its data more available. Forrester also estimates that, on average, data-driven businesses grow by more than 30% every year.

To find out how you can build a modern data strategy and data-driven culture that unlocks agility and helps you make the right decisions to drive future growth, get in touch with a member of the AWS team and AND Digital.

Benefits of a modern data strategy 


Data-driven organisations tend to share the following characteristics: 


  1. Data is treated as an organisational asset, not stored in silos by individual departments
  2. Data is collected, stored, organised and processed in a secure way and is accessible to anyone who needs it
  3. Data is put to work via analytics and machine learning (ML), and used to make better decisions, create efficiencies and drive innovation


Unlocking the potential of your data has huge benefits – from improved operational efficiency to better customer experiences – but building a data-driven company comes with its own challenges. 


The first major challenge is the sheer scale of data available. It’s predicted that more data will be created in the next 3 years than in the last 30 years combined, and old on-premise tools and data stores will simply not be able to handle the scale. 


As well as processing large volumes of data, businesses need to unlock the potential of data by breaking down silos and optimising analysis. While some organisations are using disruptive technologies, such as ML, to fuel innovation, many are struggling to make meaningful progress due to a lack of in-house skills. In fact, organisations with artificial intelligence experience only moved 53% of their AI proof of concepts to production over the last two years, indicating a sustained lack of expertise, despite experience. 

And finally, in a world of increasingly stringent data security, privacy and compliance regulations, organisations need to be able to carefully define, monitor and manage who has access to data. 


There are many challenges to overcome, but for your business to thrive, you need a modern data strategy that will grow with you in the future. 


Becoming Cloud Native


To be considered Cloud Native, your architecture must not only exist in the cloud but make use of decoupled cloud services to unlock scalability, performance and cost savings. And in the context of data platforms, you should take advantage of the agility, power and flexibility afforded by cloud platforms. 


Legacy data platforms, generally referred to as data warehouses, are eye-wateringly expensive upfront and often inflexible in their architecture. You can’t easily increase capacity, and buying hardware is the only real option to increase performance. This level of rigidity stifles innovation. 


But as we move away from traditional on-premise solutions and into the cloud, it’s now possible to decouple compute and storage capacity. So if you need to ramp up processing for peak trading, you can. If you need to onboard a large data source without freeing up capacity, you can do that too. Even from a continuity management perspective, you can ensure data is safe and accessible, even in the event of regional failure. And because there’s no physical hardware to manage in house, you can scale up and down as required. You can dial down resources to save money during quiet periods, or scale up to meet increased demand. 


Transitioning to the cloud brings many other benefits. You can plug into managed services to offload infrastructure management entirely to the cloud provider. You can also build your own infrastructure, test the codebase, and deploy through automated pipelines just like any other piece of software.


The cloud brings the flexibility, agility, scalability and capacity required for constant innovation and reinvention. 


Building Cloud-Native data platforms 


When it comes to designing data platforms, engineers have always thrived on finding the balance between cost and performance. But it’s actually more important to balance fast and right


To find what’s right for your business, you need to build a playground-like environment for data analysts and scientists to explore the hidden corners of your data, and experiment to find a new feature or model which could give you the edge. And when they find it, you need to push it into production quickly. You need what’s right, fast.


Data platforms should also be reliable and trustworthy, with the enterprise-grade features and governance found in legacy platforms. You need to be able to monitor the environment and alert any issues or changes, protect data from accidental or malicious corruption, and trace the flow of data through the platform accurately. Your audit and compliance requirements should be met, too – whether you’re evidencing a credit decisioning process or processing personal data in accordance with GDPR. 


So what does a modern data strategy look like? 


While data requirements are different for every business, a modern data strategy combines the best of both data lakes and purpose-built data stores. It enables you to store any volume of data, at low cost and in open, standards-based data formats. It helps you break down data silos, manage access using data governance controls, and empower your teams to run analytics or machine learning using their preferred technique. 


Ultimately, a modern data strategy will unlock the potential of your consolidated and shared data, enabling you to make fast decisions and extract unprecedented value. 


If you’re looking to enhance your data strategy, or further utilise your data platform  on the cloud, get in touch today. 



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