As digital transformation initiatives continue to be a top priority for organisations worldwide, the volume of data produced by these and other activities continues to grow. 

Consider IDC’s ‘Data Age 2025: The Digitization of the World’ report, which predicts that the global datasphere will total 175 zettabytes of data by the year 2025 – 30 per cent of which will require real-time processing. 

The transformative potential of all of this data can’t be understated, yet many companies are finding that more data doesn’t necessarily equal more insight. According to another survey from Matillion and IDG, ‘Optimizing Business Analytics by Transforming Data in the Cloud’, more than 90 per cent of participants reported struggling ‘to make data available in a format that is useful for analytics’.

Specific data analytics obstacles cited by participants in Matillion and IDG’s survey included ‘a lack of necessary data granularity, manual coding of data pipelines, and difficulty connecting with multiple data sources’. Yet a further one-third of participants reported needing to ‘manually code their data into the necessary format before they load it into business intelligence and analytics tools’.

It’s clear that the era of Big Data is upon us. With that in mind, how can companies both capture necessary data and use it to successfully drive digital transformation? The answer may lie, in part, in data reuse.

The state of the market 

That data volumes are increasing seems obvious and intuitive. We’ve all seen the way technology has grown in adoption and sophistication, including everything from the programs powering new remote work requirements to the ongoing expansion of AI, ML, and the Internet of Things. 

But these trends only paint part of the picture. Additional factors contributing to data growth behind the scenes include, among others: 

• The integration of quality systems with other data silos, such as spreadsheets, custom databases, ERPs, PLCs, and MRPs, which creates a significant volume of transactional data points. 
• Growing reliance on embedded devices, which may account for as much as 20 per cent of all data created by 2025, according to the IDC report.
• Improper backups, which can create duplicate records that clutter systems and make existing data difficult to parse.

Separating the true insights from the background noise generated by large volumes of data is likely to be one of the primary challenges companies face in our ‘big data future’. Yet the way companies store, manage, and protect their data often adds to this complexity. In fact, a report by Veeam suggests that ‘almost half of global organizations are being hindered in their DX journeys due to unreliable, legacy technologies’.

At many organisations, data lives in many different places, including – but not limited to – data centres, the cloud, and shared in-house storage systems. Unfortunately, the legacy tools designed to back-up files and applications on-premises can’t always handle the data requirements of today’s hybrid, multi-cloud world. 

Navigating past this challenge requires that companies commit to updating their data storage and management approaches. Only after this need is addressed will companies be able to fully leverage the value of their existing data through analysis and reuse approaches.

Utilising data already stored in backup systems 

If your business is like many other companies, the odds are good that you’re sitting atop of a mountain of existing data. Learning how to utilise the data already stored in your backup systems comes with a number of business transformation benefits.

To take a simple example, imagine that your website includes an e-commerce component that sells physical goods. You may already be tracking metrics such as new vs. returning customers, customer lifetime value (CLTV), or average revenue per order. But if you’re using any of the common e-commerce platforms, there’s a good chance your system is capturing (or could be configured to capture) engagement and transactional data on a much more granular basis. Identifying trends in this data could improve your ability to connect with customers and to refine your product offerings or on-site workflows to better meet their needs. 

Utilising your existing data also empowers your company to improve its cost efficiencies and overall bottom line. Manufacturing is a good example here, as much of today’s manufacturing equipment captures asset performance data. Using this data to predict maintenance needs has the potential to minimise repair costs and unanticipated down-time – but only if it’s analysed appropriately.

Considerations when utilising existing data

While it’s true that analysing existing data to uncover new insights has tremendous potential, utilising existing data isn’t always an easy or straight-forward process.

For example, if you’ve been collecting data for years without actively using it, there’s a chance that some of the information you’ve captured now runs afoul of current privacy regulations. New compliance guidance – such as the passage of the General Data Protection Regulation (GDPR) – gives customers in some countries the right to access their data and to be forgotten. Holding data that does not comply with these and other requirements may leave your business vulnerable.

Malware is another important consideration, as it can lie dormant in data backups for long periods of time before infecting systems. As you make plans to access and analyse existing data, consider incorporating deep scans of existing backups into your workflow. Going forward, ensure your data backup solution has the appropriate security standards in place to lessen your risk of an attack.

One final piece of guidance is that just because you have access to existing data doesn’t necessarily mean it must be utilised. With seemingly unending pools of information available, it’s tempting to want to leverage every data point possible to drive business transformation. 

However, this approach risks wasting time and resources. Not every stored data point can produce meaningful change. Instead, companies with data analytics services develop strategic data analysis, plans and workflows that will allow them to utilise the data they have gathered to drive improvements that have the impact of connecting with customers in more meaningful ways and delivering real value to the business’s bottom line.

A holistic approach to Digital Transformation strategy

Ultimately, although data reuse holds tremendous potential for the companies that are willing to invest in accessing and analysing their legacy data, it’s only one piece of the digital transformation puzzle. To learn more about digital transformation strategy in 2023, here's a complete digital transformation guide.

By investing in modern Cloud services, as well as appropriate data storage governance and access practises, organisations can position themselves well to take advantage of the full benefits of our Big Data future.

Need more information on cloud services and data backup? Speak to the expert team at Canon Business Services now about the ways your organisation can benefit from cloud services and our entire suite of managed IT services.