Digital transformation is a term that has encapsulated the modern business landscape in recent years. Yet, despite it never being far from the boardroom agenda, research shows that 70 percent of digital transformation initiatives fail to reach their stated goals. Every failed initiative represents a drain on business resources, both in terms of time and money. And, in our hyper-competitive environment, this is something businesses can ill-afford.
The fact is most businesses still don’t understand that true transformation means more than simply ‘going digital’. Blinded by the buzzword, they are failing to see what separates a true and effective digital transformation initiative from a false one—data.
In recent years, many IT processes have become more streamlined; applications have been moved to the cloud, compute and code have been automated. However, traditionally businesses have held back when it comes to data—considering it riskier in terms of compliance. This is especially apparent among enterprises with complex and tangled multi-generational infrastructure. For organizations looking to achieve true digital transformation, data is the last automation frontier.
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The key differentiator
Modern businesses need access to streamlined, fast, and automated data. This is where API-driven data automation comes in.
Put simply, an API—or an Application Programming Interface—provides simple, uniform ways to request data from all sources across an organization, from mainframe to cloud-native. This is essential for the success of digital transformation initiatives as it increases visibility and enables the sharing of lightweight data across teams, testing environments, and IT processes.
An API-first platform that automates data delivery eliminates friction in coordinating work across teams and manual tasks such as database, infrastructure, and security management. By automating these everyday processes, it enables IT teams to focus on more valuable work and increase productivity. In fact, IDC found that IT staff productivity levels increased by 24percent when one of these platforms was in place.
As well as increased productivity, the research indicated that companies with modern data capabilities—such as those driven by APIs—are better positioned to deal with unplanned outages. This is because software bugs and usability glitches make up the majority of production operation challenges. When companies trace the cause of those defects, it often all comes back to stale and incomplete data in non-production environments.
API-driven data automation helps to streamline end-to-end integration testing, thereby accelerating and improving testing processes and reducing the number of errors per application. Application development teams can use these platforms to enable shift-left testing and find bugs earlier in the overall SDLC (software development lifecycle) before hitting UAT (user acceptance testing) or production, making it easier and less expensive to fix. In fact, IDC found that the majority of companies experienced a reduction in the number of errors reaching UAT by 55percent, which reduced the need to retest and recode. This led to better quality and speed with less rework time.
Of course, fewer outages mean less unplanned downtime, which can mean huge cost savings for organizations. IDC’s research predicted that, on average, businesses are clawing back about $72,000 in lost revenue through improved data availability.
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Increased innovation without compromised compliance
In today’s competitive landscape, digital transformation can’t just be about doing the basics. Companies need to invest in innovation to stand out from the crowd and attract and retain customers. For example, application development is often referred to as the innovation driver and difference-maker for the modern enterprise. IDC forecasts that by 2023 more than 500 million new digital applications will be developed, which will only widen the chasm between the technically nimble and the legacy encumbered.
Organizations need to be able to access data efficiently and quickly in order to innovate. However, this data also needs to be safeguarded and compliant with data protection regulations. If it isn’t, organizations not only risk huge financial costs but also severe reputational damage which won't be easy to recover from.
Data masking is one method organizations can use to secure data whilst still driving digital innovation. It is particularly effective when it comes to working in QA environments to test and analyze data. This is because masking data still keeps some of its integrity.
Profiling and anonymizing sensitive data such as Personal Identifiable Information (PII) and Personal Health Information (PHI) for use in non-production environments is a key component of a holistic data governance program. API-driven masking leverages regulation or application-specific algorithms to accurately de-identify data while maintaining referential integrity for comprehensive testing, whether on-premise or in cloud environments. For example, zip codes are replaced with generated zip codes that mask the actual zip code but preserve regionality. Similarly, a masked credit card number will still have certain characteristics of a real credit card number, without risking security or compliance.
With API-driven masking, the data is precise enough to be useful, but vague enough to prevent the identification of any individuals. Essentially users can mask data across multiple platforms whilst still ensuring usability. This supports wider innovation without compromising on compliance.
Every company is a data company
Digital transformation has undoubtedly become the number one mandate at the top of every business leader’s list of priorities. However, without automated access to the correct data at the correct time, any strategy is doomed to fail from the very beginning.
At a time when companies are facing a never-ending stream of challenges and disruption—whether it’s increased customer expectations, concerns around compliance and the consistent pressure to innovate or even the impact of a global pandemic—they cannot afford to be bogged down by inefficient data processes and operations.
API-driven data automation—which combines data delivery and data compliance—is the final piece in the digital transformation puzzle. By incorporating it into a wider business strategy, every company can truly become a data company. And a growing data company at that.
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Dan Graves, CTO, Delphix