For enterprise architects, the emergence of digital-native disruptors has put the microscope on whether the role is a necessity. While enterprise architecture was always concerned with addressing IT complexity, technological advancements – such as the cloud – have seen enterprise architects struggling to keep pace. With economic headwinds raising pressure on keeping businesses lean, the crosshairs are on enterprise architects. However, looking to cut costs by retrenching enterprise architects, in a bid to emulate tech-savvy upstarts, is not cost-effective for organizations with legacy systems.
Simply put, different organizations have different needs and there is no one-size-fits-all solution. Firms with legacy systems need a modern approach tailored to their needs. Intelligent investment is crucial and the answer lies with leveraging real-time data so that enterprise architects make better decisions and reduce technical debt. But harnessing data in real time hinges on several crucial factors. For enterprise architects to thrive in this new, cloud-native world chock full of digital disruptors, they need to understand the architectural underpinnings of real-time customer experiences.
Business and Technical Implications for Enterprise Architects to Consider
One of the biggest challenges facing many enterprise architects is integrating real-time data solutions with existing systems and data sources to provide a complete picture. There is also a need to handle large volumes of data at high velocities. Then, enterprise architects need to account for high availability and low latency. All while ensuring that the new solution deployed can store and process large volumes of data and ensure intuitive, actionable data visualization, that facilitates stakeholder understanding. In other words, nothing short of a headache.
On the business end, enterprise architects must take stock of how real-time data solutions impact the organization's resilience. These range from data privacy and security policies that are compliant with regulations and laws, to data quality that ensures accuracy and relevance.
Enterprise architects must also understand that real-time data solutions must provide value for money and be cost-effective. Knowing the costs associated with implementing real-time solutions, including hardware, software, and staffing costs, is critical. It is incumbent on enterprise architects to, then, ensure that these costs are aligned with the organization's goals and budget constraints.
Ultimately, real-time data solutions must provide a tangible return on investment to justify the costs of implementation. Enterprise architects must work with business stakeholders to define and measure the ROI of real-time solutions and ensure that the solutions are delivering value to the organization.
The weight of these considerations is nothing to scoff at. The good news, however, is that these challenges can be overcome, as the technology already exists to do so.
Transforming Data in Motion
To truly grasp the power of data, enterprise architects need access to an open data stack powered with real-time AI/ML to empower the business to activate large amounts of data at scale.
Leveraging such a cloud-native database is crucial, as it makes operational data-at-rest easy to use and build on. At the same time, it allows the business to respond to constant motion and act upon data in motion as it is generated.
Fundamentally, this gives enterprise architects the freedom to deploy on demand, without the operational burden, so they can actually bring value to the business.
Go Serverless and Launch Apps within Minutes
With the need for speed, many enterprise architects may find that they run up against a wall because of a lack of native support for their preferred languages and toolsets. Modern enterprise architects need to be empowered with an open-source data API gateway that allows them to create real-time data applications easily with the language and APIs they are already best acquainted with.
This, then, also allows for greater accessibility and significantly less complexity by enabling the pivot to a cloud-native architecture that embraces openness and abstracts complexity.
By going serverless, enterprise architects can ensure that teams are able to use their favorite tool and language to deliver scalable, resilient apps on any cloud. With no infrastructure, configuration, or operational distractions to worry about, the focus can then be on what really matters — delivering the best performance and digital experience for your users and business.
Serverless architecture also allows massive scale without compromising performance. When enterprise architects can configure consistency individually for each read and write operation, there arises the opportunity to precisely control how to manage trade-offs. All this then enables enterprise architects to adjust consistency, availability, and performance accordingly, in service to delivering the real-time experiences customers demand.
Enterprise Architects Are Key for Evolution
The data management needs of the average organization has changed dramatically over the last decade. In particular, businesses with legacy frameworks have been playing catch up, not knowing how to make the next step in the face of digital-natives usurping them.
Inevitably, there has been a scramble to leverage real-time data, but often enterprise architects have had little in the way of support as far as efforts to rethink data is used. With the proliferation of large-scale, globally distributed data, organizations must implement corrective measures that steer them down a different path.
To stay relevant, organizations need to ensure that enterprise architects are equipped to manage a consistent technology stack.
This goes beyond just capturing and warehousing data. On the contrary, enterprise architects need the provision of technology components to develop, deploy, and test new functionalities. As a consequence, the organization can activate data in real time to deliver in-the-moment customer experiences, create instant intelligence, or fuel machine learning.
Not only will this ensure the business can actually deliver on real-time experiences, it will tangibly benefit the business by avoiding the pitfalls of poorly scaled pilot functions, such as technical debt, and ensure innovation that is faster and better. And it might just ensure that enterprise architects have a key role to play in the future of their organizations.
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