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Leading thinkers and technology experts have been talking about data first for decades. But what does data first actually mean? And how can you achieve a data first approach in your digital transformation?
Becoming a data first organization requires serious commitment and a big cultural shift. And it won’t happen overnight.
Data first organizations prioritize business innovation and risk models built around multiple sources of digital intelligence. Data first organizations expand upon API first approaches using a multitude of technologies.
This allows for a more complex flow of data and minimizes the need to re-architect APIs when application needs shift. Data first approaches enable agility in applications and APIs through asynchronous data, GraphQL, and SOAP.
Let’s start by acknowledging that achieving a data-first approach is tough. According to Harvard Business Review, over 92% of mainstream companies surveyed cite cultural and alignment challenges as major stumbling blocks to their data-first initiatives. Furthermore, there’s simply more data than ever before to grapple with. Which means, leadership is often left wondering:
Despite the challenges to achieving a data first approach, the benefits of doing so are enormous.
For many years and continuing to this day, API first approaches to application builds have been popular. Yet, API first focuses on RESTful APIs. This limits the complexity of how data flows internally and externally for the enterprise, while at the same time potentially creating data overflows.
Let’s use customer data as an example. When an application requires customer data, an API is created to provide that customer data. But this RESTful API is limited in what data it can call. For example, if you simply needed a customer telephone number, the RESTful API would retrieve all the data as determined by the design of the API. So in making a call to the API, the application would receive the entire set of data. This adds complexity to performance, cost, and efficiency. Which translates to an overage of data being delivered over the network or cloud, driving costs up.
Additionally, sending excess customer data to an application potentially exposes more information than is necessary. This is a security risk.
GraphQL enables applications to make query-based calls that retrieve just the right amount of data as required by the application. This allows applications to indicate exactly what sub-set of data is required in a specific application task. In this scenario an application can make a call to receive just the customer telephone number (from our example above).
In data first approaches to application development, GraphQL, asynchronous APIs, REST, and SOAP allow enterprises to pick the right approach for the specific situation rather than mandating a particular API strategy.
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Download the white paper, Disrupt or Be Disrupted and learn how to make APIs the cornerstone of your digital strategy.
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Data first might seem elusive and complicated, but it doesn’t have to be. By following a few key principles, you can achieve a data first strategy at your organization. Here are some key components.
Many organizations that achieve data first approaches to application development adopt fail fast cultures. What does this mean? Fail fast is similar to lean, or agile, approaches to application development. It’s a startup mindset that prioritizes:
In the end this approach allows organizations to create innovative applications, products, and services while minimizing development costs to the organization. How? Using the fail fast approach, the impetus is on building quickly versus extensive planning. The goal is to more quickly reveal potential shortcomings, thereby allowing the company to abandon projects earlier if they fail.
Another important aspect to fail fast culture is the concept of pivoting. Companies may start with one idea, start building it, and discover it doesn’t have value. Yet in the process they discover another idea, and then pivot to pursue the new application or service.
Often times we collect all available data, yet we don’t know what it truly means. This is like trying to drink from a fire hose. Instead, we must ask ourselves what’s the story it’s telling. How will I improve my products and services with it? Aside from reporting, is it actionable? And most importantly, how does all data paint a picture that guides the way?
If your team is not able to put specific sources of data to use, your approach to analytics is akin to checking the weather. Here’s how you can go deeper with data across the following categories:
There’s a wide array of marketing data available to modern organizations. Consider investigating correlations between various data points in the following manner:
In all, this is about making connections. Whether behavioral, content, or conversion-based, find ways to weave your metrics into a single narrative that informs product development, marketing, and innovation efforts.
Keep in mind that API management platforms offer a means for connecting all of these data sources in order to view and manage them as a single source of truth.
According to IDC, 65% of global GDP will be digital by 2022. Which means no matter the business you’re in, your digital operations must run efficiently. Data first organizations use performance metrics to inform future builds and track whether digital transformation efforts are performing adequately. Whether you are taking a data first approach with applications, services, or digital transformation, your performance data should remain front and center.
So what should you focus on? It depends. No matter your technology, use the following performance categories to ensure digital operational efficiency:
As we have discussed, the data first approach to enterprise technology requires cultural and technical shifts.
So what does this all have to do with APIs? Full lifecycle API management practices offer the best solution for unifying data first programs. No matter the technology, platform, or data source, APIs can be scaled to monitor and manage the entire data first ecosystem.
When APIs are built to interface with data first software, systems, or applications, they can be used to monitor performance. Furthermore, they can provide analytics on all of the systems which APIs have been built on top of. This means your data first monitoring and analytics processes can be simplified and centrally managed.
Similarly, API management platforms like Akana can be used to unify and manage all of your applications, tools, and platforms. Instead of tackling data first initiatives with custom builds and managing all of your digital entities separately, you can use an API management platform to create a single linked ecosystem.
APIs create a proxy layer in front of your applications, services, and platforms. Which means they can detect security threats before these threats enter into your internal systems. APIs act as the last line of defense and provide an added layer of security to every system they are scaled upon. As you prioritize data first thinking, take it a step further by securing your APIs and systems with API security best practices.
Whether you’re just getting started with a data first approach or are well on your way, the Akana API platform can help you achieve the following:
The Akana API platform offers everything you need to succeed with an API first or data first strategy. Access our out-of-the-box developer portal which allows you can publish, promote, and monetize APIs. You’ll also get the Akana API gateway, which allows you to secure APIs and control access to applications. Finally, you’ll get tools to monitor and support your APIs throughout the entire lifecycle.
See for yourself how Akana can improve your data first initiative.
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