Article written by Antonios Chalkiopoulos
Sometimes an unexpected challenge can open up new perspectives — and point a way forward toward new opportunities. For enterprises seeking to maximize the value of their digital data, the current healthcare crisis can deliver insights into how you can create a foundation for a more agile, outcome-focused organization.
Complexity has been quietly growing within enterprises for years. Multiple projects are constantly underway at large organizations, where multiple teams are often working in parallel. Although coordination between these diverse teams and professionals is not always an obvious problem, hidden vulnerabilities can take shape over time. The chances of duplicate and parallel work can steadily grow, creating inefficiencies and expense. When a crisis emerges, issues that had been hidden can spring to the forefront. For our current situation, companies recognized the urgent need to respond with agility, mitigate its impact and maintain business continuity. Making data the protagonist while minimizing inefficiencies in project deliverables and engineering is the key.
Data Observability And Socialization Are Fundamental
Enabling data observability, socialization and collaboration is a key first step for organizations to be able to respond to new challenges fast — and forge a path toward long-term opportunities. Data is tremendously rich with potential and drives every business. However, without the right context and understanding around the right data, we can’t make the best decisions.
Data observability creates a transparent environment that helps data engineers to be more efficient and businesses to better leverage the power of data. It helps bring together and enhance the business and technical processes, enabling us to discover and understand what is happening across different project streams so that we can find the best synergies between people and processes. Data observability also builds a foundation to support the next step forward: data socialization.
Businesses have long been aware of the benefits of data democratization. However, data socialization happens at a broader level. It helps foster a more collaborative environment, increasing visibility further up the pipeline. It also enables people to see deeply into their organization’s data, applications and logic — and understand them – so they can start talking about driving new experiences to deliver additional business value. The result is a “dialogue for data” that actively engages employees and helps keep them aligned to driving business outcomes.
Data socialization is essential to empowering people in different roles with the context they need to succeed. Businesspeople may not always understand technology, just as engineers may not have clarity into business imperatives. Bringing two disciplines together lets organizations intermix their perspectives and share experience and expertise. With a broader, deeper understanding of data, business and technical professionals can move forward together to deliver more meaningful business results.
The Opportunity To Embrace Open Source With DataOps
How can organizations move forward on their journey toward a DataOps-driven enterprise? The first step is a shift in mindset: Make data socialization part of the mission of every product and deliverable, encouraging teams to broadcast activities to the organization.
Open-source technology is helping redefine how we deliver data software-related projects, and as it consolidates and winners emerge, it will become easier to implement. When combined with a DataOps approach, its advanced capabilities can point the way toward a more data-driven organization. Spanning multiple disciplines and skills, DataOps practices foster an environment where people can collaborate, reduce process complexity and fully optimize the use of their data.
Many businesses are recognizing the importance of this environment. In fact, according to a recent 451 Research study, 90% of those surveyed said their businesses would be increasing their investment in DataOps technology this year. But where should companies start this increase?
The first step toward implementing DataOps is to choose a platform and a mesh of preferred best-of-breed data technologies to make all data projects, applications and business logic accessible, addressable and understandable. They should seek out accessible solutions that require a low knowledge threshold, such as SQL, so that a wider array of people can utilize the platform and technologies.
To help ensure that this collaborative approach is effective, organizations should also devise a system to measure team and individual performance on how much data they share across their organization.
DataOps also encompasses the notion of a data and application catalog. The automated, intelligent use of metadata can enable organizations to offer a “Google Search” experience to a wide audience of internal users. At the same time, it can offer a “Google Maps” view into how people and applications are using that data. This perspective empowers business and technology leaders to find and understand data — and to gain better insight into how applications and people interact with it.
Keeping Data Ethics Top Of Mind
Data ethics is fundamental for any data-driven organization. As you unleash more potential of data, it’s important not to lose sight of the tremendous responsibility data brings. Tim Berners-Lee, one of the creators of the World Wide Web, recently critiqued some of the pitfalls of technology and proposed a “Contract for the Web.” One of its key principles focuses on “supporting corporate accountability and robust privacy and data protection by design.”
Implementing a focus on data observability and socialization provides the visibility and accountability that can enable organizations to better uphold data ethics.
The first step in establishing this accountability is to make data more observable in order to improve transparency into who is working with data — and how. Then, organizations can go a step further to socialize it. Data socialization focuses on bringing business and technology stakeholders together to collaborate in real time and discuss whether data is utilized in an ethical way.
It’s clear that organizations across every industry are facing unprecedented challenges. But with the right approach, organizations can rethink how they deliver data and software-related projects, especially while embracing new open-source technologies.
By making a robust data optimization strategy a fundamental part of their mission, organizations can respond faster to immediate challenges — and tap new efficiencies and business outcomes.
Original Source: https://www.forbes.com/sites/forbestechcouncil/2020/05/28/in-the-face-of-a-crisis-why-data-and-dataops-are-key/#76cabcb24a3a