In a post-COVID-19 world, remote access has rapidly emerged as the new normal, for every organization. The shift to a remote-first world was already well underway. In fact, in 2019, 54% of U.S. workers reported working remotely at least once per month. But there’s no question the pandemic has accelerated inevitable change.
According to Gartner, 74% of CFOs expect to permanently transition many employees to remote work. In spite of all the disruption, these changes are also opening up some new opportunities to help employees be more engaged and satisfied—and get more done while they’re at it. Another survey by Kickstand Communications found that 85% of employees enjoy working from home, while 27% say they’re more productive.
In the healthcare arena, providers are responding to the COVID challenge by making healthcare services more accessible to more people, through self-service. For example, Babylon Health has launched an automated new service to provide people with self-service mobile access to real-time diagnostics, consultation, and symptom logging, all powered by artificial intelligence (AI). Healthcare providers and office staff save time, while staying safe by interacting with patients remotely.
Self-service is gaining momentum across the enterprise, as people increasingly expect an effortless experience at scale. We’re already seeing it in service desk use cases that let business users trigger automated workflows like password resets, ordering new laptops, and other tasks. Like many tech professionals, data engineers are increasingly working remotely, and equipping them with a self-service approach to working with data could bring these types of benefits to the data world, to enable them to accelerate digital transformation and get solutions to market faster.
All too often, today’s data engineers spend much of their time going back and forth between infrastructure teams and business stakeholders to get access to data. There’s no reason why they shouldn’t be able to take advantage of more self-service approaches to working with data. The key is getting the right data to the right people, so they can ask and answer their own questions.
Data is the product, and owning it end to end is the best way to serve it. But to do it, you need the right tooling for engineers and their business partners to support a self-service system, so they can work with data from anywhere. You also need to improve accessibility using a baseline like SQL, to reduce the threshold for developer productivity. Setting up a common way to talk about data also makes it easier for business partners to collaborate in your data initiatives and provide context and guidance.
A data mesh architecture is a natural for empowering data engineers who are working remotely. It’s all about accessibility and personalization, and it lets you move beyond centralized, monolithic data warehouses and data lakes to deliver access to data at scale. Instead of struggling with the limitations of a data lake, you can utilize a distributed data architecture that’s owned by cross-functional teams. Although a data mesh is very much an ecosystem, it provides centralized governance and is standardized for interoperability.
