Click to learn more about author Emily Washington.
Forty-two percent of the U.S. workforce is working from home full-time, according to the Stanford Institute for Economic Policy Research — almost twice as many employees as this time last year.
As companies reimagine a post-pandemic workforce, many are either abandoning their office spaces completely or embracing a hybrid workforce.
With the work-from-home revolution here to stay, this new normal requires the right technology and processes to keep information flowing and businesses operational.
While more companies are embracing digital transformation and collaboration tools, there are still many challenges to remote working. Beyond connectivity and issues with VPN and cloud-based applications to access critical information, communication, engagement, and collaboration around enterprise data often suffers when employees are no longer under the same roof.
Working from Home Short-Circuits Data Communication
The model for a digital workplace begins with a Data Governance framework that involves staff from across the entire organization. This includes employees across sales, finance, marketing, customer service, and IT.
Together, they define data processes, access methods, data definitions, and build data catalogs to operationalize effective searching and accessing of data. But as soon as physical proximity is removed, collaborating on any initiative, let alone Data Governance efforts, becomes increasingly difficult.
We have discussed the need to break down silos and improve collaboration for years. And one benefit to working remotely over the past year is that it has shed new light on the criticality of its importance and has forced a major change in the way organizations interact with data. Individuals across the entire organization are finding new and creative ways to become more efficient in their work-from-home environments.
However, despite the modern digital transformation efforts and increased availability of telecommuting apps like Zoom and Slack, business users still struggle to find and access data to complete their data-driven tasks.
As the Data Governance discipline has evolved, requirements in successfully implementing it have evolved with it. With information spread across highly complex hybrid cloud environments, automating the collection, curation, and organization of data has become a top priority to quickly document the lineage across all environments. And increasingly, data analytics and technology teams have been assigned this difficult task, given their understanding of the data structures.
Solving the Data Collaboration Challenges of Remote Work
Data Governance is the foundation of establishing collaboration around enterprise data assets. It brings together data, people, and processes so no matter your role in the organization, you have a clear understanding of where your data resides, what it means, and who owns it at any given time — whether you’re working nine-to-five or late into the evening after everyone is asleep and your home is quiet.
A Data Governance program helps rally all data stakeholders across the organization to agree on standard data definitions. Businesses utilize a data catalog tool to document the meaning and other details about data. However, data definitions are only the start of a modern data catalog.
What Is a Data Catalog?
A data catalog is a detailed inventory of all enterprise data assets. Leveraging insights derived from valuable metadata, the catalog helps users search and find relevant and trustworthy data based on attributes, governance scores, related data, and who else has interacted with the data.
A data catalog typically starts with precise details about technical data assets. Using analytics, the data catalog collects and curates metadata across a wide range of enterprise sources. Data catalogs also provide automated data lineage features. With automated data lineage in the catalog, users can visualize where data flows from one system to the next.
However, to increase adoption of a data catalog enterprise-wide, it is critical to enrich this technical metadata with business context — such as who owns the data from various points of view, including data stewards, business users, technical users, and other subject matter experts. And to enable collaboration and break down silos, it must provide workflow management and other interaction paradigms. Subsequently, users can quickly communicate with the appropriate data owner or search for business context or Data Quality metrics.
Once users see these various dimensions of a data asset, the picture becomes clearer of what data is available.
Benefitting from 3D Data Lineage Visualization
With this business context, data lineage can take on a new meaning. Lineage is no longer about what technical systems data moves from and to. Instead, lineage empowers all users to understand what business processes, governance metrics, and impacts data is associated with. With 3D lineage in the catalog, users have unprecedented contextual clarity into the enterprise data. The different dimensions associated with the data, people, and processes important to a Data Governance program are enabled through the data catalog.
Turning data into a competitive advantage is conditional upon enterprise-wide collaboration. It doesn’t matter if a business is fully remote, has a flexible work environment, or is in the office every day; a modern data catalog is a critical need for communication around data.