CEO of Infogix & a visionary executive with over 30 years of experience in all aspects of growing innovative software companies.
Every year, data management tools evolve, data intelligence mining processes mature, and barriers to transforming enterprise data into a legitimate business asset erode.
This situation creates problems for departmental staff across the enterprise who rely upon on-demand, self-service data to improve processes, build client relationships, accelerate product innovation and develop business growth strategies.
Throughout 2020, we saw advances in integrated data technologies that augment data processes and procedures through comprehensive automation features. Still, as new technologies continue to shape our future and state-of-the-art solutions are introduced, companies won’t survive if they’re still hampered by ill-defined processes, business roadblocks to data and inadequate technology.
The State Of Business-Ready Data In 2020
According to a NewVantage Partners’ survey (via Harvard Business Review), 53% of organizations admit that they do not treat data as a business asset. One of the most significant barriers preventing business users from leveraging enterprise data is internal priorities within different departments. For example, let’s look at the constraints and challenges IT teams face.
We know IT resources are swamped as they navigate complex regulatory requirements, manage organizational data and communications, and handle companywide systems and databases. However, most business users who often don’t possess the technical skills necessary to understand and prepare data for enterprise use rely on IT to locate the business data critical to their projects. When deadlines go unmet, they get caught in an endless loop of follow-up with IT and project delays — and by the time they receive the data they need, it’s often too late to make a difference.
With IT departments more underwater than ever before, many organizations have begun fully embracing automated self-service technologies that are fast, easily accessible and reduce costs, thereby releasing IT to do what it does best.
As part of the move to self-service business-ready data, many organizations have prioritized knowledge discovery to integrate disparate systems and make it easier for business users to find and track information. One example is developing a data catalog that acts as a single source of data knowledge for an enterprise.
To establish a data catalog detailing business knowledge, organizations unite all data management efforts under an enterprise data governance framework. Data governance streamlines cross-departmental communication among all data users, including business and IT stakeholders, aligning users around the goal of extracting value from data. It gathers both business and technical knowledge distributed across diverging lines of business.
Through governance, businesses define and agree on standard business definitions and rules as well as imposable data standards across departments. Data governance also assigns data owners, stewards and users for critical data assets. Together, they track and document data lineage — the foundation of the data catalog that outlines data’s origin, where it travels and how it is consumed.
Before the pandemic, many companies started their business-ready data catalog initiatives. However, some did not consider that building a data catalog and tracking lineage relies on open communication lines.
By March, when the pandemic struck, most companies were forced to adjust to new, more complicated ways of communicating. Leaders ushered workforces into remote working, removing physical proximity between data users. This transition seriously hindered enterprise communication around data, forcing many companies to delay or place their data catalog initiatives on hold.
The Pandemic Shifted Priorities In 2020
With nearly 100% of workforces telecommuting and hosting virtual meetings, organizations adapted and began adopting new technologies to enable remote communication. As a result, we saw significant usage around Zoom and Slack applications to support videoconferencing and instant messaging.
This increased usage of remote collaboration tools and communications highlighted companies’ need to ensure data security and privacy and protect themselves from cyberattacks. It also underscored the importance of adopting cloud services, installing the right infrastructure and rethinking how data users quickly find the correct information.
Fast-forward to today. Organizations continue to invest in modern systems, platforms and tools while updating business and data management processes.
As we start the new year, companies are beginning to think about the next steps to take, including building a 3D view of data lineage in their data catalog to connect data to business context.
Achieving Success With Data In 2021
A data catalog with 3D lineage should guide businesses toward data success in 2021 and beyond. Having business context around data is a must to advance data-driven initiatives in remote work environments.
To design a data catalog with 3D lineage, companies must adapt their data governance framework to solve additional data challenges. While governance helps track and document standard data definitions, ensuring data quality is still a challenge. By incorporating data quality controls within a data governance framework, organizations can establish accurate, consistent and reliable data in the catalog.
Data governance and data quality are the foundation of building a data catalog with 3D data lineage, but automated tools are also critical. Businesses must look for a tool with a suite of automated data governance, data quality, data catalog and data lineage features. By deploying a comprehensive tool, organizations can establish a 3D view of lineage and strengthen data literacy — even in a remote work environment.
With 3D lineage, organizations can provide additional transparency into enterprise data. For example, 3D lineage can enable organizations to quickly track data’s origins and identify and resolve the root cause of data quality issues. It can help business users understand the effect that data has on various business processes. Most importantly, 3D lineage can connect business knowledge to data assets for a business-ready data catalog.
Is your business set up with a self-service, business-ready data catalog that includes a 3D view of data lineage for data success in 2021?
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