In this special guest feature, John Wills, Field CTO at Alation, discusses creating a culture of data consciousness and the five ways he has seen to work best. John focuses on strategic customer and partner advocacy, supporting strategic opportunities, and closely following industry trends to help craft corporate strategy and product priorities. John has 30+ years of experience in data management with a number of startups and service providers. Throughout his career, he has had concentrated experience in data warehousing, BI, data integration, metadata, data governance, data quality, data modeling, application integration, data profiling, and master data management. John also holds numerous architecture certifications and has authored several methodologies.
Whether you call it the data boom or the data revolution, the amount of data produced globally is rising exponentially. As a result, organizations have started implementing a myriad of technologies to find, understand, and trust their data in order to enable data-driven decision-making. Yet, this surge in data has created another challenge for organizations – data silos.
Data silos occur when pockets of information are stored across various systems, departments, and applications. Data silos are not necessarily a new challenge for organizations. Before the internet, silos occurred when departments failed to share information with each other. Today, increasing use of technologies across teams and departments that create, manage and own their own data sets can result in silos.
While data silos are not intentionally created, they tend to grow over time. The negative side effect is that they create cross-functional, enterprise inefficiencies. Decision accuracy also suffers because it’s unclear and unknown if the best and most complete data is being used to represent the current state of reporting and future projections. Additionally, significant time is spent searching for data and trying to understand if it’s trusted, accurate, and reliable each time a new question is asked. When data isn’t reused and corporate knowledge isn’t retained, transparency becomes opaque.
Data is the foundation for today’s organizations and removing data silos while improving transparency is critical to make better decisions faster. The solution is to implement a data culture: a strategic culture initiative that requires executive buy-in, and most importantly, is valued by each individual in an organization. A strong data culture encourages data literacy at all levels and increases transparency across the organization.
Building the Case for Data as a Key Corporate Asset
Many of today’s Chief Information Officers (CIOs) and Chief Data Officers (CDOs) understand the power of data and how it can be used as a competitive advantage. These leaders also understand the risk tied to data silos. For some organizations, this may not be enough to develop a culture where data literacy and transparency thrive. Executive stakeholders must also see data as a key asset to driving revenue and competitive advantage. This often begins with the CEO and trickles down to all levels of management. From executives to middle managers, everyone must understand and believe that the speed, confidence, and effectiveness of their decisions are rooted in data transparency and trust.
Organizations that don’t recognize data as a corporate asset or struggle to understand the importance of data transparency, won’t succeed. In the most successful organizations, the CIOs, CDOs, and data management leaders are accountable for facilitating and implementing the transparency process. But, the functional business stakeholders are the ones responsible for communicating the importance of data and cascading it down through their teams.
Building a Data Culture and Driving Greater Transparency
After securing executive buy-in, the next step to building a data culture and providing transparent access to data lies in the technology and the approach to driving enterprise-wide data awareness and transparency. Key tech enablers and approaches include:
- Implementing capabilities that represent a lifecycle of collection, improvement, and reuse: Automate harvesting of data assets; provide data search and discovery; crowdsource curation for data classification and description; social voting, commenting, and collaboration; and provision request automation.
- Provide data literacy training for all: Drive a company-wide data literacy training and certification program. This allows everyone to share the same perspective, vocabulary, and basic analytic skills.
- Inclusion in onboarding: Each functional business unit and area should include data training as part of their employee onboarding. The training should provide a review of an organization’s authoritative data and data-related assets, the process to maintain them, and an expectation for how employees should participate.
- Recognize and reward employees: Recognize and reward your employees for their contributions. This can be done through company-wide awards, newsletters, or shout-outs from the executive staff. Each recognition further reinforces the data culture.
- Report provenance: A more mature goal is to aim for an organization that is trained to expect standard indicators (metadata) associated with every report and dashboard they use. These indicators communicate what is known about the supporting data, which translates into a level of confidence.
While data culture won’t resolve all data silos across an organization, it will create transparency needed to improve data posture. Instilling a data culture starts at the top. Executives who value data culture and put that passion into practice by understanding data is an asset have a distinct advantage in the marketplace.
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