Tag: data governance

Our previous discussion focused on the data retention aspects of our data governance programs. Policies must be defined early, shared via data literacy programs and technical controls built to automate the retention, protection and purging of data. These policies are…

Previously we discussed the growth in certain types of data, specifically data lineage. Data lineage information allows us to programmatically build systems that respond to changing conditions of data access, data quality and consumption.   Another type of data that is growing…

Previously, we discussed metadata and how it has become the connective glue in modern data architectures that allows different technologies to have common layers of reference for process and access automation. Centralized metadata storage through common data catalogs and features stores…

Episode 60 Shownotes Welcome to another episode of the Datascape Podcast. VP of Analytics Joey Jablonski joins us to discuss data-related trends and challenges, as well as his 20+ year career in technology, including his time at the US Department…

In our previous discussion, we explored the role of data stewards and their vital function for data governance programs. They’re the champions that identify data quality shortfalls and work with business partners to improve data quality. Data stewards are the…

In our previous discussions, we evaluated how to kickstart our data governance programs. We discussed the cultural principles to be set, priorities to be communicated, and roles and responsibilities to be established. These elements ensure alignment in execution for data…

In our previous discussions we reviewed the two primary dimensions to a data governance program. First are the functions necessary to be successful including compliance and risk management, policy, data management, literacy, and architecture. Second is the organizational model for how these capabilities…

In our previous post we discussed the five phases of data governance programs. These include define, design, build, transition and measure. These phases allow us to plan work, execute, and understand a program’s impact while adjusting future prioritization and maximizing…

As organizations embark on their Data Governance journey, many struggle with justifying the costs with program outcomes that have traditionally been viewed as required but not delivering significant business value. This often pits data governance programs against product initiatives in…

An explainer on achieving consistency, trustworthiness, and accessibility across your data estate. The Wild West might be entertaining in movies or TV, but it’s the equivalent of a horror show when it comes to your organization’s data. That’s why strong…