Data management is the technical implementation of data governance. It is the process of executing and enforcing policies and processes that have been established by data governance. Data governance is a broad set of policies that are implemented across the organization, while data management is more limited and focuses on executing the specific processes that support the data governance policy. One of the best practices in business data management is to establish data governance according to the recommendations of standards such as ISO 38505. This will ensure that only authorized users have access to the necessary data.
Matillion Data Loader makes it easy to transport your data to the cloud data stores of your choice, allowing you to create a single source of veracity for your data. Poor data quality affects everything from analytics and business intelligence (wrong conclusions are drawn) to employee productivity (time wasted due to repetition of work and poor work). To prevent this, both the DBA and the business unit manager must coordinate with their respective teams when making changes or implementing new programs that affect business data. Tracking the data lineage will provide your organization with visibility into how data moves through your systems, allowing you to optimize organizational decision-making and the cost of data management.
In addition, enterprise data management also offers an internal benefit to organizations by reducing the time spent on new data regulation. For example, a financial institution could employ operators to manage market data and analysts from investments to manage customer transactional data. The Databricks team organized a fantastic conference with thousands of partners, customers and technology evangelists to learn from.