Transportation organizations in the infrastructure construction industry are developing data analytics strategies and striving to become more data-driven in their decision-making practices. This is generating a greater reliance on the treatment of data as an organizational asset and the recognition that they must put in place the fundamentals for better data management processes. In addition to the goal of data analysis and data-driven decision-making, organizations are expected to have accurate and high-quality data for a myriad of reporting purposes, whether for legislators, constituents, customers or for more formal audit and compliance requirements. Finally, as transportation agencies pursue digital delivery as part of their core business, having good data management practices is becoming essential. This blog will explore the fundamental aspects of a modern, mature data-centric organization.
Data management is the process of managing your data environment to ensure it is available, reliable and secure. The core elements of data management include:
Data governance
Data governance refers to how the policies and processes on how data is collected, stored, accessed and maintained in a repeatable and structured way. This includes assigning responsibilities to staff to act as data owners, data managers, data custodians and includes documented policies and processes relating to how data is managed in their respective organisation.
Data objectives
Data objectives address a simple and essential question: Are you collecting the right data for the right purpose? Having a good plan for how you want to use your data is essential for data-driven decision making and predictive analytics. This should include an analysis of how the data will be used in your organization and answer questions about what strategic initiatives your data supports and who your stakeholders are.
Data storage
A well-designed, scalable, responsive and adaptive data environment is also important. Many organizations are developing a data warehouse to manage their data environment that is flexible and adaptable to changing business needs.
Catalogue/Data Inventory
Having a clear picture of your data environment, documented metadata and processes in place to ensure it stays up-to-date is a critical element of good data management. You need to understand what data you have and the characteristics of your data environments, and you need to know what you need to manage effectively.
Data quality
Ensuring accurate, complete, consistent and up-to-date data is essential for decision-making, and having data quality standards is essential.
Data integration
Gathering data from multiple sources to create a unified platform (a single window) is needed to help break down data and business silos.
