Transportation organizations in the infrastructure construction industry are developing data analytics strategies and are striving to become more data driven in their decision-making practices. This is creating greater dependence on treating data as an organizational asset and the recognition they must put in place the foundational aspects for better data management processes. In addition to a goal of data analytics and data driven decision-making, organizations are expected to have high quality and accurate data for myriad reporting purposes, whether to legislative bodies, 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 foundational aspects of a modern and mature data focused organization. 

Data Management is the process of managing your data environment to ensure it is available, reliable, and secure. The foundational elements of data management include:

Data Governance

Data governance refers to how policy and processes around how data is collected, stored, accessed, and maintained in a repeatable and structured manner. This includes assigning responsibility to staff to act as data owners, data stewards, data custodians, and includes documented policies and processes related to how data is managed in their respective organization.

Data Objectives

Data objectives refer to a simple, essential question - are you collecting the right data for the right purpose? Having a good plan for how you intend to use your data is essential for data driven decision-making and predictive analytics. This should include an analysis of how data will be used in your organization and to answer the questions of what strategic initiatives is your data supporting, and who your stakeholders are.

Data Storage

A well-designed, scalable, responsive, and adaptable data environment is important as well. Many organizations are developing a data warehouse to manage their data environment that is flexible and adaptable to the changing business needs.

Data Catalog/Inventory

Having a clear picture of your data environment, documented metadata, and processes in place to ensure it is kept up to date is a critical element of good data management. You need to understand what data you have and the characteristics of the data environments, and you need to know what you have to effectively manage it.

Data Quality

Ensuring accurate, complete, consistent, and up-to-date data is a must for making decisions, and having data-quality standards in place is essential.

Data Integration

Gathering data from various sources to create a unified platform (one stop shop) is necessary to help break data and business silos.

Data Accessibility