Real-World Big Data for Active Transportation Planning

whitePaper | August 25, 2022

Most organizations realize data governance is necessary - if not indispensable - for mitigating data risk while sustaining its longterm value. However, there’s still a fair amount of ambiguity around what exactly data governance is and how to best implement it. By definition, data governance is an enterprise-wide initiative for formalizing the processes, people, and protocols for using data. It reduces risk while increasing data’s ultimate value: consistent reusability for achieving mission critical objectives. Data governance is a strategic approach for creating unassailable trust in data throughout the enterprise.

whitePaper | May 6, 2022

Every organization today recognizes the strategic value of generating actionable insights from their enterprise data.

whitePaper | August 25, 2022

Everyday user experiences are being completely reimagined. Requesting a ride through an app is better than calling a cab. Buying online is changing the way we go shopping. And gone are the days of waiting in long lines at your local bank. Data within these modern businesses is in constant motion, flowing, in real-time, across systems, environments, and applications every time a user interacts with the system.

whitePaper | September 16, 2022

With the 2022 data and analytics edition, we further expand our series of Horizon Reports to focus on an emerging area of practice that is driving institutional decision-making and strategic planning for the future—the trends, technologies, and practices that are shaping the world of postsecondary data and analytics. Based on a methodology that grounds the findings in the perspectives and expertise of a panel of leaders in higher education data and analytics, in this report we summarize the panel’s input on the major trends shaping higher education, including panelists’ reflections on the implications of this research for the future of higher education for particular institutional roles.

whitePaper | October 17, 2022

Today, massive amounts of data are collected, processed, and stored for a range of analytical purposes around the world. Every customer, device, transaction, email, and image leaves a data trail. At present, this data is growing too big, changing too fast, and becoming hyper distributed. The traditional ways of doing integration and analytics are no longer viable or scalable. It is not feasible to create millions of data pipelines and to continue moving large amounts of raw data to a data lake or a centralized data warehouse.

whitePaper | August 2, 2022

The volume of data has exploded across all sectors in the last decade. Enterprise data has grown enormously, and organizations must contend with more unstructured data than ever. In fact, 95 percent of businesses cite the need to manage unstructured data as a challenge.