Many organizations including the intelligence community, security organizations, law enforcement, regulatory bodies, news organizations, and non-governmental organizations work together to disrupt transnational crime networks. Their missions include combating illicit trade; disrupting human, animal, and narcotics trafficking; detecting money laundering; and exposing political corruption. This community needs rapid analysis of large, diverse streams of information about air transportation networks, because air transportation is the fastest way to conduct illicit trade internationally. The nonprofit Center for Advanced Defense Studies (C4ADS) built the Icarus Flights application to meet this need. By building on AWS using managed cloud services, C4ADS spends less time and energy managing infrastructure, which frees them to focus on building innovative analytics and alerting services that their user community needs.
Modern data engineering covers several key components of building a modern data lake. Most databases and data warehouses, to an extent, do not lend themselves well to a DevOps model. DataOps grew out of frustrations trying to build a scalable, reusable data pipeline in an automated fashion. DataOps was founded on applying DevOps principles on top of data lakes to help build automated solutions in a more agile manner. With DataOps, users apply principles of data processing on the data lake to curate and collect the transformed data for downstream processing. One reason that DevOps was hard on databases was because testing was hard to automate on such systems. At California State University Chancellors Office (CSUCO), we took a different approach by residing most of our logic with a programming framework that allows us to build a testable platform. Learn how to apply DataOps in ten steps.
In a world where data is produced and handled at unprecedented speeds and quantities, the need for effective methods to securely store, analyze, and interpret this data is more important now than ever. As agencies within the U.S. Department of Defense and Intelligence Community turn to cloud adoption, they are able to bring new capabilities closer to the tactical edge and accelerate their digital transformation. Agencies can effectively leverage these new technologies such as AI, ML, and data analytics to free up time and resources for warfighters and analysts to focus on mission critical tasks.
While disruptive events are challenging for any organization, sudden and large-scale incidents such as natural disasters, IT outages, pandemics, and cyber-attacks can expose critical gaps in technology, culture, and organizational resiliency. Even smaller, unexpected events such as water damage to a critical facility or electrical outages can negatively impact your organization if there is no long-term resiliency plan in place. These events can have significant consequences on your employees, stakeholders, and mission, and can result in long-term financial losses, lost productivity, loss of life, a deterioration of trust with citizens and customers, and lasting reputational damage.
The University of Illinois Urbana-Champaign (UIUC) believes that technology is a powerful tool for driving results and innovation on campus. Their chief information officer, Mark Henderson, developed a task force—called the Data and Technology Innovation Lab—to identify department challenges and task individuals to build innovative solutions using technology. One area where UIUC identified an opportunity was sports analytics using machine learning (ML). Learn more about how UIUC was inspired by what they were seeing in professional sports, using data to shift their approach to coaching football.
The impact of COVID-19 has K12 and higher education institutions working hard to prepare for students to return to learning that will be anything but typical. The 2020-2021 academic year will include various teaching and learning modalities—virtual, hybrid, and face-to-face—and most expect a shift from one to another throughout the year. Globally, EdTechs are working with AWS to accelerate features and solutions to better support students and educators in teaching and learning, physical and mental wellness, and health and safety.
Public sector organizations are experiencing a high volume of requests for information ranging from health to finances to municipal services. At a time when in-person interaction is limited, citizens can call into contact centers to get the insights they need to make real-time decisions about their health and safety. Many organizations are turning to the cloud to quickly scale and deploy a contact center. But, understanding your cloud contact center at granular level can help better serve your constituents.
Organizations across the globe are using advanced analytics and data science to predict and make decisions. They are finding ways to use their vast and diverse data stores to predict the best place to put their next retail store, what products to recommend to customers, how many employees they need for peak hours of operation, and how long a piece of machinery has until it needs maintenance. Public sector organizations in government, education, nonprofit, and healthcare are looking to use data to advance their missions too. Learn how.
OSU-OKC upskills its workforce and drives real-time decision making with live reporting and analytical modeling
Oklahoma State University in Oklahoma City (OSU-OKC), a two-year, technical-focused college, has historically faced challenges with consistent reporting, database management, and analytics. Technology generalists hired to do these tasks required extensive training to successfully extract data from traditional student information systems, manipulate data for state and federal compliance reporting, and generate limited campus reporting for operational or academic program review and analysis.
Data is an organization’s most valuable asset, and the volume and variety of data that organizations amass is always growing. Simpler data analytics, cheaper data storage, advanced predictive tools like machine learning (ML) and data visualization are necessary to make data-driven decisions and maximize the value of data. The new Data Lifecycle and Analytics in […]