A Roadmap for End-to-End Monitoring of Enterprise Applications in Hybrid Multi-Cloud

whitePaper | April 16, 2020

Since its inception in 1983, Green Mechanical has grown from 1 to 3 offices, taking on larger, more complex projects. However, success came with its own unique challenges. With employees spread across multiple cities and states, Green Mechanical built custom workflows for various systems to ensure collaborators had access to the information they needed. That meant employees had to keep track of multiple remote logins to complete simple tasks like printing job cost reports. Additionally, some employees used digital processes, while others used pen-and-paper. As a result, teams were often working off outdated information.

whitePaper | October 13, 2022

Walk into any Fortune 500 organization, and you’re more than likely to find a room full of data scientists. These individuals are being described by many as the difference makers, the propagators of change, the fuel to the fire of innovation, and the essential ingredient to survival in today’s digital economy. Data scientist job openings are among the hardest positions to fill in the market, yet they are among the highest paying jobs at many companies.

whitePaper | January 20, 2022

Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there is an increasing interest in developing neural network (NN) solutions to deploy them on low-power edge devices such as the Arm Cortex-M microcontroller systems. To enable that, we present CMSIS-NN, an open-source library of optimized software kernels that maximize the NN performance on Cortex-M cores with minimal memory footprint overhead. We further present methods for NN architecture exploration, using image classification on CIFAR-10 dataset as an example, to develop models that fit on such constrained devices.

whitePaper | August 6, 2020

The purpose of any data acquisition system is to gather useful measurement data for characterization, monitoring, or control. The specific parameters of your application will dictate the resolution, accuracy, channel count, and speed requirements of a data acquisition system. A wide assortment of data acquisition components and solutions is available on the market, including low-cost USB modules, benchtop data loggers, and large channel systems. Before you start your search for a data acquisition solution, carefully analyze your application requirements to understand how much capability and performance you need to purchase.

whitePaper | June 28, 2022

Artificial intelligence (AI) has been accelerating across sectors. It has great potential to benefit society but the technology’s full potential can only be realized if it includes the diversity of the populations it represents throughout every step of its development. With growing concerns about bias, data privacy and lack of representation, it is critical to re-evaluate the way in which AI is both designed and deployed to ensure that all affected stakeholders and communities reap the benefits of the technology, rather than any harm.

whitePaper | May 4, 2022

The pandemic has brought about significant economic disruption, thereby increasing the need for banks and financial institutions to be more agile. However, Covid-19 is not the only factor that drives automation and digitalization in the credit and lending process in credit institutions. Incumbent banks are increasingly facing pressure from neobanks, these having the strategic advantage of being “born digital”. In addition, customers demand fully digitalized processes with regard to the ease of use and fast turnaround times.