The United States Veterans Administration (VA) over the last decade underwent a massive enterprise-wide IT transformation, eliminating its fragmented shadow IT and adopting a centralized system capable of supporting the agency’s 400,000 employees and more effectively utilizing its $240 billion-plus annual budget. The result: A more reliable and modern IT environment that improves access, availability, and user experience -ultimately supporting the VA mission more effectively.

Performance optimization is a basic need for software development. When it comes to optimizing app performance, tracking frequency, maintaining production, or perpetuation method calls, profilers play a vital role. Learn why Python cProfile is a recommended profiling interface and how it enhances your software performance.

Trying to integrate your marketing data sources? Here are the fundamental differences between Fivetran and Supermetrics as marketing ETL tools.

This is the story of how Appian helped organizations worldwide get thousands of people back to work during the worst global pandemic in over a century, safely and legally. The Appian Workforce Safety Solution COVID-19 threw people worldwide into what seemed like a black hole of chaos. As infection rates rapidly grew, and related concerns grew even faster, communities struggled to respond.

From the Wright Brothers and Ada Lovelace, to Elon Musk and Steve Jobs, when we consider who is behind the most celebrated innovations and industry transformations, we often think about individual bright thinkers and disruptors. However, over the years, studies have shown that the greatest potential lies in the “power of many," fostered by a shift in how new generations work.

Last month, we were proud to launch our Hitachi Kubernetes Service, a true storage-as-a-service (SaaS) offering to improve the performance and management of multiple Kubernetes environments. By enabling users to manage their clusters simply and securely across any major cloud provider and on premises, Kubernetes can play an instrumental role in businesses’ modernization efforts. It’s for this reason that we are always working to get it on the radar of our existing clients.

When working on complex, or rigorous enterprise machine learning projects, Data Scientists and Machine Learning Engineers experience various degrees of processing lag training models at scale. While model training on small data can typically take minutes, doing the same on large volumes of data can take hours or even weeks. To overcome this, practitioners often turn to NVIDIA GPUs to accelerate machine learning and deep learning workloads.

Java developers are unlikely to ever suffer from a lack of libraries, utilities, and programs at their disposal. There's no shortage of tools that offer niche as well as fundamental features. However, some tools undoubtedly stand out due to their popularity, usefulness, data representation, and in-tool features. These 8 tools listed below are often listed as some of the best Java development tools available on the market.

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection. The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization.

Enterprise data warehouse platform owners face a number of common challenges. In this article, we look at seven challenges, explore the impacts to platform and business owners and highlight how a modern data warehouse can address them.