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Developing Workforce Safety: A Rapid Response to Covid-19

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.

Why Python cProfile is the Recommended Profiling Interface

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.

What large enterprises need in software testing solutions

There are things your in-house QA team can do extremely well. This might include collaborating with engineering leaders and product managers, strategizing test cases, and converting former test cycles into automated scripts. And then there are things that an enterprise organization’s QA team will always struggle with, regardless of how smart, organized, and empowered they are.

What is a Flat File Database?

When it comes to data storage, there is almost as much diversity in the types of databases as there is in the data that they contain. Designing and implementing a strong enterprise data strategy means that you need to be aware of the different databases and how you might best apply them within your organization. In IT, the term "flat file" means something very different from the heavy-duty steel construction file cabinets that you might buy from Safco.

The Key to Unlocking IT Modernization's Power? Enterprise level Transformation

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.

Hybrid Cloud: Unlocking App Modernization With Kubernetes

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.

It's time for the augmented consumer

One of the changes that we've seen happening in the analyst space recently is a huge shift in thinking. Gartner in particular is now talking about augmented consumers and multi-experience analytics. To me, this is really interesting because they’re talking about the business user and how they want to work and consume data. In the past it was all about the data analyst, but focusing on users opens up an entirely new level of thinking.

Unleashing the "Power of Many" With Active Intelligence

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.

Enabling NVIDIA GPUs to accelerate model development in Cloudera Machine Learning

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.