End-user computing must now account for the millions of workforces that have transitioned to hybrid and remote models. Virtual workspace models such as DaaS and VDI allow users to access virtual desktops to help streamline their workflow and minimize the burden on IT staff. However, companies must consider cost, scalability and management when deploying a virtual workspace, as well as security strategies to ensure workers are protected and able to remain productive. Join the Next-Generation End User Computing summit to discover how to best implement and manage hosted and virtual workspaces including DaaS and VDI.
Managing the supply chain is exceedingly difficult with global conflicts and market ups and downs interfering with companies’ ability to timely deliver and fulfil orders. Tune into the Overcoming Supply Chain Challenges summit to hear leading experts discuss emerging technologies to help protect and streamline supply chain management along with strategies and tools to secure the supply chain against the many cyber threats it faces. Register for free and gain access to live webinars, fireside chats and keynote presentations from the world’s leading supply chain innovators, vendors and evangelists.
AI apps product development canvas – Part 2 September 16, 2023 by Bill Schmarzo In part 1 of this series on the updated “AI Apps Development Canvas,” I introduced the updated AI Apps Product Development Design Canvas. The AI Apps Product Development Canva is one of the capstone deliverables for my “Thinking Like a Data Scientist” methodology, so getting feedback is critical to ensure that the methodology is relevant.
A complete guide: Conversational AI vs. generative AI September 19, 2023 by Roger Brown The two most prominent technologies that have been making waves in the AI industry are Conversational AI and Generative AI. They have revolutionized the manner in which humans interact and work with machines to generate content.
Are data science certifications the gateway to competitive pay? September 14, 2023 by Aileen Scott Working as a data scientist is the dream of many IT professionals these days. It is no secret that data science is a skyrocketing field attracting young professionals and inspiring many to switch careers to data science.
A guide to setting up analytics at a consumer tech startup September 19, 2023 by Abhi Sawhney Where do you start if you want to build a data analytics function from the ground up? As an analytics leader at a startup, you will need to make several important decisions early on to build an effective team. This article dives into four decision areas and highlights ways in which to think about them.
CUPED for starters: Enhancing controlled experiments with pre-experiment data September 14, 2023 by Igor Khomyanin In this article, I will briefly explain the randomized controlled experiments and why modern companies use them to make data-driven decisions. Then, I will introduce you to a CUPED procedure that improves the sensitivity of these experiments. After that, I will show you why it works in theory and practice. We will simulate an ordinary A/B test and compare results with the CUPED-adjusted procedure.
Searching for sustainability in data center cooling September 14, 2023 by Jane Marsh Data centers are known for their impact on the environment. They run 24/7 and exude a lot of heat. Massive warehouses full of hot technology require advanced cooling systems or an HVAC system pushed to its limit. Data center managers and sustainability leaders no longer settle for antiquated techniques.
Collaborative visual knowledge graph modeling at the system level September 14, 2023 by Alan Morrison The best way to model business and consumer dynamics is collaboratively, with stakeholders all in the same virtual room contributing. Of course, this has been happening asynchronously for some time now, but the potential exists for more real-time interaction. Modelers don’t work in a vacuum, of course.
Securing your AI data pipeline with MLOps September 12, 2023 by Colin Priest Enterprises delving into AI data pipelines often find themselves wading through a mess of complex and convoluted code, commonly referred to as “spaghetti code.” This jumbled mass is not only challenging to understand but also hard to maintain while introducing a multitude of security risks.