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53 Questions Developers Should Ask Innovators

TechEmpower - Information Technology

Even when they have talked to multiple developers or development firms, we’re often the first to ask basic questions like “Who are your customers?” ” or “Are you developing for desktop, tablet, mobile, or all three?” The innovator/developer relationship needs to be a conversation.

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Development Team Success: What Could Possibly Go Wrong?

Forrester IT

In most successful organizations, software developers align their goals with the goals of the business. Instead, where you sit in the organization determines how you believe development teams should succeed. In an analysis of Forrester’s developer survey data, we found that: C-levels and middle managers know […]

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Announcing The Forrester Wave™: Edge Development Platforms, Q4 2023

Forrester IT

As customers seek faster, more dynamic digital experiences, businesses must build applications capable of serving those customers with lower latency, and with personalized and geographically relevant content.

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Low-Code Opens Up New Opportunities For Marketers To Elevate And Control Martech

Forrester IT

Low-code application development is revolutionizing how enterprises develop technology. Any tech ecosystem in which multiple applications, data sources, and processes intersect is ripe for low-code innovation. Marketing adoption of low-code appdev is still nascent, but the […]

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success?

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Vectorized CEO on the future of streaming data application development

Venture Beast

VentureBeat sat down with Vectorized CEO Alexander Gallego this week to discuss the future of streaming data application development. Read More.

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How to modernize and accelerate mainframe application development

CIO Business Intelligence

With that in mind, what can businesses do to modernize their applications effectively? By introducing open-source software to mainframe infrastructure, companies will improve product development, speed time to market, and open the mainframe to new developers that will drive mainframe innovation.

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The Big Payoff of Application Analytics

Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Five years ago they may have. But today, dashboards and visualizations have become table stakes. Brought to you by Logi Analytics.

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GEP Procurement & Supply Chain Tech Trends Report

2024 GEP Procurement & Supply Chain Tech Trends Report — explores the biggest technological trends in procurement and supply chain, from generative AI and the advancement of low-code development tools to the data management and analytics applications that unlock agility, cost efficiency, and informed decision-making.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.