Get started with Iceberg without the brain freeze
How to build an interoperable storage layer on a data lake without ever learning iceberg.
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Modern Software Development For Today's Systems & Applications
Data and AI Trends 2026: Predictions for Agentic AI Production
Agentic AI is moving quickly from experiments to real work. In 2026, it shows up inside the workflows that drive outcomes: decisions, operations, and accountability. In the season 7 premiere of the Data Chief podcast, host Cindi Howson sat down with three leaders who work at the intersection of AI ambition and enterprise execution: Paul Baier (GAI Insights), Jennifer Belissent (Snowflake), and Rory Blundell (Gravitee).
Build vs. Buy: Why Embedded Analytics is the Strategic Choice for Modern Data Leaders
For today’s CTOs and CIOs, the pressure to deliver actionable data insights within your products has never been higher. However, a critical dilemma often stalls your progress toward the business intelligence tools you need for the task: Should your engineering team build a bespoke analytics engine from scratch, or should you integrate a professional embedded solution?
IDP vs. OCR: Evolving Approaches to Document Processing
Reading emails, scanning contracts, manually processing invoices—the tedious tasks related to document processing can jam up your business operations. Document processing is a prime candidate for automation, but the technology is advancing so fast, it can be hard to know where to start or when it is time to modernize. OCR (Optical Character Recognition) and IDP (Intelligent Document Processing) are two approaches to tackling business documents.
25.4 Product Release Highlights
Appian is the leading platform for AI-powered process orchestration, automation, and intelligence. With Appian, organizations are transforming their mission-critical processes for better outcomes. Discover Appian’s latest innovations from the 25.4 release.
Bitrise Build Cache: Gradle Setup & Configuration
Lex, a solution architect at Bitrise, provides a demonstration on how to configure Bitrise Build Cache for Gradle projects when using Bitrise CI. While Build Cache works with any CI solution, the setup procedure shown is tailored for Bitrise CI users. Bitrise, Gradle Build Cache, CI/CD, Continuous Integration, Mobile Development, Android, Build Optimization, Cache Warming, Workflow Configuration, Android Development.
Bitrise Build Cache: Comparing invocations to identify bottlenecks
Lex, a solution architect at Bitrise, guides you through a demonstration on comparing build cache invocations to identify the causes of build speed, cache hit rate, or overall build behavior. The focus is on Gradle, but the comparison feature works for other build systems like Bazel and Xcode. Bitrise, Build Cache, Gradle, CI/CD, Troubleshooting, Performance, Cache Hit Rate, Invocation Comparison, Build Optimization, Diff Tracker, Bazel, Xcode.
Bitrise Build Cache: Xcode Setup & Configuration
Join Lex, a solution architect at Bitrise, for a demonstration on how to configure Xcode build cache and validate that the configuration has been done correctly. This video focuses on using the build cache with Bitrise CI, although the build cache also works with external CI. Bitrise, Xcode Build Cache, CI/CD, Continuous Integration, Mobile Development, Xcode 26, App Development, Build Optimization, Cache Warming, Workflow Configuration, iOS.
How to Connect LLM Chat and AI Agents to Enterprise Data Using Built-In MCP in DreamFactory
TL;DR: DreamFactory 7.4+ includes a built-in MCP (Model Context Protocol) server that lets you connect any LLM—ChatGPT, Claude, Perplexity, or custom AI agents—to your enterprise databases through governed, role-based APIs. Setup takes minutes: create an MCP service in the admin console, copy the OAuth credentials, and point your AI application to the generated endpoint.
The Future of AI in the Enterprise
As AI continues to rise in importance across all industries, the cost of implementation, readily available access to cloud computing, and practical business use cases make AI-powered offerings a competitive advantage for product managers, engineering, and data leaders. However, AI isn’t without its fair share of risks and challenges.