Holistics vs Chord
Side-by-side trajectory, velocity, and editorial themes.
Holistics leans into analytics-as-code with agentic dev workflows and a Power BI migration path
Holistics is a BI platform built around analytics-as-code, where models and dashboards are defined in its AMQL language and version-controlled in Git. Recent releases push on three fronts at once: competitive migration (a one-command Power BI importer), AI-native authoring (Claude Code setup skills and a conversational Ask AI), and steady breadth work like an Oracle connector and org-level GitHub App auth. The throughline is making the code-first workflow easier to adopt and operate.
The direction is to lower the switching cost from incumbent BI tools while betting that analytics teams will work through agents and code rather than point-and-click. Migration tooling and agentic setup skills both target the same friction: getting a team productive in Holistics fast. Parallel embed and dashboard-runtime polish (auto-run, KPI styling) point to a continued focus on the embedded-analytics use case.
Expect the migration story to extend to other incumbents and the agentic-development skills to deepen, given the back-to-back Power BI importer and Claude Code setup releases. Embedded-analytics controls look set to keep maturing.
Chord rebuilds Copilot from the ground up, betting its CDP on conversational AI.
Chord, a commerce data and CDP platform, has put nearly all its recent product energy into Chord AI and its Copilot assistant. The changelog is a steady stream of Copilot refinements — feedback loops, memory, documentation grounding — culminating in Copilot Next, a ground-up rebuild now reaching early customers.
The arc is clear: Chord is turning its CDP into a conversational analytics surface where users ask questions and Copilot answers from their data. The progression from Enriched Context to feedback memory to a full rebuild with persistent, shareable chat shows AI moving from a feature to the core interface.
Expect Copilot Next to widen from its limited early-access group toward general availability, with continued work on answer transparency ('show their work') and conversation sharing.
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