broom.helpers
After eleven quiet months, the tidier under gtsummary is back to absorbing model classes.
A side-by-side editorial comparison of haze and Power BI — release velocity, themes, recent moves, and the top alternatives to consider.
Mesh interpolation drops its custom fork dependency and sheds weight.
haze does per-vertex smoothing and interpolation on triangular meshes, aimed at mapping neuroimaging surface data between subjects, with k-d tree lookup and interpolation in C++. After three years dormant it has shipped twice in a month: a modernization pass to get through R CMD check, and now the removal of its dependency on a custom Rvcg build. It has never been on CRAN because of package size.
Power BI's monthly grind: authoring defaults, DAX documentation, and mobile finally catching up.
Power BI ships on a monthly cadence where each release is a long list of small, independently useful changes rather than a headline feature. The current batch runs from report-wide theme customization and DAX measure descriptions written as triple-slash comments, through matrix expand and collapse reaching general availability, to the mobile apps gaining Excel export and one-tap layout rotation. Nothing here redirects the product; all of it removes a specific piece of manual work.
haze does per-vertex smoothing and interpolation on triangular meshes, aimed at mapping neuroimaging surface data between subjects, with k-d tree lookup and interpolation in C++. After three years dormant it has shipped twice in a month: a modernization pass to get through R CMD check, and now the removal of its dependency on a custom Rvcg build. It has never been on CRAN because of package size.
Both recent releases point at the same obstacle. Needing a patched Rvcg meant users could not install from any normal source, and package size is the stated reason CRAN was ruled out at the first release; this release removes the first barrier and starts on the second by deleting unused data files. Nothing has been added to the interpolation surface since 2022.
The direction of travel suggests a CRAN attempt once the size problem is solved, though the package has not said so and the earlier note put it ten times over the limit.
Power BI ships on a monthly cadence where each release is a long list of small, independently useful changes rather than a headline feature. The current batch runs from report-wide theme customization and DAX measure descriptions written as triple-slash comments, through matrix expand and collapse reaching general availability, to the mobile apps gaining Excel export and one-tap layout rotation. Nothing here redirects the product; all of it removes a specific piece of manual work.
The through-line is moving decisions from repetition to defaults. Theme customization sets report-wide visual defaults and exports them for reuse or for organizational themes; matrix row-header freeze becomes a saved authoring choice rather than a per-session right-click; measure documentation lives inside the DAX rather than in a separate step. A second, quieter thread is mobile parity — exporting to Excel with filters, slicers, drill state and row-level security intact is the kind of gap that kept people on the desktop. The formatting long tail continues in parallel, mostly axis, padding, and slicer styling controls.
Expect the preview features in this window — modern visual defaults and theme customization — to move toward general availability, and the formatting pane to keep absorbing controls that were previously theme-file edits.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either haze or Power BI.
After eleven quiet months, the tidier under gtsummary is back to absorbing model classes.
OpenHouse starts adding per-column defaults while still closing silent-failure holes.
Julia's distribution library keeps filing down the edges where sampling meets array types
ggquiver is awake again, fixing arrow scaling that quietly misread irregular data.
A lazy vector container keeps closing the gaps where it quietly materialised anyway.
A mesh renderer grows a scene graph and an exit route into glTF.
See all haze alternatives → · See all Power BI alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. haze and Power BI are shipping at a similar cadence (velocity 5.0 vs 5.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. haze and Power BI are shipping at a similar cadence (velocity 5.0 vs 5.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top haze alternatives in Analytics are ranked by recent ship velocity. Browse the "haze alternatives" section above for the current picks, or visit /alternatives/haze for the full list with editorial commentary on each.
Top Power BI alternatives in Analytics are ranked by recent ship velocity. Browse the "Power BI alternatives" section above for the current picks, or visit /alternatives/power-bi for the full list with editorial commentary on each.