modeltime
modeltime built conformal intervals in, then went quiet on features.
A side-by-side editorial comparison of Power BI and tidyr — release velocity, themes, recent moves, and the top alternatives to consider.
Power BI's monthly grind: authoring defaults, DAX documentation, and cleaner axes.
The recent stream is classic Power BI monthly-release material — small, specific authoring improvements spread across embedding, modeling and visual formatting. Nothing restructures the product; each item removes a particular annoyance for report authors.
tidyr replaced separate() with a family that says what it does.
tidyr is at 1.3.2, a collection of argument additions — fill() gains .by, expand_grid() gains .vary — and better error messages around unchop() and pivot_wider_spec(). The structural work is 1.3.0, which introduced separate_wider_delim(), separate_wider_position(), separate_wider_regex(), separate_longer_delim() and separate_longer_position() as thorough replacements for separate(), extract() and separate_rows().
The recent stream is classic Power BI monthly-release material — small, specific authoring improvements spread across embedding, modeling and visual formatting. Nothing restructures the product; each item removes a particular annoyance for report authors.
The through-line is reducing per-report manual work. Theme customization moves formatting decisions to report-wide defaults, triple-slash measure descriptions let documentation live in DAX rather than a separate step, and the SharePoint embed flow drops URL copying for direct workspace selection.
Expect Modern Visual Defaults to move from preview toward general availability and to absorb more per-visual formatting into report-level control.
tidyr is at 1.3.2, a collection of argument additions — fill() gains .by, expand_grid() gains .vary — and better error messages around unchop() and pivot_wider_spec(). The structural work is 1.3.0, which introduced separate_wider_delim(), separate_wider_position(), separate_wider_regex(), separate_longer_delim() and separate_longer_position() as thorough replacements for separate(), extract() and separate_rows().
Two habits define this window. Verbs are being split into explicitly named variants rather than overloaded with arguments, which is what the separate_* family does to separate(). And .by is spreading as the standard way to express grouping inline — nest(.by=) in 1.3.0, fill(.by=) in 1.3.2 — pulling users away from wrapping calls in group_by().
Given that .by has now reached fill() and nest(), the next release most likely extends the same argument to further verbs rather than reworking another function family.
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 Power BI or tidyr.
modeltime built conformal intervals in, then went quiet on features.
performance keeps adding ways to check a model you have already fitted.
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
DoWhy adds one estimation method a year and keeps its identification edge.
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
See all Power BI alternatives → · See all tidyr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Power BI is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. Power BI is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
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.
Top tidyr alternatives in Analytics are ranked by recent ship velocity. Browse the "tidyr alternatives" section above for the current picks, or visit /alternatives/tidyr for the full list with editorial commentary on each.