← Back to home
Comparison · Analytics

Basedash vs OneSampleMR

A side-by-side editorial comparison of Basedash and OneSampleMR — release velocity, themes, recent moves, and the top alternatives to consider.

Basedash vs OneSampleMR: at a glance

FeatureBasedashOneSampleMR
SectorAnalyticsAnalytics
Velocity score7.50.0
Sparks · 30d10
Top themesai-analyst, prescriptive-analytics, embedded-bi, enterprise-controlsmendelian randomization, r, instrumental variables, epidemiology
Last editorial update4h ago1h ago
WebsiteVisit →Visit →

What is Basedash?

Basedash is done answering questions about your data — it now wants to tell you what to do next.

Basedash spent July and early August building the surfaces of an AI-native BI tool: suggestions that propose questions before you type, subscriptions that push dashboards to Slack and email, audit logs that record every query the AI runs, and a developer platform exposing the whole feature set through an API. Tasks, now in research preview, changes the output shape entirely — instead of charts and answers it produces a ranked list of work with a stated rationale and expected outcome, then watches whether the metrics move. A sidebar rebuild the day before quietly names the product's five pillars: Chat, Dashboards, Automations, Insights, and Data.

Read the full Basedash trajectory →

What is OneSampleMR?

OneSampleMR found that argument order in a formula was silently changing its estimates

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

Read the full OneSampleMR trajectory →

Basedash vs OneSampleMR: editorial side-by-side

B
Basedash
ANALYTICS
7.5

Basedash is done answering questions about your data — it now wants to tell you what to do next.

◆ Current state

Basedash spent July and early August building the surfaces of an AI-native BI tool: suggestions that propose questions before you type, subscriptions that push dashboards to Slack and email, audit logs that record every query the AI runs, and a developer platform exposing the whole feature set through an API. Tasks, now in research preview, changes the output shape entirely — instead of charts and answers it produces a ranked list of work with a stated rationale and expected outcome, then watches whether the metrics move. A sidebar rebuild the day before quietly names the product's five pillars: Chat, Dashboards, Automations, Insights, and Data.

◆ Where it's heading

The arc runs from self-serve querying toward prescription and closed-loop measurement. Each release chips away at the assumption that a human must decide what to look at: suggestions removed the blank prompt, subscriptions removed the visit, and Tasks removes the interpretation step. The navigation rework is the tell that this is now a multi-module product rather than a chat box with extras — and the enterprise scaffolding arriving alongside it, audit logs covering AI queries plus retention controls, is what makes an autonomous analyst deployable rather than a demo.

◆ Prediction

Tasks graduating from research preview will be the release to watch; the outcome-tracking loop it describes only has value once it has run long enough to show whether its recommendations worked. Expect Tasks to become a sixth sidebar module and to be exposed through the developer platform API, since that is where every other Basedash capability has landed.

O
OneSampleMR
ANALYTICS
0.0

OneSampleMR found that argument order in a formula was silently changing its estimates

◆ Current state

OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.

◆ Where it's heading

Two threads. The first is reach — fsw() now reads models fitted by AER::ivreg(), estimatr::iv_robust() and fixest::feols() in addition to ivreg::ivreg(), which makes conditional F statistics available without refitting in the package's own idiom. The second is hardening: clear errors when more than one exposure is given or when a variable collides with the reserved name y, and print methods that no longer fail on user-specified t0 with log or logit links. Both come largely from user reports rather than a plan.

◆ Prediction

The estimator-support work has been adding one IV-fitting package at a time on outside contributions, so further backends are the likeliest next content — the package's own estimators have been stable since first release.

Alternatives to Basedash and OneSampleMR

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 Basedash or OneSampleMR.

See all Basedash alternatives → · See all OneSampleMR alternatives →

Recent activity from Basedash and OneSampleMR

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 15h agoBasedashIntroducing Tasks: your operations, on autopilot
  2. 1d agoBasedashA sidebar that follows what you’re working on
  3. 7d agoBasedashIntroducing Basedash Subscriptions
  4. 8d agoBasedashSort and arrange tables without changing the chart
  5. 14d agoBasedashIntroducing Basedash audit logs
  6. 15d agoBasedashMotherDuck is now a supported data source
  7. 1mo agoOneSampleMROneSampleMR fixes estimates broken by covariate order in the formula
  8. 5mo agoOneSampleMROneSampleMR computes conditional F for three more IV packages
  9. 1y agoOneSampleMROneSampleMR 0.1.6
  10. 2y agoOneSampleMROneSampleMR 0.1.5
  11. 2y agoOneSampleMROneSampleMR 0.1.4
  12. 3y agoOneSampleMROneSampleMR 0.1.3

Frequently asked questions

What is the difference between Basedash and OneSampleMR?

They serve adjacent needs but don't currently overlap on shipped themes. Basedash is currently shipping more aggressively (velocity 7.5 vs 0.0), with 1 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.

Is Basedash better than OneSampleMR?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Basedash is currently shipping more aggressively (velocity 7.5 vs 0.0), with 1 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.

What are the best alternatives to Basedash?

Top Basedash alternatives in Analytics are ranked by recent ship velocity. Browse the "Basedash alternatives" section above for the current picks, or visit /alternatives/basedash for the full list with editorial commentary on each.

What are the best alternatives to OneSampleMR?

Top OneSampleMR alternatives in Analytics are ranked by recent ship velocity. Browse the "OneSampleMR alternatives" section above for the current picks, or visit /alternatives/onesamplemr for the full list with editorial commentary on each.