104 of 19.670 listings match.
Time = 5y,
src = 10/10,
lang = all,
dict = D1,
terms = 7(ANY). last watermark · 2026-05-07
Demand index · last 4 wk vs window mean
4688%
above baseline
Reg. pressure (D5 mentions)
4
across all listings in window
Top mover · D1
Postgres
∞ (z=99.0)
Recurring clusters
5
near-duplicate templates
01All 20 terms · Tools
14/20 have ≥1 citation · sparkline = trend · click row to filter · zero-count terms shown at bottom
02Term trend · top 5
anomalies marked · z > 2.5
DATEVPostgresPower BIExcelBigQuery
03Top movers · current half vs prev half
largest |Δ%| · z-score (Poisson)
| Term | Now | Prev | Δ % | z |
|---|---|---|---|---|
| Postgres | 23 | 0 | ∞ | 99.0 |
| Power BI | 9 | 0 | ∞ | 99.0 |
| sevdesk | 2 | 0 | ∞ | 0.0 |
| Confluence | 2 | 0 | ∞ | 0.0 |
| Excel | 5 | 0 | ∞ | 99.0 |
| Jira | 2 | 0 | ∞ | 0.0 |
| Snowflake | 2 | 0 | ∞ | 0.0 |
| BigQuery | 4 | 0 | ∞ | 99.0 |
| Tableau | 1 | 0 | ∞ | 0.0 |
| Looker | 1 | 0 | ∞ | 0.0 |
| Metabase | 1 | 0 | ∞ | 0.0 |
| HubSpot | 1 | 0 | ∞ | 0.0 |
| Lexware | 1 | 0 | ∞ | 0.0 |
| DATEV | 69 | 1 | +6800.0% | 68.0 |
04Co-occurrence · top 20 pairs
Lift = P(A,B)/(P(A)·P(B)) · click to filter on both
| Term A | Term B | Count | Lift |
|---|---|---|---|
| DATEV | exportieren | 7 | 1.04× |
| Postgres | API | 5 | 2.83× |
| Postgres | integrieren | 4 | 3.62× |
| Postgres | pipeline | 4 | 3.62× |
| pipeline | API | 4 | 10.40× |
| DATEV | API | 3 | 0.56× |
| Excel | Power BI | 3 | 6.93× |
| Power BI | analysieren | 3 | 8.67× |
| DATEV | Buchhalter | 3 | 1.49× |
| Postgres | exportieren | 3 | 1.36× |
| Postgres | DSGVO | 3 | 3.39× |
| DATEV | REST | 2 | 1.49× |
| DATEV | SOAP | 2 | 1.49× |
| API | REST | 2 | 13.00× |
| API | SOAP | 2 | 13.00× |
| REST | SOAP | 2 | 52.00× |
| DATEV | sevdesk | 2 | 1.49× |
| sevdesk | exportieren | 2 | 10.40× |
| DATEV | Pflege | 2 | 0.99× |
| Confluence | reporten | 2 | 26.00× |
05Recurring clusters · near-duplicate listings
indicates productizable workflows · click row for records