IS WORK OVER?

Automation index

How much of a Data architect’s job can AI already do?

A lake diagram comes earlier. Data that can be used, and does not rot, do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Data architect

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Models, lineage and the catalogue.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Pipelines, quality and the data contract.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
The analyst who finds nothing and the mess.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Privacy, retention and the field you cannot keep.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
The business, shadow IT and not building another lake.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
That it gets used, and not letting raw data rot.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%28%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • model data
  • lineage
  • data catalogue
  • data contracts
  • pipeline quality
  • retention
  • data lakes
  • privacy

Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511

Category manager

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Assortment, prices and the shelf.
Estimate

No public source provides a precise figure. This is our estimate.

18%48%+8.6
Supplier, the negotiation and the one that will not list.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Promo, the calendar and the one that clashes.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Data, margin and not killing the category.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Own-label, the clash and not hiding it.
Estimate

No public source provides a precise figure. This is our estimate.

18%14%+2.5
That the category wins.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%27%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • assortment
  • supplier negotiation
  • category margin
  • promos
  • own-label
  • the shelf
  • calendar
  • listings

Sources for this job· O*NET 11-2022.00· ESCO/ISCO 1221

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