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Datasets:
datamatastudios
/
skill-scarcity-index

Modalities:
Tabular
Text
Formats:
csv
Languages:
English
Size:
1K - 10K
Tags:
jobs
labor-market
skills
hiring-trends
salaries
recruiting
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
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Update 2026-08-17 (5421 rows)

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  1. README.md +107 -107
  2. dataset-cover-image.png +2 -2
  3. skill-scarcity-index.csv +488 -0
  4. skill-scarcity-index.json +0 -0
README.md CHANGED
@@ -1,107 +1,107 @@
1
- ---
2
- license: cc-by-4.0
3
- pretty_name: Datamata Skill Scarcity Index
4
- language:
5
- - en
6
- tags:
7
- - jobs
8
- - labor-market
9
- - skills
10
- - hiring-trends
11
- - salaries
12
- - recruiting
13
- size_categories:
14
- - n<10K
15
- source_datasets:
16
- - original
17
- configs:
18
- - config_name: default
19
- data_files: skill-scarcity-index.csv
20
- ---
21
-
22
- ![Datamata Skill Scarcity Index](dataset-cover-image.png)
23
-
24
- # Datamata Skill Scarcity Index
25
-
26
- Which tech skills are genuinely hard to hire for: a daily composite scarcity score per skill built from how long roles stay open (time-to-fill), the salary premium employers pay over the category median and how often the same role is re-posted after failing to fill. Computed from active job listings across public company career pages and job boards.
27
-
28
- - **Latest snapshot:** 2026-08-05
29
- - **Rows in this release:** 4933
30
- - **Updated:** daily
31
- - **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — free to use and adapt, including commercially, with attribution.
32
- - **Source & methodology:** <https://www.datamatastudios.com/datasets/skill-scarcity-index>
33
-
34
- ## Quickstart
35
-
36
- ```python
37
- import pandas as pd
38
-
39
- # Stream straight from the Hub — no download step needed
40
- df = pd.read_csv("hf://datasets/datamatastudios/skill-scarcity-index/skill-scarcity-index.csv")
41
-
42
- # Headline: hardest-to-hire data skills right now
43
- latest = df[df.snapshot_date == df.snapshot_date.max()]
44
- print(
45
- latest[latest.category == "data"]
46
- .sort_values("scarcity_score", ascending=False)
47
- [["skill_name", "scarcity_score", "median_days_open", "salary_premium_pct"]]
48
- .head(10)
49
- )
50
- ```
51
-
52
- Or load it with the 🤗 `datasets` library:
53
-
54
- ```python
55
- from datasets import load_dataset
56
-
57
- ds = load_dataset("datamatastudios/skill-scarcity-index")
58
- ```
59
-
60
- ## What you can answer with it
61
-
62
- - Which skills keep roles open longest — and whether that gap is widening.
63
- - Which skills command a salary premium over their category median.
64
- - Which skills employers repeatedly fail to hire for (repost rate).
65
- - How scarcity is shifting as AI skills flood into job requirements.
66
-
67
- ## What's NOT in this file (live on the site)
68
-
69
- The composite score is here in full. Three deeper cuts are computed from the
70
- same pipeline but only published interactively:
71
-
72
- - **Company adoption feed** — the first date each company started hiring for
73
- each skill ("47 companies added Iceberg to job requirements this quarter"):
74
- <https://www.datamatastudios.com/datasets/skill-scarcity-index>
75
- - **Stack combinations** — which skill *triples* (e.g. AWS + dbt + Snowflake)
76
- actually appear together in postings, monthly.
77
- - **Time-to-fill by role and seniority** — the same lifespan metric cut by
78
- role rather than skill.
79
-
80
- ## Columns
81
-
82
- | Column | Type | Description |
83
- |---|---|---|
84
- | `snapshot_date` | string | UTC date the snapshot was taken (YYYY-MM-DD). |
85
- | `category` | string | Job category: data, engineering, product, devops, security or ai. |
86
- | `skill_name` | string | Canonical skill name from the extraction taxonomy. |
87
- | `demand_count` | number | Active listings mentioning the skill on the snapshot date. |
88
- | `demand_pct` | number | demand_count as a percentage of all active listings in the category. |
89
- | `median_days_open` | number | Median days recently-closed listings with this skill stayed open. Blank below the sample floor. |
90
- | `salary_premium_pct` | number | Median disclosed salary of listings with this skill vs the category median, in percent. Blank below the sample floor. |
91
- | `repost_rate_pct` | number | Share of this skill's listings that are re-posts of an earlier identical role (a failed-hire signal). |
92
- | `scarcity_score` | number | 0-100 weighted percentile-rank composite of the three components within the category. Higher = harder to hire. |
93
-
94
- ## How it is built
95
-
96
- Each day we snapshot every active job listing scraped from public company
97
- career pages and job boards, extract skills with a curated taxonomy and
98
- combine three hard-to-hire signals per skill: median lifespan of closed
99
- listings (time-to-fill), median disclosed salary vs the category median and
100
- the share of listings that are re-posts of an earlier identical role. The
101
- score is a weighted percentile-rank composite within each category, so scores
102
- are comparable across categories. Full method and known limitations:
103
- <https://www.datamatastudios.com/methodology>.
104
-
105
- ## Citation
106
-
107
- > Datamata Studios. "Datamata Skill Scarcity Index." 2026-08-05. https://www.datamatastudios.com/datasets/skill-scarcity-index. Licensed under CC BY 4.0.
 
1
+ ---
2
+ license: cc-by-4.0
3
+ pretty_name: Datamata Skill Scarcity Index
4
+ language:
5
+ - en
6
+ tags:
7
+ - jobs
8
+ - labor-market
9
+ - skills
10
+ - hiring-trends
11
+ - salaries
12
+ - recruiting
13
+ size_categories:
14
+ - n<10K
15
+ source_datasets:
16
+ - original
17
+ configs:
18
+ - config_name: default
19
+ data_files: skill-scarcity-index.csv
20
+ ---
21
+
22
+ ![Datamata Skill Scarcity Index](dataset-cover-image.png)
23
+
24
+ # Datamata Skill Scarcity Index
25
+
26
+ Which tech skills are genuinely hard to hire for: a daily composite scarcity score per skill built from how long roles stay open (time-to-fill), the salary premium employers pay over the category median and how often the same role is re-posted after failing to fill. Computed from active job listings across public company career pages and job boards.
27
+
28
+ - **Latest snapshot:** 2026-08-17
29
+ - **Rows in this release:** 5421
30
+ - **Updated:** daily
31
+ - **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — free to use and adapt, including commercially, with attribution.
32
+ - **Source & methodology:** <https://www.datamatastudios.com/datasets/skill-scarcity-index>
33
+
34
+ ## Quickstart
35
+
36
+ ```python
37
+ import pandas as pd
38
+
39
+ # Stream straight from the Hub — no download step needed
40
+ df = pd.read_csv("hf://datasets/datamatastudios/skill-scarcity-index/skill-scarcity-index.csv")
41
+
42
+ # Headline: hardest-to-hire data skills right now
43
+ latest = df[df.snapshot_date == df.snapshot_date.max()]
44
+ print(
45
+ latest[latest.category == "data"]
46
+ .sort_values("scarcity_score", ascending=False)
47
+ [["skill_name", "scarcity_score", "median_days_open", "salary_premium_pct"]]
48
+ .head(10)
49
+ )
50
+ ```
51
+
52
+ Or load it with the 🤗 `datasets` library:
53
+
54
+ ```python
55
+ from datasets import load_dataset
56
+
57
+ ds = load_dataset("datamatastudios/skill-scarcity-index")
58
+ ```
59
+
60
+ ## What you can answer with it
61
+
62
+ - Which skills keep roles open longest — and whether that gap is widening.
63
+ - Which skills command a salary premium over their category median.
64
+ - Which skills employers repeatedly fail to hire for (repost rate).
65
+ - How scarcity is shifting as AI skills flood into job requirements.
66
+
67
+ ## What's NOT in this file (live on the site)
68
+
69
+ The composite score is here in full. Three deeper cuts are computed from the
70
+ same pipeline but only published interactively:
71
+
72
+ - **Company adoption feed** — the first date each company started hiring for
73
+ each skill ("47 companies added Iceberg to job requirements this quarter"):
74
+ <https://www.datamatastudios.com/datasets/skill-scarcity-index>
75
+ - **Stack combinations** — which skill *triples* (e.g. AWS + dbt + Snowflake)
76
+ actually appear together in postings, monthly.
77
+ - **Time-to-fill by role and seniority** — the same lifespan metric cut by
78
+ role rather than skill.
79
+
80
+ ## Columns
81
+
82
+ | Column | Type | Description |
83
+ |---|---|---|
84
+ | `snapshot_date` | string | UTC date the snapshot was taken (YYYY-MM-DD). |
85
+ | `category` | string | Job category: data, engineering, product, devops, security or ai. |
86
+ | `skill_name` | string | Canonical skill name from the extraction taxonomy. |
87
+ | `demand_count` | number | Active listings mentioning the skill on the snapshot date. |
88
+ | `demand_pct` | number | demand_count as a percentage of all active listings in the category. |
89
+ | `median_days_open` | number | Median days recently-closed listings with this skill stayed open. Blank below the sample floor. |
90
+ | `salary_premium_pct` | number | Median disclosed salary of listings with this skill vs the category median, in percent. Blank below the sample floor. |
91
+ | `repost_rate_pct` | number | Share of this skill's listings that are re-posts of an earlier identical role (a failed-hire signal). |
92
+ | `scarcity_score` | number | 0-100 weighted percentile-rank composite of the three components within the category. Higher = harder to hire. |
93
+
94
+ ## How it is built
95
+
96
+ Each day we snapshot every active job listing scraped from public company
97
+ career pages and job boards, extract skills with a curated taxonomy and
98
+ combine three hard-to-hire signals per skill: median lifespan of closed
99
+ listings (time-to-fill), median disclosed salary vs the category median and
100
+ the share of listings that are re-posts of an earlier identical role. The
101
+ score is a weighted percentile-rank composite within each category, so scores
102
+ are comparable across categories. Full method and known limitations:
103
+ <https://www.datamatastudios.com/methodology>.
104
+
105
+ ## Citation
106
+
107
+ > Datamata Studios. "Datamata Skill Scarcity Index." 2026-08-17. https://www.datamatastudios.com/datasets/skill-scarcity-index. Licensed under CC BY 4.0.
dataset-cover-image.png CHANGED

Git LFS Details

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  • Pointer size: 130 Bytes
  • Size of remote file: 16 kB

Git LFS Details

  • SHA256: 8314a1ea2e204101b5103b8b56b43e2e6c2aa475f418b2e538086770a52d53b4
  • Pointer size: 130 Bytes
  • Size of remote file: 16.1 kB
skill-scarcity-index.csv CHANGED
@@ -4932,3 +4932,491 @@ snapshot_date,category,skill_name,demand_count,demand_pct,median_days_open,salar
4932
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  2026-08-05,security,Zero Trust,67,2.8,0.0,2.7,12.5,38.7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  2026-08-05,security,Terraform,121,5.1,0.0,-29.6,7.6,28.8
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5024
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5025
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5026
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5027
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5028
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5030
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5034
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5035
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5036
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5037
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5040
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5041
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5042
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5043
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5044
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5045
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5046
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5047
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5049
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5050
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5051
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+ 2026-08-17,data,Git,434,4.5,1.0,9.7,5.5,58.1
5053
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5054
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5055
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5056
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5057
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5058
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5059
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5060
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5061
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5062
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5063
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5064
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5065
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5066
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5067
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5068
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5069
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5070
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5071
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5072
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5073
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5074
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5075
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5076
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5077
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5078
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5079
+ 2026-08-17,data,NLP,174,1.8,0.0,28.2,16.7,48.5
5080
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5081
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5082
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5083
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5085
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5086
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5088
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5089
+ 2026-08-17,data,Python,1596,16.5,0.0,-12.0,10.6,34.2
5090
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5091
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5092
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5094
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5095
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5096
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5097
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5098
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5099
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5100
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5101
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5102
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5104
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5105
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5108
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5109
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5110
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5111
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5112
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5119
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5121
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5122
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5123
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5124
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5128
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5129
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5130
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5139
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5141
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5143
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5144
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5147
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5148
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5149
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5150
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5151
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5154
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5155
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5156
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5157
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5159
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5160
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5161
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5163
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5165
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5166
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5167
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5168
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5169
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5170
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5171
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5172
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5173
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5174
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5175
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5176
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5177
+ 2026-08-17,devops,Python,528,9.4,0.0,-11.6,8.5,30.4
5178
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5179
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5180
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5181
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5182
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5183
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5184
+ 2026-08-17,devops,Rust,42,0.8,1.0,-37.9,10.4,46.8
5185
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5186
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5187
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5188
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5189
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5190
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5191
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5192
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5193
+ 2026-08-17,devops,Spring,45,0.8,,13.8,0.0,41.1
5194
+ 2026-08-17,devops,SQL,219,3.9,0.0,-32.5,7.7,17.2
5195
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5196
+ 2026-08-17,devops,Swift,12,0.2,,,8.3,57.3
5197
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5198
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5199
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5200
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5201
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5202
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5203
+ 2026-08-17,engineering,A/B Testing,360,2.3,8.0,30.3,3.0,67.2
5204
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5205
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5206
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5207
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5208
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5209
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5210
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5211
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5212
+ 2026-08-17,engineering,ArgoCD,17,0.1,8.0,-42.0,0.0,32.7
5213
+ 2026-08-17,engineering,AWS,2336,14.8,0.0,-19.9,8.5,32.6
5214
+ 2026-08-17,engineering,AWS Security,84,0.5,0.0,-9.8,6.9,35.2
5215
+ 2026-08-17,engineering,Azure,940,5.9,1.0,-29.0,11.4,46.2
5216
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5217
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5218
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5219
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5220
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5221
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5222
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5223
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5224
+ 2026-08-17,engineering,Data Modeling,191,1.2,4.0,39.1,0.5,62.6
5225
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5226
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5227
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5228
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5229
+ 2026-08-17,engineering,Datadog,189,1.2,22.0,-36.1,2.8,51.8
5230
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5231
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5232
+ 2026-08-17,engineering,Django,133,0.8,1.0,-43.9,1.9,23.5
5233
+ 2026-08-17,engineering,Docker,846,5.4,1.0,-50.3,13.7,38.6
5234
+ 2026-08-17,engineering,DynamoDB,214,1.4,15.0,-7.7,4.1,66.9
5235
+ 2026-08-17,engineering,Elasticsearch,224,1.4,0.0,-23.6,12.4,35.4
5236
+ 2026-08-17,engineering,ETL,171,1.1,8.0,-10.9,7.4,63.2
5237
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5238
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5239
+ 2026-08-17,engineering,Figma,134,0.8,1.0,-66.3,2.8,22.1
5240
+ 2026-08-17,engineering,Fine-tuning,59,0.4,1.0,51.5,9.5,65.0
5241
+ 2026-08-17,engineering,Fivetran,80,0.5,44.0,25.2,9.3,84.6
5242
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5243
+ 2026-08-17,engineering,Flink,51,0.3,,53.3,9.1,85.5
5244
+ 2026-08-17,engineering,GCP,938,5.9,7.0,-14.7,13.1,69.1
5245
+ 2026-08-17,engineering,Git,1087,6.9,2.0,-21.3,10.8,59.8
5246
+ 2026-08-17,engineering,Go,341,2.2,1.0,-8.9,2.9,43.8
5247
+ 2026-08-17,engineering,Grafana,744,4.7,0.0,16.3,0.8,32.7
5248
+ 2026-08-17,engineering,GraphQL,352,2.2,1.0,-15.1,1.9,39.3
5249
+ 2026-08-17,engineering,Helm,34,0.2,0.0,50.3,0.0,32.6
5250
+ 2026-08-17,engineering,Incident Response,200,1.3,57.0,-14.3,0.9,64.2
5251
+ 2026-08-17,engineering,Java,2500,15.8,0.0,-11.1,11.8,41.0
5252
+ 2026-08-17,engineering,JavaScript,1834,11.6,0.0,-36.1,7.9,23.4
5253
+ 2026-08-17,engineering,Jira,102,0.6,9.0,-36.1,4.2,51.3
5254
+ 2026-08-17,engineering,Kafka,338,2.1,1.0,10.8,4.9,52.4
5255
+ 2026-08-17,engineering,Kotlin,542,3.4,11.0,-4.9,5.3,69.1
5256
+ 2026-08-17,engineering,Kubernetes,1082,6.8,8.0,-20.5,10.5,64.3
5257
+ 2026-08-17,engineering,LangChain,38,0.2,0.0,-41.5,2.0,13.2
5258
+ 2026-08-17,engineering,Linear,25,0.2,1.0,19.0,0.0,42.3
5259
+ 2026-08-17,engineering,Linux,299,1.9,0.0,-23.2,8.9,31.6
5260
+ 2026-08-17,engineering,LLM APIs,61,0.4,,44.3,13.1,89.0
5261
+ 2026-08-17,engineering,LLMs / GenAI,1488,9.4,0.0,5.5,5.9,38.3
5262
+ 2026-08-17,engineering,Looker,34,0.2,,,0.0,0.0
5263
+ 2026-08-17,engineering,Machine Learning,808,5.1,0.0,13.3,4.0,37.4
5264
+ 2026-08-17,engineering,MCP,61,0.4,,,4.9,48.7
5265
+ 2026-08-17,engineering,Microservices,112,0.7,1.0,10.6,3.7,49.5
5266
+ 2026-08-17,engineering,MLflow,60,0.4,,,0.0,0.0
5267
+ 2026-08-17,engineering,MongoDB,250,1.6,2.0,-39.0,9.3,49.5
5268
+ 2026-08-17,engineering,MySQL,330,2.1,0.0,-41.1,24.9,31.4
5269
+ 2026-08-17,engineering,Next.js,423,2.7,0.0,-33.2,11.3,30.5
5270
+ 2026-08-17,engineering,NLP,43,0.3,0.0,24.1,10.3,48.0
5271
+ 2026-08-17,engineering,Node.js,985,6.2,0.0,-28.0,10.4,32.4
5272
+ 2026-08-17,engineering,Oracle,38,0.2,,-10.9,2.6,46.4
5273
+ 2026-08-17,engineering,OWASP,23,0.1,,-52.4,4.3,19.7
5274
+ 2026-08-17,engineering,Pandas,11,0.1,,-48.1,75.0,46.2
5275
+ 2026-08-17,engineering,PHP,151,1.0,0.0,-50.3,19.7,25.6
5276
+ 2026-08-17,engineering,PostgreSQL,761,4.8,2.0,-32.1,11.7,56.9
5277
+ 2026-08-17,engineering,Power BI,21,0.1,1.0,-32.9,2.9,33.5
5278
+ 2026-08-17,engineering,Prometheus,105,0.7,30.0,,3.2,70.2
5279
+ 2026-08-17,engineering,Prompt Engineering,76,0.5,,47.8,2.6,65.9
5280
+ 2026-08-17,engineering,Prototyping,358,2.3,1.0,-20.8,3.9,39.6
5281
+ 2026-08-17,engineering,Pulumi,28,0.2,,,0.0,0.0
5282
+ 2026-08-17,engineering,Python,2693,17.0,1.0,-16.9,11.5,52.0
5283
+ 2026-08-17,engineering,PyTorch,75,0.5,8.0,-28.4,1.2,47.0
5284
+ 2026-08-17,engineering,RAG,222,1.4,6.0,20.2,17.8,79.7
5285
+ 2026-08-17,engineering,React,2077,13.1,0.0,-29.0,7.7,27.1
5286
+ 2026-08-17,engineering,Redis,167,1.1,1.0,-41.8,8.4,34.2
5287
+ 2026-08-17,engineering,Redshift,34,0.2,,-36.1,5.9,35.8
5288
+ 2026-08-17,engineering,REST API,424,2.7,0.0,-18.6,10.6,36.6
5289
+ 2026-08-17,engineering,Ruby,419,2.7,23.0,0.5,4.3,72.0
5290
+ 2026-08-17,engineering,Rust,394,2.5,0.0,-37.5,9.0,24.7
5291
+ 2026-08-17,engineering,SageMaker,10,0.1,,,0.0,0.0
5292
+ 2026-08-17,engineering,Salesforce,137,0.9,,50.8,3.6,70.6
5293
+ 2026-08-17,engineering,SAP,18,0.1,,,0.0,0.0
5294
+ 2026-08-17,engineering,Scala,203,1.3,0.0,-43.3,1.6,9.4
5295
+ 2026-08-17,engineering,scikit-learn,23,0.1,,-41.8,0.0,8.0
5296
+ 2026-08-17,engineering,Segment,57,0.4,,-36.1,3.3,29.0
5297
+ 2026-08-17,engineering,ServiceNow,20,0.1,,6.3,0.0,42.3
5298
+ 2026-08-17,engineering,SIEM,25,0.2,0.0,-42.0,13.2,26.4
5299
+ 2026-08-17,engineering,Snowflake,124,0.8,47.0,53.0,8.6,88.9
5300
+ 2026-08-17,engineering,SOC 2,19,0.1,32.0,,0.0,57.2
5301
+ 2026-08-17,engineering,Spark,282,1.8,6.0,15.3,1.3,60.2
5302
+ 2026-08-17,engineering,Spring,559,3.5,0.0,-16.3,22.3,42.3
5303
+ 2026-08-17,engineering,SQL,1609,10.2,0.0,-23.8,13.4,36.7
5304
+ 2026-08-17,engineering,Stakeholder Mgmt,1753,11.1,1.0,-0.1,9.7,56.3
5305
+ 2026-08-17,engineering,Statistical Analysis,40,0.3,0.0,-51.7,4.3,12.1
5306
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5307
+ 2026-08-17,engineering,Svelte,28,0.2,13.0,-11.3,0.0,53.2
5308
+ 2026-08-17,engineering,Swift,148,0.9,19.0,-8.8,4.4,68.9
5309
+ 2026-08-17,engineering,System Design,348,2.2,15.0,-20.7,5.4,62.8
5310
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5311
+ 2026-08-17,engineering,TensorFlow,65,0.4,8.0,-41.8,1.4,39.1
5312
+ 2026-08-17,engineering,Terraform,497,3.1,2.0,-26.2,9.8,56.9
5313
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5314
+ 2026-08-17,engineering,TypeScript,1664,10.5,1.0,-33.3,7.5,38.6
5315
+ 2026-08-17,engineering,User Research,31,0.2,,,0.0,0.0
5316
+ 2026-08-17,engineering,Vector Databases,45,0.3,,,13.3,89.7
5317
+ 2026-08-17,engineering,Vue,267,1.7,46.0,-33.1,1.7,55.3
5318
+ 2026-08-17,engineering,Workday,31,0.2,,,12.9,84.6
5319
+ 2026-08-17,engineering,Workflow Automation,32,0.2,,-4.3,6.2,62.8
5320
+ 2026-08-17,engineering,Zero Trust,20,0.1,,,0.0,0.0
5321
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5322
+ 2026-08-17,product,Agile / Scrum,147,5.5,0.0,-41.7,2.9,21.7
5323
+ 2026-08-17,product,AI Agents,275,10.3,,55.8,2.9,78.1
5324
+ 2026-08-17,product,AI Coding Tools,54,2.0,,,0.0,0.0
5325
+ 2026-08-17,product,Amplitude,32,1.2,,58.2,0.0,44.3
5326
+ 2026-08-17,product,Angular,36,1.3,1.0,-21.0,80.5,34.0
5327
+ 2026-08-17,product,AWS,130,4.9,0.0,52.3,0.0,23.8
5328
+ 2026-08-17,product,AWS Security,11,0.4,,,0.0,0.0
5329
+ 2026-08-17,product,Azure,80,3.0,,-15.5,0.0,7.0
5330
+ 2026-08-17,product,BigQuery,11,0.4,,,0.0,0.0
5331
+ 2026-08-17,product,C#,34,1.3,,-21.0,97.1,44.0
5332
+ 2026-08-17,product,CI/CD,29,1.1,1.0,,0.0,12.3
5333
+ 2026-08-17,product,Data Modeling,14,0.5,,,0.0,0.0
5334
+ 2026-08-17,product,Data Pipeline,12,0.4,,,0.0,0.0
5335
+ 2026-08-17,product,Data Visualization,18,0.7,49.0,,15.4,81.5
5336
+ 2026-08-17,product,Databricks,80,3.0,75.0,,0.0,54.2
5337
+ 2026-08-17,product,Datadog,76,2.8,,,0.0,0.0
5338
+ 2026-08-17,product,dbt,52,1.9,,-7.3,1.9,42.9
5339
+ 2026-08-17,product,Dynamics 365,10,0.4,,,0.0,0.0
5340
+ 2026-08-17,product,Elasticsearch,44,1.6,27.0,,0.0,29.5
5341
+ 2026-08-17,product,ETL,26,1.0,,,0.0,0.0
5342
+ 2026-08-17,product,Excel,99,3.7,8.0,,0.0,22.2
5343
+ 2026-08-17,product,Figma,243,9.1,1.0,-4.9,2.3,39.6
5344
+ 2026-08-17,product,Fine-tuning,36,1.3,37.0,,2.4,66.5
5345
+ 2026-08-17,product,Fivetran,55,2.1,,-7.3,0.0,11.7
5346
+ 2026-08-17,product,GCP,74,2.8,1.0,,0.0,12.3
5347
+ 2026-08-17,product,Git,17,0.6,,,0.0,0.0
5348
+ 2026-08-17,product,Grafana,14,0.5,,,0.0,0.0
5349
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5350
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5351
+ 2026-08-17,product,Kafka,19,0.7,0.0,107.6,0.0,33.6
5352
+ 2026-08-17,product,Kubernetes,35,1.3,,,0.0,0.0
5353
+ 2026-08-17,product,LLMs / GenAI,368,13.8,30.0,-5.9,2.6,51.9
5354
+ 2026-08-17,product,Looker,12,0.4,,115.7,7.7,97.2
5355
+ 2026-08-17,product,Machine Learning,88,3.3,22.0,26.5,0.9,50.9
5356
+ 2026-08-17,product,MCP,26,1.0,,,0.0,0.0
5357
+ 2026-08-17,product,Mixpanel,21,0.8,,58.2,0.0,44.3
5358
+ 2026-08-17,product,MLflow,19,0.7,89.0,,0.0,61.5
5359
+ 2026-08-17,product,MongoDB,39,1.5,,,0.0,0.0
5360
+ 2026-08-17,product,MySQL,14,0.5,,,0.0,0.0
5361
+ 2026-08-17,product,NLP,11,0.4,,,0.0,0.0
5362
+ 2026-08-17,product,Node.js,29,1.1,43.0,46.6,0.0,49.6
5363
+ 2026-08-17,product,PostgreSQL,14,0.5,,,0.0,0.0
5364
+ 2026-08-17,product,Prompt Engineering,14,0.5,,,7.1,91.7
5365
+ 2026-08-17,product,Prototyping,218,8.2,37.0,25.7,2.0,56.0
5366
+ 2026-08-17,product,Python,41,1.5,75.0,,0.0,54.2
5367
+ 2026-08-17,product,RAG,70,2.6,,,1.4,73.3
5368
+ 2026-08-17,product,Ruby,17,0.6,,,0.0,0.0
5369
+ 2026-08-17,product,Salesforce,27,1.0,,45.8,0.0,32.7
5370
+ 2026-08-17,product,SAP,20,0.7,,,0.0,0.0
5371
+ 2026-08-17,product,Segment,42,1.6,0.0,58.2,0.0,26.6
5372
+ 2026-08-17,product,SIEM,18,0.7,,-8.0,0.0,9.3
5373
+ 2026-08-17,product,Snowflake,23,0.9,,,3.8,90.0
5374
+ 2026-08-17,product,Spark,32,1.2,53.0,,0.0,46.8
5375
+ 2026-08-17,product,SQL,177,6.6,41.0,79.8,0.0,57.8
5376
+ 2026-08-17,product,Stakeholder Mgmt,901,33.8,15.0,31.0,2.2,52.8
5377
+ 2026-08-17,product,Statistical Analysis,18,0.7,,,0.0,0.0
5378
+ 2026-08-17,product,System Design,22,0.8,66.0,45.8,0.0,53.2
5379
+ 2026-08-17,product,Tableau,16,0.6,,,10.0,95.0
5380
+ 2026-08-17,product,User Research,184,6.9,82.0,15.9,1.9,69.8
5381
+ 2026-08-17,product,Vector Databases,10,0.4,,,0.0,0.0
5382
+ 2026-08-17,security,Agile / Scrum,43,1.7,1.0,15.7,15.1,55.2
5383
+ 2026-08-17,security,AI Agents,143,5.7,,153.9,7.7,83.3
5384
+ 2026-08-17,security,AI Coding Tools,14,0.6,,,0.0,0.0
5385
+ 2026-08-17,security,AWS,349,13.8,0.0,-1.1,12.0,25.0
5386
+ 2026-08-17,security,AWS Security,123,4.9,0.0,21.2,7.5,27.9
5387
+ 2026-08-17,security,Azure,245,9.7,0.0,18.3,8.1,28.0
5388
+ 2026-08-17,security,C++,17,0.7,79.0,,0.0,56.4
5389
+ 2026-08-17,security,CI/CD,145,5.7,0.0,22.1,13.1,34.7
5390
+ 2026-08-17,security,CISSP,44,1.7,,-7.0,4.3,26.3
5391
+ 2026-08-17,security,Databricks,21,0.8,,,0.0,0.0
5392
+ 2026-08-17,security,Datadog,25,1.0,72.0,,0.0,53.8
5393
+ 2026-08-17,security,Docker,63,2.5,0.0,22.4,1.1,23.9
5394
+ 2026-08-17,security,Elasticsearch,14,0.6,,,5.6,50.0
5395
+ 2026-08-17,security,Excel,31,1.2,0.0,,0.0,0.0
5396
+ 2026-08-17,security,GCP,175,6.9,0.0,26.5,4.2,26.9
5397
+ 2026-08-17,security,Git,68,2.7,,36.2,4.2,52.4
5398
+ 2026-08-17,security,Incident Response,220,8.7,0.0,4.4,10.3,26.0
5399
+ 2026-08-17,security,Java,32,1.3,,74.8,0.0,47.0
5400
+ 2026-08-17,security,JavaScript,42,1.7,,144.7,22.2,93.1
5401
+ 2026-08-17,security,Kubernetes,76,3.0,26.0,103.3,3.3,68.2
5402
+ 2026-08-17,security,Linux,49,1.9,1.0,-38.8,4.8,37.5
5403
+ 2026-08-17,security,LLMs / GenAI,100,4.0,51.0,39.8,17.9,73.8
5404
+ 2026-08-17,security,Machine Learning,57,2.3,,61.9,27.1,82.9
5405
+ 2026-08-17,security,MLflow,14,0.6,,,0.0,0.0
5406
+ 2026-08-17,security,MongoDB,12,0.5,,,0.0,0.0
5407
+ 2026-08-17,security,Next.js,14,0.6,,144.7,60.0,95.2
5408
+ 2026-08-17,security,OWASP,48,1.9,79.0,29.4,18.2,77.7
5409
+ 2026-08-17,security,Penetration Testing,82,3.3,0.0,29.4,11.5,37.9
5410
+ 2026-08-17,security,Python,159,6.3,51.0,62.8,1.5,65.8
5411
+ 2026-08-17,security,React,15,0.6,,-63.8,60.0,40.6
5412
+ 2026-08-17,security,Rust,19,0.8,,96.0,0.0,48.9
5413
+ 2026-08-17,security,SIEM,261,10.3,0.0,-27.1,10.0,20.9
5414
+ 2026-08-17,security,Snowflake,15,0.6,,-45.7,0.0,1.9
5415
+ 2026-08-17,security,SOC 2,33,1.3,12.0,40.2,9.3,67.2
5416
+ 2026-08-17,security,Spark,34,1.3,0.0,,0.0,0.0
5417
+ 2026-08-17,security,SQL,33,1.3,79.0,15.3,7.3,60.6
5418
+ 2026-08-17,security,Stakeholder Mgmt,150,5.9,0.0,27.1,5.9,31.2
5419
+ 2026-08-17,security,System Design,18,0.7,,103.3,0.0,50.8
5420
+ 2026-08-17,security,Terraform,100,4.0,0.0,-1.1,19.1,28.1
5421
+ 2026-08-17,security,TypeScript,23,0.9,55.0,48.7,0.0,58.2
5422
+ 2026-08-17,security,Zero Trust,48,1.9,0.0,6.3,8.3,25.3
skill-scarcity-index.json CHANGED
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