TOP 10 Data Science tools and technologies YOU must learn to master the ART of Data Science🎨📊📈

A 🧵↓

1. MS Excel

Job relevance:

1. Data Analyst: 40.4%
2. Business Analyst: 31.0%
3. Data Scientist: 8.0%

CC: @DataKwery
🔗 https://t.co/hVcjHFXjnp
2. Python

Job relevance:
1. Data Scientist: 75.2%
2. Data Engineer: 65.9%
3. Data Architect: 39.3%

CC: @DataKwery
🔗 https://t.co/d2wrumpXs6
3. Pandas

Job relevance:
1. Data Scientist: 6.7%
2. Data Engineer: 4.2%
3. Data Analyst: 1.9%

CC: @DataKwery
🔗 https://t.co/OzmAYpOkFh
4. Sciki-learn

Job relevance:
1. Data Scientist: 11.1%
2. Data Engineer: 4.9%
3. Data Analyst: 0.7%

CC: @DataKwery
🔗 https://t.co/7tTHkzmyGc
5. PySpark

Job relevance:

1. Data Engineer: 4.7%
2. Data Scientist: 3.0%
3. Data Architect: 1.0%

CC: @DataKwery
🔗 https://t.co/cqBLaxpJxc
6. SQL/NoSQL

Job relevance:
1. Data Analyst: 65.8%
2. Data Architect: 53.1%
3. Data Scientist: 52.9%

CC: @DataKwery
🔗 https://t.co/G4bFq9A8h9
7. Tensorflow and Keras

Job relevance:
1. Data Scientist: 15.9%
2. Data Engineer: 10.6%
3. Data Architect: 4.3%

CC: @DataKwery
🔗 https://t.co/0qQua1W5g3
8. Rapidminer

Job relevance:
1. Data Scientist: 0.3%
2. Data Architect: 0.2%
3. Data Analyst: 0.1%

CC: @DataKwery
🔗 https://t.co/5AnYUF0V0M
9. PowerBI

Job relevance:
1. Data Analyst: 13.9%
2. Data Architect: 7.6%
3. Data Engineer: 6.7%

CC: @DataKwery
🔗 https://t.co/CWQteGrubE
10. AWS

Job relevance:
1. Data Architect: 43.8%
2. Data Engineer: 36.7%
3. Data Scientist: 20.6%

CC: @DataKwery
🔗 https://t.co/NV4AkcldJV
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