ใญใฃใชใขใใน
The
Executive Development Programme in Data-Driven Revenue Strategy focuses on the growing need for professionals who can leverage data to drive business growth. This section features a 3D pie chart that highlights the current job market trends in the UK for data-related roles.
Data Scientist positions represent 25% of the market, requiring skills in statistical analysis, machine learning, and data visualization. With a median base salary of ยฃ55,000, according to
Glassdoor, this role requires a strong background in mathematics, programming, and data manipulation.
Business Intelligence Analyst roles, accounting for 20% of the market, focus on using data to optimize business operations. The median base salary for these professionals is ยฃ37,500, as reported by
Glassdoor. Key skills include data mining, SQL, and data visualization.
Data Engineer positions, with 15% of the market, deal with building and maintaining data systems for collecting, storing, and processing large volumes of data. The median base salary for this role is ยฃ50,000, according to
Glassdoor. Proficiency in software engineering, distributed systems, and data warehousing is essential.
Data Analyst roles take up 20% of the market and involve analyzing and interpreting complex data sets. The median base salary for these professionals is ยฃ30,000, as reported by
Glassdoor. Skills in statistical analysis, data visualization, and data management are crucial for success in this role.
Lastly,
Machine Learning Engineer positions, with 10% of the market, specialize in designing and implementing machine learning systems. The median base salary for this role is ยฃ60,000, according to
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ใณใผในใๆญฃๅธธใซๅฎไบใใใจใไฟฎไบ่จผๆๆธใๅใๅใใพใใ
ใชใไบบใ
ใใญใฃใชใขใฎใใใซ็งใใกใ้ธใถใฎใ
ใฌใใฅใผใ่ชญใฟ่พผใฟไธญ...
ใใใใ่ณชๅ
็งใใกใฎใณใผในใฏใไปฅไธใๅซใ้ไธญๅญฆ็ฟไฝ้จใๆไพใใพใ๏ผ
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ๆฌ็ใชใณใผในๆๆ
- ใใชใใฎใใผใบใซๅใใใๆ่ปใชๅญฆ็ฟในใฑใธใฅใผใซ
- ่ชๅทฑใใผในใฎๅญฆ็ฟ็ฐๅข
- ็ป้ฒๆ้ไธญใฎใณใผในใณใณใใณใใธใฎใขใฏใปใน
- ใณใผในๅฎไบๆใฎไฟฎไบ่จผๆๆธ
ใใชใใฎในใฑใธใฅใผใซใซๅใใใฆ2ใคใฎๆ่ปใชๅญฆ็ฟใในใๆไพใใพใ๏ผ
- ใใกในใใใฉใใฏ๏ผ ้ฑ3-4ๆ้ใฎๅญฆ็ฟใง1ใถๆใงๅฎไบ
- ในใฟใณใใผใใขใผใ๏ผ ้ฑ2-3ๆ้ใง2ใถๆใงๅฎไบ
่ชๅใฎใใผในใง้ฒๆญฉใใ24ๆ้ๅนดไธญ็กไผใงๆๆใซใขใฏใปในใงใใพใใ
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- UnderstandingKeyConcepts
ๆญฃๅผใช่ณๆ ผใฎ่ฃๅฎ
ใใฎใณใผในใฏใไธป้กๅ้ใฎ็ฅ่ญใจ็่งฃใๆไพใใไปฅไธใซไพกๅคใใใใพใ๏ผ
- ๅ้ใฎ็่งฃใๆทฑใใ
- ๅฐ้่ฝๅ้็บใใผใใใฉใชใชใซ่ฟฝๅ
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ใใฎใณใผในใฏ่ฒด้ใช็ฅ่ญใๆไพใใพใใใ็นๅฎใฎใญใฃใชใขๆๆใๅฐฑ่ทใไฟ่จผใใใใฎใงใฏใชใใใจใซใๆณจๆใใ ใใใใณใผในใฎไพกๅคใฏใ็ฟๅพใใ็ฅ่ญใๅฐ้็ใชๆ่ใงใฉใฎใใใซๆดป็จใใใใซใใฃใฆๆฑบใพใใพใใ
ใชใผใใณ็ป้ฒใทในใใ ใ้ใใฆใใณใผในๆๆใธใฎๅณๅบงใฎใขใฏใปในใๆไพใใฆใใพใใใใใฏไปฅไธใๆๅณใใพใ๏ผ
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- ๅพ
ๆฉๆ้ใๅบๅฎ้ๅงๆฅใฏใใใพใใ
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- ใ้ฝๅใฎ่ฏใๆใซ้ๅงใใๆ่ปๆง
ใใฎ่ชๅทฑใใผในใขใใญใผใใซใใใๆขๅญใฎใณใใใใกใณใใซๅญฆ็ฟใ้ฉๅฟใใใชใใใใใใซใใญใใงใใทใงใใซ้็บใฎๆ
ใๅงใใใใจใใงใใพใใ
็งใใกใฎใณใผในใฏใไปฅไธใๆไพใใๅ
ๆฌ็ใช่ช็ฟใใญใฐใฉใ ใจใใฆ่จญ่จใใใฆใใพใ๏ผ
- 24ๆ้ๅนดไธญ็กไผใงใขใฏใปในๅฏ่ฝใชๆง้ ๅใใใๅญฆ็ฟๆๆ
- ่ช็ฟใฎใใใฎๅ
ๆฌ็ใชใณใผในๅ
ๅฎน
- ใฉใคใในใฟใคใซใซๅใใใๆ่ปใชๅญฆ็ฟในใฑใธใฅใผใซ
- ๅฟ
่ฆใชใในใฆใฎใชใฝใผในใจๆๆใธใฎใขใฏใปใน
ใใฎ่ชๅทฑไธปๅฐๅๅญฆ็ฟใขใใญใผใใซใใใ่ชๅใฎใใผในใง้ฒๆญฉใงใใๅญฆ็ฟในใฑใธใฅใผใซใฎๆ่ปๆงใๅฟ
่ฆใจใใๅฟใใๅฐ้ๅฎถใซ็ๆณ็ใงใใใฉใคใใฏใฉในใๅฎ่ทตใปใใทใงใณใฏใใใพใใใใใณใผในๆๆใฏ่ช็ฟใ้ใใฆไธป้กใฎๅพนๅบ็ใช็่งฃใๆไพใใใใใซ่จญ่จใใใฆใใพใใ
