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Namangan Institute of Engineering and Technology nammti uz
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| bet | 586/693 | | Sana | 13.05.2024 | | Hajmi | 15,56 Mb. | | #228860 |
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Introduction. In an era where data is described as the new oil, the ability to effectively work
with big data has become a crucial asset for organizations. The surging demand for data analytics
has led to a significant skills gap in the workforce. Addressing this gap requires targeted training
strategies that equip professionals with the necessary skills to harness the power of big data. This
article delves into the strategies for training individuals to meet the challenges of big data
analytics.
Literature Review
1.
Essential Skills for Big Data Analysis: Johnson and Smith (2022) outline the core
competencies required for big data analysis, including statistical analysis, data mining, and
machine learning.
2.
Training Methodologies for Big Data Analytics: Lee and Kim’s (2023) comprehensive
study analyzes various training methodologies, from traditional classroom settings to online
courses and workshops, focusing on their effectiveness in imparting big data skills.
3.
Challenges in Big Data Education: Patel's (2021) research discusses the challenges in
big data education, including keeping up with rapidly evolving technologies and the need for real-
world data handling experience.
4.
Future Trends in Big Data Skill Development: Zhang's (2024) forecast examines
emerging trends in big data education, emphasizing the growing importance of data ethics and
privacy in training programs.
Sections of the Article
1.
Key Skills for Big Data Professionals: This section details the essential skills required in
big data analytics, including data processing, visualization, and interpretation skills.
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