The Commandments of Workplace Reskilling and Upskilling in 2020. Principles of Skills Management. The Modern Workplace and Reskilling in 2020 The coronavirus pandemic has forced companies to transform their operations with remote work becoming the norm.
Every organization needs a skilled workforce to compete in the changing technological landscape. However, many organizations are falling behind skill requirements as business evolution continues with employees lacking the right skills.In the digital environment, companies are upskilling and reskilling¹ to respond to changes and stay ahead of the curve. Technology solutions including #computervision, machine learning, and *data science *are sweeping across the business world and forcing companies to implement automation to derive value.
Executives according to a McKinseysurvey face skill gaps with most companies lacking strategies to address the problem. The choice between recruitments and internal employee training is becoming obvious for cost reasons. IBM and Amazon are leading efforts in employee reskilling in their latest initiatives for 2020 where employees undergo training programs to make them compatible with the current digital environment².The COVID-19 pandemic is accelerating reskilling and upskilling as companies adapt to the new normal of remote work and coordinating teams. Employees and employers are transforming in the wake of the pandemic and the time is right for a new approach to skill management. The current talent shortage and competition among companies to hire the best brains further complicates the situation and is forcing businesses to develop practical solutions for the widening skills gap³.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
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A data scientist/analyst in the making needs to format and clean data before being able to perform any kind of exploratory data analysis.