The subject area is: Data Analytics
Background to the task:
IBM is a large sof
The subject area is: Data Analytics
Background to the task:
IBM is a large software and hardware vendor, with a focus on AI and Quantum. Part of IBM’s strategy is to support the skilling up to 30 million people by 2030, in order to cater to the changing needs of the information technology industry. One of our main vehicles for this is IBM Skills Build, a platform where students and adult learners can have free access to online courses/badges.
IBM Skills Build is IBM’s main online platform for delivering learning to both students and adult learners who are looking to transition to another role. IBM Skills Build is the avenue to achieve IBM’s goal of skilling up 30 million people by 2030. In order to achieve this goal, IBM would need to ensure that the learning material contained in IBM Skills Build meets the needs of the information technology industry, and will help learners cross the skills gap, thereby filling the skills needs of the industry, both today and in the future (next 3 years).
In order to ensure that Skills Build continues to be the relevant to the user base, you are required to review the Skills Build content, and perform an analysis of the data provided by the UK Government Employment and Skills survey, and provide recommendations on the evolution of the IBM Skills Build, especially to determine which content should be sunset, which content is relevant, and what content IBM should consider including.
Some links to help you get started:
https://www.ibm.com/uk-en
https://skillsbuild.org/about
https://digital-skills-jobs.europa.eu/en/inspiration/resources/ibm-skillsbuild-empowering-digital-skills-all
IBM Skills Build overview:
https://bit.ly/PathWaytoLearning
UK Government Data Skills Survey (2022):
https://explore-education-statistics.service.gov.uk/find-statistics/employer-skills-survey/2022
Further research (as required) is to be carried out by the student.
Requirements:
1. Familiarize with the IBM Skills Build program, how the program has evolved and what skills needs are currently addressed.
Carry out research on skills programs and their contribution to the information technology industry, business community and society at large.
2. Familiarize with IBM as an organization, and their business strategy to support the skills requirements of the fast-changing information technology industry.
3. Familiarize with the UK Government Data Skills Survey of 2022, understand the recent study skills gaps in the UK and how the skills needs have evolved.
Carry out research on any other digital skills requirements that may address future needs.
4. Analyze the data contained in the UK Government Skills Employment Survey of 2022.
Select a dataset that will support your analysis, cleanse the data as required.
5. Analyze the skills needs currently addressed by the IBM Skills Build program.
Prepare a quality dataset that will support your analysis, by using the sources given.
6. Import the data into a data analytics platform of your choice. It is recommended to use SAS Enterprise Miner, which was introduced as part of the university short course.
7. Transform the raw data by carrying out your own analysis using the software tools and produce compelling, meaningful, and relevant visualizations. Discuss your analysis in the report.
8. Frame the data set based on the requirement, apply linear regression model and interpret the results using the features of the software tool, to predict the trend of future increased skills needs. Discuss your findings in report.
The analysis must include (but not limited to):
– Projected skills shortfalls
– Sector-wise analysis
9. Reflect on the project
– what was your learning?
– challenges faced?
– what would you do differently?
10. Explain the work carried out (as separate appendices):
a. What data was collected for the analysis and what sources were used.
b. How the data was cleansed.
c. What model was selected for the predictive analysis and why.
11. Evidence of the work carried out (in report and/or as separate appendices):
a. Cleansed data sets
b. Data visualizations
c. Predictions
Requirement #5 dataset is doing an excel sheet.
6 & 7 needs someone who knows SAS miner
All of the above requirements doesn’t require much words
Except for the part 1,2,3,4, 9 and 10
Please show proof of answers (screen shot from the SAS and other softwares)
No need for an introduction or conclusion
Just answer the questions