Big Data Skills Gap Questionnaire
This questionnaires purpose is to assess the big data skills gap coming from industry requirements with a focus on the digital economy.
This questionnaire was designed by Cambridge Spark, EJJV and UCTS.
Wh at are your industry sectors?
Infrastructure and Construction
Oil and Gas
What sort of data do you work with?
Textual data (documents, pdfs, surveys etc)
Numerical Data (e.g. sensor values, transactions)
Tabular data (e.g. excel spreadsheet, csv files)
Graph and Network data
Unstructured (a mix of everything)
What are the business outcomes you seek to achieve?
Increased revenue via new products
Higher operational efficiency
Better insights of the business through collection and processing of quantitative data
Increase automation of internal processes
What are the most relevant data science techniques and technologies to apply to your business problems?
Summarisation of data and Visualisation
Clustering (e.g. customer segmentation)
Time Series Analysis
NoSQL (document-oriented, graph databases)
Big Data Processing (e.g. Spark)
Big Data Storage and Data Warehousing (e.g. Parquet, Redshift, Hive)
Deep Learning (e.g. image recognition, video recognition)
Natural Language Processing (e.g. text summarisation, topic modelling)
Deploying Machine Learning in Production (monitoring, maintenance and optimisation of predictive models)
How many data scientists do you foresee your organisation will require within three years?
What is your biggest challenge you need support with?
What programmes are you most interested in for you or your organisation?
One-Month Python Programming Bootcamp in Sarawak
Six-Month Data Science Leaders Exchange Program in Cambridge, UK
Three-Month Data Analyst Program
One-Day Executive Seminar: Becoming data-driven: Leverage your defensible asset
Two-Day Executive Seminar: Making Sense of Emerging Technology Trends
Short Intensive Hands-on Data Science and Machine Learning Training Courses
Data Science Awareness Seminar for Executives And Data Science Consulting Process
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