Issues
Big Data analytics is associated with non-negligible challenges and issues, notably veracity. This refers to the quality of the data, which can vary greatly and requires adequate approaches, rules and techniques. There are also issues related with data protection and privacy requiring safeguards.
Coverage of the labour market (demand) by OJVs needs to be assessed when exploring OJV data as a source for LMI. Certain important issues of the labour market, such as features and trends of informal employment, which in many countries is very large, remain a serious challenge for new analytics as well.
Before diving into the techniques of Big Data analytics, an interested organisation or group of stakeholders needs to start by asking:
- What is the problem at large in our domain?
- How do we see ourselves solving it?
- Who needs and who will use the insights we will deliver?
- What will be the scope, granularity and visualisation of the insights?
- Who will make sense of the data-driven insights?
Big Data for LMIS combines a range of specific elements of the digital transformation, including machine-learning algorithms, use of large volumes of internet data and specific computing architecture. These novel techniques and data sources will continue to evolve.
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