Through recognizing the importance of a qualified workforce, skills research has become one of the focal points in economics, sociology, and education. Great effort is dedicated to analyzing labor demand and supply, and actions are taken at many levels to match one with the other. In this work we concentrate on skills needs, a dynamic variable dependent on many aspects such as geography, time, or the type of industry. Historically, skills in demand were easy to evaluate since transitions in that area were fairly slow, gradual, and easy to adjust to. In contrast, current changes are occurring rapidly and might take an unexpected turn. Therefore, we introduce a relatively simple yet effective method of monitoring skills needs straight from the source-as expressed by potential employers in their job advertisements. We employ open source tools such as RapidMiner and R as well as easily accessible online vacancy data. We demonstrate selected techniques, namely classification with k-NN and information extraction from a textual dataset, to determine effective ways of discovering knowledge from a given collection of vacancies.

In the aftermath of digital revolution the existence of any organisation relies upon its ability to accurately and timely answer questions. With accelerating technological advances, the HOW has been replaced with the WHAT and the WHY. Whereas many business entities struggle to survive in the word of abundance ruled by the fickle needs of their customers, governments have to stay abreast of changes to better serve the public. Despite its complexity, public sector can greatly benefit from the adoption of business intelligence that facilitates indepth analysis and informed decision making. Online services superseding traditional forms of interaction with citizens produce massive amounts of data that are sources of potentially useful information. This paper summarises the main advantages of adopting business intelligence in government driven environment. In fact, it makes valuable points for any organisation enforcing operational transparency and working for the common good.

This paper analyses the use of data mining techniques in evaluating job readiness of unemployed population in Ireland. To effectively help a jobseeker to enter or return to employment, it is necessary to develop a personal plan and provide them with suitable services. This report investigates how employment and further education needs are recognized among the customers of the Irish public employment services. Following the steps of CRISP-DM methodology, it explores the characteristics of the group and attempts to identify the underlying pattern. Finally, after applying suitable mining techniques, it is discussed whether the classification system with regard to job readiness can be automated.

Parental gender preferences may affect partnership decisions and as a result lead to early life disadvantages. We study these preferences in five post‐communist countries of Central and Eastern Europe, a region with strong traditional gender norms and persisting inequalities between women and men in labour market outcomes. Using subsamples of census from Belarus, Hungary, Poland, Romania and Russia around 2000 and 2010, we follow Dahl and Moretti (2008), The demand for sons, to examine the effect of the gender of the first‐born child(ren) on fertility decisions and relationship stability of their parents. We only find strong evidence of ‘boy preferences’ in fertility decisions in the cases of Romania and Russia. However, unlike Dahl and Moretti (2008), The demand for sons, for the US, we cannot confirm a relationship between the children's gender and parental partnership decisions. This is the case for all examined Central and Eastern European countries, as well as for a number of countries from Western Europe. The cases of Romania and Russia raise questions about other potential consequences of the documented gender preferences. We argue that our approach can be applied more broadly to identify other countries characterised by parental gender preferences, and to motivate further examination of different forms of gender driven early life disadvantages.