![]() ![]() The case studies received already show a range of approaches to data stewardship with different levels of involvement from the NSO. The practices reviewed through the case studies were organized under four outcome 'pillars': better governance, better collaboration, better methods and capability and better access and understanding. The HLG-PCCB, in undertaking the review, defined data stewardship with the broad goal to improve the use of data in society. ![]() In 2020, the High-level Group for Partnership, Coordination and Capacity-Building for statistics for the 2030 Agenda for Sustainable Development (HLG-PCCB) initiated a review of existing practices attributable to data stewardship in National Statistical Offices and other Government bodies. This year's event on data stewardship builds on the discussion held last year at the High-level Forum on Official Statistics during the 51st session of the UN Statistical Commission (UNSC) on whether the concept of data stewardship is an approach NSOs can use to realize opportunities presented in this rapidly changing data ecosystem and addresses some of the huge transformations the data landscape is presenting to NSOs some of which are being accelerated by the impact of Covid-19. In the new data ecosystem, NSOs can broaden their mandate and play the role of data stewards at different levels and with different arrangements, to ensure the efficient utilization of all data sources while safeguarding data quality, confidentiality and security. NSOs (National Statistical Offices) have proved the value of official statistics as a trusted source of information. The more extensive use of private sector data during the pandemic has also intensified the need for improved data governance and for developing principles and tools for data privacy protection. Over the last year, the new challenges posed by the Covid-19 pandemic have accelerated this transformation and often forced national statistical offices to reshape their data programmes to adapt to the new circumstances. With data demands ever increasing and a rapidly changing data ecosystem, national statistical authorities have responded by modernizing and integrating new data sources in the regular data production and strengthening their role as coordinator and custodians of data principles and data quality. Principles Governing International Statistical Activities.Fundamental Principles of Official Statistics.National and international data sources and links.Civil registration and vital statistics.How would a new team member know if “Eric Smith” is actually spelt “Erik Smith”? However this would be glaringly obvious to a sales person that speaks to Erik on a daily basis. Hiring a data expert for your team will only fix certain things, but what about data that needs context e.g. A lot of this comes from the fact that this person may not know the context behind the data, they may not be the best person to qualify data. To know if you have these types of people at your work already, ask yourself this question, if the data quality of a system is bad, do you know who is responsible? Could this person be held accountable or even fired if the quality is not good enough or if initiative is not shown to make it better over time?Įven with this organisational governance in place, few have the technology needed to fuel these individuals with a good process around increasing the quality of data. The CRM is probably the best example in the past, of systems that are governed the most - as, if the CRM is of good quality, then proper sales forecasting can be achieved and more. The new roles revolve around this idea of being responsible for data quality of a particular set of data. There are new roles emerging in the data space, but yet very few businesses have established a process to enable these new roles. How does the Data Steward and Data Citizen play a role today?
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