R and Data Management


R is most often seen as providing a very broad range of analytical and BI functions. However, data management is much more than just analysis and visualisation. Good analytical outcomes come at the end of data value chain for effectively managing the data. The data should be well understood in its quality and lineage. The data we analyse is often the result of integration of multiple data sets varying in structure, sometimes velocity and volume. How does R manage integration?. Control over the data ensures that there is a single source of truth. Access to the data may also need to be controlled. Each one of these represents a specific kind of data practice within the overall discipline of data management.

R offers tools to help users with some of these other kinds of data management. In this presentation, R's way of managing data beyond analysis and visualisation is explored. Some of these tools will be familiar as features of R, but might be seen differently from this data management perspective. Limitations of R for data management will also be examined and therefore, we will also look at ways in which R can paired with other tools to help address those limitations.

Speaker Bio
John leads the new Strategic Data Management (SDM) group in the 460degrees expert management consultancy based Melbourne. The SDM group brings together a group of data professionals across the full range of data management discipline areas including data governance, architecture, data analysis, BI, data migration and data quality assurance, metadata management and master data management.

John previously worked with Hitwise at Connexity where he led the group responsible for developing and managing the Hitwise data. The Hitwise dataset was the largest digital market research dataset in the world. He has previously worked in market research as chief statistician with DBM consultants and at Roy Morgan Research. He has worked as a data analyst and researcher throughout his career of over 40 years.

John is passionate about the role of data in good management and decision making - 'you cannot manage what you cannot measure'. While much emphasis is put on analysis and reporting, a particular characteristics of working successfully with data is that the entire data value chain - everything that goes to make up data management - is essential. No matter what role you play with data, whether analyst or architect, appreciating the whole data management picture is essential.