As all data in MOOC is big data so if we are using dash boards for showing students performance or progress, then it will be considered as part of learning analytics or Big data analytics ?
What's the exact line of difference between the two.
Dear Jyoti,
Big Data refers to humongous volumes of data that cannot be processed effectively with the traditional applications that exist. The processing of Big Data begins with the raw data that isn’t aggregated and is most often impossible to store in the memory of a single computer. A buzzword that is used to describe immense volumes of data, both unstructured and structures, Big Data inundates a business on a day-to-day basis. Big Data is something that can be used to analyze insights which can lead to better decision and strategic business moves. The definition of Big Data, given by Gartner is, “Big data is high-volume, and high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation". However, learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. Data Analytics the science of examining raw data with the purpose of drawing conclusions about that information. Data Analytics involves applying an algorithmic or mechanical process to derive insights. For example, running through a number of data sets to look for meaningful correlations between each. However, please see this video tutorial to learn more about Mooc:
https://www.youtube.com/watch?v=eW3gMGqcZQc
Given the currently ever growing volume of information, the Big Data and Data Analytics are essential to give sense or highlight important-relevant information to the subject of interest. The You Tube video on Mooc is very good and clear introduction. There are many tools and platforms such as Data Centers, where Big Data are stored, processed and communicated such as, Google - Facebook - Amazon -Plus Data Centres.
Keep in mind that not all MOOC data are considered big, especially outside of an educational context.
You can think of learning analytics and big data analytics as two circles in a Venn diagram. Assuming the MOOC data underlying your analytics dashboard can be described as big, it would be represented by the intersection of these two circles.
Big Data applications in education uses tools such as Hadoop, Hive, Sqoop, and MongoDB.
Chapter Affordances of Data Science in Agriculture, Manufacturing, a...
Given the global nature of large enterprise you may find interesting the data-analytics example in the ERP SAAP, such as: the ERP Core with SAP S/4HANA https://www.sap.com/index.html
and baton simulations: http://www.batonsimulations.com/
Data analytics is generally more focused than big data because instead of gathering huge files of unstructured data, data analysts have a specific goal in mind and sort through relevant data to look for ways to gain support. On the other hand, big data is a collection of a huge volume of data that requires a lot of filtering out to derive useful insights from it.
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