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REAL-TIME ANALYTICS

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INTRODUCTION  It is important to deal with real-time data when it comes to visual analytics. As the stream processing engines, there are several ways to use like WSO2 SP, Esper, Kafka streaming and etc. which you can use for real-time event processing. In here I have used WSO2 Data Analytics Server. WSO2 Data Analytics Server (DAS) listens to a constant stream of events that represents the transactions and activities of an enterprise from different sources, processes them in real time and communicates the results in a variety of interfaces. This allows organisations to respond quickly to their environments, thus gaining an advantage over their competitors. In addition, WSO2 DAS combines real-time analytics with batch (equipped with incremental processing), interactive and predictive (via machine learning) analysis of data into one integrated platform to support the multiple demands of the Internet of Things (IoT) solutions, as well as mobile and Web apps as...
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BATCH ANALYTICS

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INTRODUCTION This blog mainly consists of two parts. Batch analytics  Real-time analytics Above two parts are combined with 3 different phases.  Data collection (Source of the data)  Data processing  Data visualization Since test data is already provided with no need to invest much time for data collection purposes but there is some work involved in this for real-time analytics First We'll look into the  Batch analytics section. BATCH ANALYTICS  Step 01 -Data Collection (Given Data Set) Step 02 -Data Preprocessing This involves the multiple steps for cleaning and pre-processing the dataset. There are two main packages in python which can be used to perform this:  pandas  and  numpy. Points to Remember:        The  pandas  package provides high-performance, easy to use structures and data analysis tools. The  numpy package  is  used  to perform differen...
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