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Real Time Event Processing

This includes event by event processing by analyzing continuous stream of real-time data with the help of continuous queries.The knowledge thus gained helps in under- standingwhat can be used for making effective decision and to identify actionable patterns and trends(Harzog, 2015). This includes two important set:

1. Aggregation-Oriented Processing: In this online algorithm is created so that required processing of the data entering into the system can take place. It is the analytical process for analyzing and exploring large data sets to find hidden rules, associations, patterns among the parts of data, which help to formalize and plan the future decision making process which is enabled by knowledge featureFor example, for an inbound event calculating the average of the data. 2. Detection-oriented processing: In this we look for the specific pattern and behavior of the events so that valuable insights can be converted into actions. This analysis helps to understand what customer wants to purchase, where they want to go on vacations, what they want to eat etc. So that valuable insights can be converted into actions. The knowledge thus gained helps in understanding the needs of every customer individually so that it becomes easier to do the business with them.

Comprehensive Data Collection

Voluminous amount of data needs to be enterinto the computer system in the format which can be understood by the computer. For storing data into data warehouse it needs to follow certain rules while maintaining the consistency and integrity of the data. This helps in discovering, exploring and extracting unseen patterns and relationship among large data sets. Analyzing erroneous data leads to the discovery of wrong patterns and relationship. Thus false information will be gained resulting into the production of imprecise results (Harzog, 2015).

Deterministic Data Collection

In this we focus on calculating as close value to the actual as possible and not an estimated value. This helps to understand the needs and behavior of growing IT industry in the better way because averaging value sometimes lead to enormous decision.

 
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