Couple of weeks back, I did a talk titled "Big Data Analysis:Deciphering the haystack" , which is about different tools available for bigdata analysis.
Tools I categorised based on following taxonomy based on what they do. Note there are tools for streaming (a.k.a. realtime) analytics as well as for store and processing.
Also I categorised Analysis techniques, or in other words making sense of data, based on what they are used to achieve into three sub topics based on the goals.
Following is the slidedeck I used, and please check it out for more information.
Tools I categorised based on following taxonomy based on what they do. Note there are tools for streaming (a.k.a. realtime) analytics as well as for store and processing.
Also I categorised Analysis techniques, or in other words making sense of data, based on what they are used to achieve into three sub topics based on the goals.
- To know what happend - this is basic analytics
- To explain what happend - this is detecting patterns. e.g. data mining.
- To forecast what will happen - this is forecasting models e.g. regression, numerical modes (e.g. weather models that use simulation) and other machine learning algorithms etc.
Following is the slidedeck I used, and please check it out for more information.
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