I am on a project dealing with a lot of data in the form of images and videos (Data related to wind engineering). My requirement is to build a predictive algorithm based on the data I have. I have found many tools with which I can analyse the data where each tool has its own advantages and disadvantages. Big data being really new to me, I find it very difficult to choose a platform to start with. There should be other people here who should have dealt with similar situations.What criteria should I mainly take into account before selecting atool for analysing big data?I could update my question with the tools that I have found so far if that would be relevant for the question and my requirement.UPDATESome of the Criteria that I have taken into account : Visualization, Interaction, Security, Data Access and integration, Speed of response, Integrated Data Mining, Pattern Matching, Ease of use etc. As you can see the list that I have made for the criteria comes from the extensive reading of different articles on the topic. But I can't narrow down the list nor find the individual contribution of these criteria in the various tools available for analysis.Let me also list some of the tools that I found after googling : Knime, Statistica 2, Rapidminer, Orange, WEKA, KEEL, R and RATTLE. On what basis could I choose a tool from a list of tools that perform similar tasks?
Dealing with big data
performance;data;tools;big data