Big Data Book Explained

My Big Data book In yesterday's blog, I announced the publication of my new book, Principles of Big Data, 1st Edition: Preparing, Sharing, and Analyzing Complex Information.  Here is a short essay describing some of the features that distinguish this Big Data book from all of the others.The book describes:How do deal with complex data objects (unstructured text, categorical data, quantitative data, images, etc.), and how to extract small data sets (the kind you're probably familiar with), from Big Data resources.How to create Big Data resources in a legal, ethical and scientifically sensible manner.How to inspect and analyze Big Data. How to verify and validate the data and the conclusions drawn from the data..The book expands upon several subjects that are omitted from most Big Data books.Identifiers and deidentification. Most people simply do not understand the importance of creating unique identifiers for data objects. In the book, I build an argument that Big Data resources are basically just a set of identifiers to which data is attached. Without proper identifiers there can be no useful analysis of Big Data. The book goes into some detail explaining how data objects can be identified and de-identified, and how data identifiers are crucial for merging data obtained from heterogeneous data sources. Metadata, Classification, and Introspection. Classifications drive down the complexity of Big Data, and metadata permits data obje...
Source: Specified Life - Category: Pathologists Source Type: blogs