Big Data processing deals with the data collection and preparation for later analysis. For example, collecting unstructured, structured, and semi-structured and using Hadoop and Map-Reduce techniques in order to prepare data for analysis. This involves understanding the problem from SCV (Speed, Consistency, and Volume) perspective and if the data is accessed in realtime or batch to define the proper "workloads" and to distribute the tasks properly.
The analysis, on the other hand, focuses on the prepared data in a form that lets different techniques such as machine learning techniques to be applied in order to understand the patterns, trends, relationships and such among the data.
There is also another term, data analytics, that is more widely used in Big Data, which refers to the management of a combination of data processing and data analysis methods development. In fact, in data analytics, data scientists try to develop scientific methods that would be used in data analysis.
A very good resource that you can cosult with is: "Big Data Fundamentals" by Erl et al.
