To slice and dice is to break a body of information down into smaller parts or to examine it from different viewpoints so that you can understand it better.
The term has its roots in cooking and describes two types of knife skills every chef needs to master. To slice means to cut and to dice means to cut into very small uniform sections and the two actions are often performed sequentially. For example, a chef may first cut an onion into slices and then cut the slices up into dices. In data analysis, the term generally implies a systematic reduction of a body of data into smaller parts or views that will yield more information. The term is also used to mean the presentation of information in a variety of different and useful ways.
Pivot tables are a popular self-service BI tool for slicing and dicing data. Essentially, a pivot table sorts, counts and totals the data stored in one database table or spreadsheet and creates a second table – the actual pivot table – that summarizes the data. Typically, users will use a pivot table to extract information from a BI solution’s data warehouse in order to mine through data in an interactive manner without requiring the IT department to run an ad hoc report.
Slice and dice contrasts with the terms drill down, drill across and roll up. To drill down is to look at more detailed data in progressively deeper levels of a body of information's hierarchy. To drill across is to compare data in similar levels of a body of information's hierarchy, and to roll up is to aggregate data by removing detail levels from the hierarchy.