You wouldn't buy a car or a house without asking some questions about it first. So don't go buying into someone else's data without asking questions, either.
Data management is the foundation of every good data analysis. One needs to consider issues like how data is entered, documented, and stored. Careful attention to these issues will help save time and frustration during the data analysis.
Data Analysis is an analytic process designed to explore data (usually large amounts of data - typically business or market related) in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data.
There are various ways to analyse data before undergoing through the different statistical methods, which may involve cleaning data, data transformations, selecting subsets of records and - in case of data sets with large numbers of variables ("fields") - performing some preliminary operations to bring the number of variables to a manageable range (depending on the statistical methods which are being considered).
Exploratory data analysis is used to identify systematic relations between variables when there are no (or not complete) a priori expectations as to the nature of those relations. In a typical exploratory data analysis process, many variables are taken into account and compared, using a variety of techniques in the search for systematic patterns.
Analogue has developed extensive capabilities in analysing all forms of survey data. Not only are we capable of producing standard cross-tabulations, but also non-standard and unusual types of data analysis. We are also able to enhance the cosmetic appearance of tables and analyses, by putting the computer output through a desktop publishing package, to produce a professional finish.