{'fraction_non_alphanumeric': 0.03015075376884422, 'fraction_numerical': 0.0, 'mean_word_length': 4.858823529411764, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Number Crunching for Fun and Profit

Abstract Organizations generate and store huge amounts of data. They use if for transaction processing, business intelligence, data mining, planning, decision making, and much more. It is the lifeblood for managing the organization. Yet data in many ways is a much-neglected subject. Yet, important changes are happening. All three books reviewed deal with coping with data in large quantity. The first book doesn't just whine about how we limit ourselves to nicely structured information in rows and columns. It is a seminal work co-authored by Bill Inmon—a founder of data warehousing—which finally brings unstructured data into the mainstream. The next deals with business intelligence—that is, the use of large volumes of data in decision-making. The third, written in a mostly non-technical, anecdotal style, is about data mining and analysis of large data sets. Taken together they represent a renaissance of thinking about data, the root of our field.