Traditional database theory dictates that you design the data set before entering any data. A data lake, also called an enterprise data lake or enterprise data hub, turns that model on its head, says Chris Curran, principal and chief technologist in PricewaterhouseCoopers’ U.S. advisory practice.  “It says we’ll take these data sources and dump them all into a big Hadoop repository, and we won’t try to design a data model beforehand,” he says. Instead, it provides tools for people to analyze the data, along with a high-level definition of what data exists in the lake. “People build the views into the data as they go along. It’s a very incremental, organic model for building a large-scale database,” Curran says. On the downside, the people who use it must be highly skilled Speed of NOSQL Alternatives to traditional SQL-based relational databases, called NoSQL (short for “Not Only SQL”) databases, are rapidly gaining popularity as tools for use in specific kinds of analytic app...