A company has invested tens of millions of dollars to collect, store, back-up, secure, and hire individuals to manage a data warehouse. Still, whenever data are actually extracted from the warehouse and used to help solve a business problem, the process of data preparation (e.g., cleaning, filtering, exploring, etc.) can typically take up to 80-90% of the time spent on an analytics project. The other 10-20% makes up the actual analytics/modeling of the data. This data paradigm has existed for many years in the company. What are some of the things that a company can do so that most of an analyst's time is spent actually doing analytics rather than getting the data ready?