Self-service has been the most dominant trend in the business intelligence and analytics world for the last few years, and rightly so. Line-of-business managers and analysts have been using tools such as Tableau and Qlikview to develop visualizations and reports by themselves instead of having to wait on IT to develop those for them.
The explosion in semi-structured and unstructured data does, however, now mean that line-of-business managers and analysts need to factor in more diverse and complex data than ever before. In other words, the bar for self-service analytics is being raised again. These new data types are being stored in Hadoop and NoSQL systems. Modeling data and developing schemas upfront is not a great option, since the types and formats of data change frequently.
Additionally, the rapid pace of data exploration gets hindered by the typical process of defining schemas and modeling. The clear answer is a SQL engine that can query any type of data and in any format. Read this whitepaper, "How Drill Enriches Self-Service Analytics" to learn how Apache Drill can: