  Traditional data systems require specialized technical skills where users
need to understand the data organization and write precise queries to access
data. Therefore, novice users who lack technical expertise face hurdles in
perusing and analyzing data. Existing tools assist in formulating queries
through keyword search, query recommendation, and query auto-completion, but
still require some technical expertise. An alternative method for accessing
data is Query by Example (QBE), where users express their data exploration
intent simply by providing examples of their intended data. We study a
state-of-the-art QBE system called SQuID, and contrast it with traditional SQL
querying. Our comparative user studies demonstrate that users with varying
expertise are significantly more effective and efficient with SQuID than SQL.
We find that SQuID eliminates the barriers in studying the database schema,
formalizing task semantics, and writing syntactically correct SQL queries, and
thus, substantially alleviates the need for technical expertise in data
exploration.
