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.

中文翻译：

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示例驱动的用户意图发现：使用户能够通过示例查询来跨越SQL障碍

传统的数据系统需要专门的技术技能，用户需要了解数据的组织并编写精确的查询来访问数据。因此，缺乏技术专业知识的新手用户在阅读和分析数据时会遇到障碍。现有的工具可通过关键字搜索，查询推荐和查询自动完成来协助制定查询，但仍需要一定的技术知识。访问数据的另一种方法是“按示例查询”（QBE），其中用户仅通过提供其预期数据的示例即可表达其数据探索意图。我们研究了一种称为SQuID的最新QBE系统，并将其与传统的SQL查询进行了对比。我们的比较用户研究表明，具有不同专业知识的用户使用SQuID的效率和效率明显高于SQL。