An Introduction to Query Builders

Query Builder is a tool that allows users to create complex SQL queries without needing in-depth knowledge of the SQL programming language. This can be especially useful for those who are new to SQL or who need to generate complex queries on a regular basis but do not have the time or expertise to write them manually.

One of the key benefits of using Query Builder is that it allows users to build queries visually, by dragging and dropping different components such as tables, columns, and conditions into a graphical interface. This makes it easy to see how the various components of the query fit together and to make changes or adjustments as needed.

In addition to its visual interface, Query Builder also offers a number of advanced features that can help users generate more complex queries. For example, it allows users to define and save their own custom functions, which can be used in queries to perform complex calculations or operations. It also supports features such as subqueries and union queries, which can be used to combine data from multiple tables or queries in a single result set.

DataOps Suite: Query Builder

DataOps Suite: Query Builder

For Beginners as well as Experts: While a SQL Query Builder might seem like a tool built to help professionals outside of the Data warehousing and ETL space to work with records, a huge number of QA Testers and Data Engineers use Query Builders on a daily basis to increase their efficiency and speed of creating the required queries.

For a Professional who has to produce and maintain a large number of queries on a daily basis

    • First, a query builder can make it easier and faster to create complex queries. With a query builder, you can visually construct a query by selecting different clauses and options, rather than having to write out the entire query in text form. This can save time and reduce the risk of syntax errors.
    • Second, a query builder can also help with query organization and management. Many query builders have features that allow you to save and reuse queries, as well as to share queries with others. This can make it easier to keep track of the queries that you have created and to collaborate with others on complex data analysis tasks. In the tool, past queries can be pulled up for reference, reuse, and specific checks.
    • Third, a query builder can also provide useful tools and features that can help you to optimize your queries and improve their performance. The DataOps Suite also holds tools made specifically to stress test ETL pipelines and using the “Enable / Disable” functionality along with the Test Data Manager System, a user can easily optimize the query in question.

DataOps Suite: Query Enable/Disable Function

For a person unfamiliar with SQL

    • A query builder can be useful for anyone who needs to access and analyze data stored in a database. For example, a sales manager might use a query builder to create queries that extract data about sales performance, customer demographics, and other metrics that are relevant to their role.
    • A query builder can also be useful for anyone who needs to collaborate with others on data analysis tasks. For example, a marketing manager might use a query builder to create and share queries with their team, or to work with data analysts on complex analysis projects.
    • A query builder can also be useful for anyone who needs to create and manage large numbers of queries on a regular basis. For example, an HR manager might use a query builder to create and manage a collection of queries that are used to extract and analyze data about employee performance, retention, and other HR metrics.

Also Read: Monitoring Your Data Pipelines In Production using DataOps Suite

Getting to Complex SQL Queries

In this section, we will showcase the DataOps Suite’s Query Builder in action creating a complex query with over 6 tables and a multitude of filters, groupings, and aggregations. But before that, a quick recap of the basics.

Recap of Basics

The traditional method of writing SQL queries is as follows –

    • Identify the data you want to retrieve from the database.
    • Determine the tables in the database that contain the data you want to retrieve.
    • Determine the relationships between the tables, such as which tables are related through foreign keys.
    • Write the SELECT statement that specifies the columns you want to retrieve from the tables.
    • Use the JOIN clause to specify how the tables are related and to retrieve the data from multiple tables in a single query.
    • Use the WHERE clause to specify any conditions that must be met for a record to be included in the result set.
    • Use the GROUP BY and HAVING clauses to group records and specify conditions for the groups.
    • Use the ORDER BY clause to specify the order in which the records should be returned in the result set.
    • Functions and Aggregations can be added with specific clauses given that their grouping elements are defined as well.

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It’s important to note that these are just general steps and the exact process for writing a complex SQL query can vary depending on the specific requirements of the query. Additionally, the complexity of a SQL query can vary greatly, so the steps outlined above may not be applicable to all complex queries. It’s always a good idea to consult the documentation for the specific SQL dialect you’re using to make sure you’re using the correct syntax and features.

Complex SQL

The video at the end shows the tool working in real time to create the query. The representation here is to showcase the speed and efficiency of using this tool as this removes a lot of fluff that engineers have to write up before even getting to the important parts of the query. In these parts, getting the naming convention correct, making sure syntax is not just valid but also what is expected, and the correct set of parameters have been set up is an error-prone if not a time-consuming task. Here, Query Builder shines to ensure that these aspects are taken care of so that users only think of the exact logic in question.

The problem statement here is that a User has to pull a set of records. The tables in question are Promotion, Product, Channel, and Cost-related Datasets. The User has to apply multiple sets of filters across all the tables, join them on the correct parent-child keys, choose the expected columns, and validate the query before testing/running it.

DataOps Suite: Complex Query Builder

Conclusion

While a SQL expert can build up the most complex of queries on a regular basis without any hiccups and a manager could ask the DE at hand to retrieve the required records from the database, having the tools to ensure that writing these queries is simple, fast, consistent, easy to implement and easy to maintain. This ensures that if an individual has the set of rules to be applied and access to the correct datasets, they can bring out the intended results without questioning syntax, joining keys, or aggregation columns.

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The Datagaps’ DataOps Suite now comes with new components that add extensibility and connectivity with other applications as well as a focus on ease of creating tests by automatically creating SQL Queries and identifying anomalies based on data profile.

 

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Datagaps

Established in the year 2010 with the mission of building trust in enterprise data & reports. Datagaps provides software for ETL Data Automation, Data Synchronization, Data Quality, Data Transformation, Test Data Generation, & BI Test Automation. An innovative company focused on providing the highest customer satisfaction. We are passionate about data-driven test automation. Our flagship solutions, ETL Validator, Data Flow, and BI Validator are designed to help customers automate the testing of ETL, BI, Database, Data Lake, Flat File, & XML Data Sources. Our tools support Snowflake, Tableau, Amazon Redshift, Oracle Analytics, Salesforce, Microsoft Power BI, Azure Synapse, SAP BusinessObjects, IBM Cognos, etc., data warehousing projects, and BI platforms.  www.datagaps.com 

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