Scuba Tech Library

What is Querying?

In order to receive information from a database, the ask needs to be in a language the database can understand. A query is a question or request for a database written in a code the database can correctly interpret, retrieve, or manipulate the right information. Among its uses, querying can uncover trends and other insights in data to help an enterprise make data-informed decisions. 

How does querying work?

There are different kinds of querying languages for various databases and functions, but the language most universally used is known as SQL. In turn, MySQL serves as the software that uses the SQL query language. Depending on the query language and its complexity, requested data can be displayed in simple rows and columns or as more sophisticated graphs. Other less frequently used languages include AQL, DMX, and Datalog.

Querying can be used to fetch data, known as select queries, or to modify data, known as action queries. Querying requires specific knowledge about the language being used in order to make requests, but there are ways to enable less advanced users to query a database, such as through the use of querying by example (QBE), which uses SQL statement templates with blank areas that users can add fields and values to. 

In addition to the SQL database, which is a relational database type good for ACID (atomicity, consistency, isolation, durability) compliant data structures, NoSQL is a type of database that’s an option well-suited for unstructured data. 

Different methods of querying

Queries can be simple or complex depending on the use case. Queries can return a broad amount of data or be more granular by setting conditions and restrictions. Some examples of methods of querying a database include:

  • Limiting fields that are searched
  • Setting a condition that limits queries to entities with a certain number of links
  • Running queries with a specific entity or link types 

What are queries used for?

In a nutshell, queries help a user find data and put it to work, and can be used for a variety of different functions, including:

  • Automating data management tasks
  • Summarizing data to uncover trends and other insights
  • Reviewing multiple tables in a single datasheet
  • Performing calculations
  • Modifying data in a database, such as adding, changing, or deleting data

How Scuba makes querying easier

Using querying languages such as SQL enables a user to locate, modify and put data to work. But, effectively harnessing the power of queries for databases requires knowledge of the code and the ability to navigate complex platforms. While there are some methods--like the QBE model--that simplify the process and make it easier for those with less technical know-how to input queries, they come with some trade-offs, such as flexibility. 

No-code querying solutions, like Scuba Analytics, eliminate this barrier to entry by making working with data more accessible and easier to digest for all stakeholders in a business. Learn more about how Scuba Analytics democratizes data across enterprise teams to find valuable insights to drive business decisions and strategies, here

Data Science

Data Lakes and Data Warehouses -- Which Is Right For You?

Data lakes and data warehouses are both commonly used for storing data, but there are key differences between the two that make them unique in their own way. Learn which fits your business purposes best and if there is a better solution.

Data Science

What is a Data Ecosystem?

The term “data ecosystem” collectively refers to all the programming languages, algorithms, applications, and the general infrastructure used to collect, analyze and store data.

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What is Data Modeling

Data modeling is a means of creating a conceptual framework for your data in preparation for storage in a data warehouse. The resulting model is a visual representation of the data which maps out the relationships between data, and the rules.

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What is Lambda Architecture?

Lambda architecture processes data through a hybrid combination of batch processing and stream processing.

Data Science

What is an ETL Pipeline?

ETL is a method to collect raw data from various sources, clean it up, and translate it so it can be used to inform decision making.

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What is Data Governance?

Data governance allows organizations to ensure high-quality data through formalized processes for management, monitoring, and control of data assets.

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What is Hadoop?

Apache Hadoop is one of the most widely used open source frameworks designed to address the problem of storing and processing big data.

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What is Parquet?

Unlike row-based formats such as CSV, Parquet is a columnar data file storage format.

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What is an Ad Hoc Query?

An ad hoc query is any kind of question you can ask a data system off the top of your head.

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What is Metadata Storage?

When building a database, all data requires some description to help identify its uniqueness, which is where metadata comes in.

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What is a Data Platform?

Data platforms are tools that allow businesses to collect, analyze, and present data.

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What is an Enterprise Data Warehouse?

An EDW is a database that centralizes data from across the business so it can be analyzed and used in decision making.

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What is Time-Series Data?

Time-series data analysis serves critical functions in most modern industries, and is a powerful method to glean accurate analysis.

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What is Data Sovereignty?

Data sovereignty defines the regulations data is subject to. Fortunately, there are actionable steps brands can take to ensure compliance.

Data Science

What is Self-Service Analytics?

Self-service analytics empower non-technical teams to interact with data, perform queries, and glean helpful business insights.

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