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Big Query is a advanced and multi-cloud data warehouse designed by Google, created with the aim of business flexibility.

What do you need to know about Big Query?

Big Query is a scalable data warehouse (cloud data warehouse) designed by Google, a global giant known by almost every internet user. What are the areas of application for this solution? It must be admitted that Big Query offers many possibilities.

Big Query allows for handling millions of queries and conducting advanced analysis of significant amounts of data in SQL language. Knowledge of this language is quite important here. At the same time, entities that use this solution do not have to worry about high costs associated with maintaining advanced technological infrastructure or scaling or balancing traffic. Google offers all new customers $300 of free funds that can be spent on Big Query. Additionally, all customers receive completely free 10 GB of storage space and even 1 TB of queries per month.

Data can be quickly uploaded or downloaded from Big Query and then analyzed in detail. We only pay for the data that we analyze, and only after exceeding the aforementioned 1 TB limit. To use Big Query, we do not have to invest in expensive equipment and tools and technologies, while the configuration is exceptionally simple.

What are the main advantages of Big Query data warehouse?

Big Query is one of the most popular data warehouses. This is mainly due to the fact that it offers a wide range of features, which are appreciated by thousands of data processing and analysis entities worldwide.

The most important advantages of the Big Query data warehouse are as follows:

• No need to invest in your own server – all data is stored in cloud technology.
• Data analysis using Big Query is fast and efficient. Big Query data warehouse stands out for its ability to analyze large amounts of data significantly faster than traditional databases. One petabyte is processed in about 3 minutes, and one terabyte in just a few seconds. This fast operation time ensures that, regardless of how much data we have to analyze, we will get results at a rapid pace. Data analysis is performed in real-time, and all changes can be observed in real-time.
• Full control over costs. In Big Query, we only pay when the number of analyzed data exceeds 1 TB per month. This billing model gives us full control over the expenses. If we do not use the tool at all or do not exceed the specified limit, we will not pay a penny.
• BigQuery offers a machine learning feature. Big Query ML feature enables creation and development of machine learning capabilities using classic SQL queries. This tool allows you to check trends, which helps to design a long-term strategy for the company in specific areas.
• The Big Query data warehouse can be invaluable in any industry. The need for fast and efficient information analysis is visible in many industries – finance, industry, marketing, logistics, etc. Therefore, any company that wants to gain significant competitive advantages should consider using it.

Why choose Big Query data warehouse?

Year after year, more and more entities analyzing significant amounts of data are choosing Google Big Query. This is because with this solution, we do not have to invest in modern equipment, manage infrastructure, perform configuration or software updates. Google engineers are responsible for ensuring proper tool operation. We can then focus on proper analysis and data collection.

To be able to use the possibilities offered by Big Query, we do not have to make major changes or rewrite the source code. This is because Big Query supports the ANSI SQL:2011 standard and also offers ODBC and JDBC programming interfaces for free.

In Big Query, we also do not have to worry about creating backups – the program performs backups on its own, which are later stored for 7 days. During this time, we can familiarize ourselves with the entire history of changes and, if necessary, restore one of the previous versions.

Big Query also has a very high level of security – the tool is known for its reliable security, management, and reliability mechanisms. All data stored in the program is encrypted by default. Google states on its website that it guarantees 99.99% uptime.

Limitations of Big Query data warehouse

Big Query data warehouse has certain limitations and limits in terms of information processing. The most important of these are as follows:

• Maximum number of exported bytes per day. The limit is 50 terabytes per day.
• Maximum number of exports per day. The limit is 100,000 exports per day.
• Number of daily queries. There are no limits on the number of bytes that can be processed in queries within a given project.
• Number of daily queries per user. There are no limits on the number of bytes that users can process in queries per day.
• Number of bytes of processed query data per hour. The limit is 1 terabyte per hour.
• Maximum size of a single table. The limit is 10 terabytes.
• Maximum size of a single partition. The limit is 4 terabytes.
• Maximum number of columns in a table. The limit is 10,000 columns.
• Maximum number of rows in a table. The limit is 1 trillion rows.
• Maximum number of partitions in a table. The limit is 10,000 partitions.

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