Fast, easy-to-use, easy-to-integrate data warehousing and analysis platform

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2. Low cost | IT department, finance department
The Economic Validation report released by the authoritative research organization Enterprise Strategy Group (ESG) in 2019 pointed out that the three-year total cost of ownership (Total-Cost-of-Ownership) of large-scale execution of data analysis operations through BigQuery data warehousing technology, It is 26% to 34% lower than using the other three cloud data warehousing systems.

Save construction and management costs :

The construction cost of software and hardware for traditional data warehousing often reaches tens or even millions. Not only do you have to purchase and maintain the computer room yourself, but you may also encounter increasing analysis needs, insufficient resources, and the need to expand when using it. At this time, not only do you need to purchase oman whatsapp phone number additional hardware and software equipment, but you may also need to update the data warehousing structure. The long process consumes a lot of money, manpower, and development resources.

However, BigQuery is a cloud-based platform as a service (PaaS). Enterprises hand over all software and hardware to Google for hosting, and do not need to purchase, develop and maintain them by themselves. For enterprises, it can not only be quickly introduced and activated, but also save huge costs.

Eliminate idle and risk costs :

In addition, the traditional data warehousing method is also prone to the problem of purchasing too much, resulting in idle waste of resources. However, BigQuery is mainly charged based on usage, and is billed based on the storage and computing resources used every month. Therefore, there is less chance of idling resources or over-purchasing and wasting credit.

In addition, BigQuery also has very high standards of data security. Customers manage their own encryption keys to minimize the risk of data leakage or theft. It also provides convenient data copy and backup functions to avoid data loss.