One of the major features of BigQuery is its ability to handle big data.
Generally speaking, it is not difficult technically and theoretically for a data system to process large amounts of data, but it is difficult to implement in practice because using traditional data warehousing technology, processing huge data will consume a lot of time, money and manpower. cost.
However, BigQuery uses new cloud technology and new data warehousing architecture to achieve fast computing and low cost, making computing large-scale data a practical matter and worth investing in.
4. Low technical threshold | Engineers, data analysts, marketers
BigQuery is easy to operate, and you only need to know the SQL language to get started quickly. For engineers and data analysts who already have database-related practical experience, they can oman whatsapp phone number save the cost of learning other languages. In addition, SQL command codes can be reused and are relatively easier to understand, so marketers and other data users without technical background can save the cost of communicating with engineers.
5. High flexibility for expansion | Marketing staff, IT department
Source :
BigQuery supports a variety of data import sources: including local, Google Drive, Cloud Storage, BigQuery Data Transfer Service (DTS), Data Fusion plug-in, etc., you can upload data to BigQuery through various methods. The data formats supported by BigQuery include: Avro, CSV, JSON, ORC and Parquet.
Data application :
As a cloud data service, the biggest advantage of BigQuery is flexibility.
Take the customer data platform CDP as an example. The traditional CDP is a "packaged CDP", while the new approach of using BigQuery to flexibly access and analyze data is called a "composable CDP". CDP)". The concept of Conposable CDP can help enterprises access data more flexibly and conveniently when they have more data analysis and application needs, and import the data into other front-line data platforms and marketing tools.
Let’s take a look at what BiqQuery services Crescendo has launched this time!
Large processing scale | Data usage unit
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