Google Cloud Unveils Technology for Unlimited Data Cloud Implementation

[Asia Economy Reporter Seungjin Lee] Google's cloud petabyte-scale data storage and analysis service 'BigQuery' is now available for use in data lakes.

On the 27th, Google Cloud held an online briefing to introduce new data cloud products across its data analytics, business intelligence (BI), artificial intelligence (AI), and database portfolio.

First, 'BigLake' is a feature that integrates the existing 'data warehouse' and 'data lake', extending BigQuery's high-performance storage technology to data lakes.

Companies typically use data warehouses and data lakes separately for historical analysis and future prediction purposes. Managing data with these different tools often creates barriers within organizations and incurs risks and costs when transferring data.

However, by utilizing BigLake, which removes data limitations, companies can analyze data regardless of existing storage formats or systems, gaining benefits such as cost reduction and improved efficiency.

Google Cloud explained that its client Twitter uses BigLake's storage along with the existing Google Cloud product 'BigQuery' to understand Twitter users' platform usage and content preferences without data limitations.

On the same day, Google Cloud also unveiled 'Spanner Change Streams' to realize unrestricted data cloud. This newly added feature to Google's cloud database 'Spanner' allows real-time tracking of changes such as inserts, updates, and deletions in the database.

The newly introduced 'Vertex AI Workbench' supports faster AI model development and easier maintenance. Features supporting access to Looker data models from Connected Sheets for the integrated BI platform Looker and Data Studio were also announced.

Google Cloud also announced a 'Database Migration Program' to help customers quickly move from existing cloud environments to Google Cloud's managed database services.

Jang Hwajin, President of Google Cloud Korea, said, “With the explosive increase in the volume and types of data, workloads, and users today, it has become difficult to realize the true value of data with traditional data architectures,” adding, “Through technological innovation in data cloud, we will support smooth utilization of data in cloud environments and do our best to enable customers to realize data-driven business value and drive successful digital transformation.”