Learn how Apache Doris breaks down data silos for insurance firms, streamlining customer data integration and boosting efficiency.
The data silos problem is like arthritis for online businesses because almost everyone gets it as they grow old. Businesses interact with customers via websites, mobile apps, H5 pages, and end devices. For one reason or another, it is tricky to integrate the data from all these sources. Data stays where it is and cannot be interrelated for further analysis. That's how data silos come to form.
partial column update set enable_unique_key_partial_update=true; insert into tb_label_result select one_id, label_value as labelxx from ..... 2. Real-time tags: Partial column updates are also available for real-time tags since real-time tags are updated at different paces. All that is needed is to set to . partial_columns true curl --location-trusted -u root: -H "partial_columns:true" -H "column_separator:," -H "columns:id,balance,last_access_time" -T /tmp/test.
Conclusion From CDP 1.0 to CDP 2.0, the insurance company adopts Apache Doris, a unified data warehouse, to replace Spark+Impala+HBase+NebulaGraph. That increases their data processing efficiency by breaking down the data silos and streamlining data processing pipelines. In CDP 3.0 to come, they want to group their customer by combining real-time tags and offline tags for more diversified and flexible analysis. The and the team will continue to be a supporting partner during this upgrade.
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