Quick BI now equips analysts with enterprise-grade, high-volume export capabilities. From any self-service query, dashboard, or spreadsheet, users can schedule a Data Export Task that runs asynchronously on the server. Once the job completes, a single click downloads the results as an Excel or CSV file—no timeouts, no browser limits. The same wizard-driven workflow applies to ad-hoc queries and parameterized reports, giving business users a seamless path from on-screen insight to offline analysis.
● Feature link: Access Knowledge Base
● Multi-system hand-offs – Business teams rarely analyse data in isolation; they must push extracts to downstream platforms, archive snapshots for compliance, or perform complex Excel modelling. Traditional BI exports cap out at 10 000 rows, forcing teams to fall back on bespoke scripts or DBA support.
● Million-row requirements – Modern retail, insurance, and IoT workloads generate granular event data well beyond the limits of standard report exports. Analysts need the freedom to retrieve entire fact tables—sometimes tens of millions of rows—without asking IT to stage flat files.
● Breadth of data sources – Quick BI connects to nearly any relational or big-data engine (MySQL, PostgreSQL, Oracle, SQL Server, Hive, MaxCompute), letting analysts query sources directly and avoid redundant ETL work.
● Export volume – Self-hosted deployments can export up to 10 million rows and public-cloud editions 1 million, using automatic chunking and compression to remove 10 k-row limits and enable data-lake-to-desktop workflows.
● Asynchronous execution – Export jobs run server-side in the background and alert users when finished, freeing browsers, preventing timeouts, and enabling reliable, unattended extraction of gigabyte-scale datasets overnight.
Beibu Gulf Insurance, a fast-growing P&C carrier, needed to extract multi-million-row policy and claim records for actuarial modelling and regulatory submission. Before Quick BI, business users filed tickets with IT, who wrote ad-hoc SQL, generated CSVs on the database server, and transferred them via SFTP—an error-prone process that could stretch over several days.
After enabling Self-Service Data Retrieval, underwriting analysts built reusable templates that join policy, premium, and claims tables, apply row-level security, and schedule exports straight from the Quick BI UI. A typical run now yields 3–5 million rows (≈1 GB) in under ten minutes, landing directly in the analyst’s local workspace. Communication overhead dropped to near zero, and actuarial cycle time improved by more than 70 %.
● Minutes, not days: >1 GB of data exported in single-digit minutes, even during peak hours.
● IT workload reduced: No database-side scripting or manual file transfers; DBAs focus on optimisation rather than ad-hoc requests.
● Auditability: Every Data-Fetch Task is logged with the SQL text, row count, and download history, satisfying compliance teams.
● Scalable foundation: The same mechanism scales from departmental spreadsheets to enterprise data-mart refreshes, future-proofing analytics operations.
With Quick BI’s high-volume export, analysts move effortlessly from interactive dashboards to deep, offline exploration—unlocking the full value of their data without bottlenecks.
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