Users extract data from production databases, performance at risk Applications in: Oracle 10g, 12c, SQL Server, Files, SAAS Creation of a data lake for query off-load Add semi-structured data from external applications and files Creation of a corporate DWH Data lakehouse platform. Data lake: - Object Storage - Autonomous Transaction Processing Datawarehouse: - Autonomous Data Warehouse Data integration: - Oracle Data Integrator Low-code development: - Oracle Application Express Use of ODI automations New secure source for reporting Autonomous database flexibility Business requirements are met quickly Analytics capabilities in DL and DWH
• Low-maintenance • Low-code • Template based integrations • 10+ data sources. • Different character sets, • Data type conversions. • High latency network. • Execution control and monitoring. • Tables with manual maintenance Project challenges Autonomous databases Oracle Data Integrator - ODI Oracle Application Express - APEX
by Oracle • Self driving, self securing, self repairing • Based on Oracle 19c • Automatic indexing • Automatic partitioning • Application Continuity • Three flavours based on your main workload • analytic, transaction processing or JSON Autonomous database
the big tables is live data. • Oracle 19c hybrid tables store part of the data as external data (files) and part as database table space. • External data can be stored in Object Storage. • Live data (most recent) can be stored in the database space and historic data can be stored in Object Storage (much cheaper). • The access is transparent for applications The "Tables with 500 GB" challenge
SQL functions • All processing inside the database, no data movement, database security applies • Languages: OML4SQL, OML4Py (Python), OML4R (R) • Interface for data scientist: Oracle Machine Learning Notebooks, based on Zeppelin notebooks • Auto Machine Learning In-database Machine Learning
generation of targets • Automatic generation of simple mappings • Based on code templates • Based on execution contexts: separate physical and logical layers to allow easy environment promotion Oracle Data Integrator - ODI
From data lakes takes: • Low-cost • Flexible storage • Unstructured data • From data warehouses takes: • Data management features • Data cleansing and ETL tools • Analytical query performance SQL or API access to every layer Easy movement from low-cost storage to analytical storage Artificial intelligence and ML capabilities in every layer Seamless access from the database to object storage Data Lakehouse platform
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