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Oracle Analytic Views

Learn about Oracle Analytic Views, a new feature in Oracle Database that simplifies development and optimization of BI applications. Enhance data sets with business models, simplify SQL queries with no joins, and optimize query performance.

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Oracle Analytic Views

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  1. Oracle Analytic Views Enhance BI Applications and Simplify Development William (Bud) EndressDirector, Product ManagementOracle Database Server TechnologyOctober 25, 2018

  2. Oracle Analytic Views What are they? A new (as of 12.2) type of view in the Oracle Database Like other views, they access data from other row sources in the database (tables, views, external tables, etc.) Analytic views enhance data sets with A dimensional business model A dimensional and hierarchical expressions A query transformation engine

  3. Oracle Analytic Views What can you do with them? Moves business logic (aggregations, hierarchies, calculations) back into database One definition, accessed by many applications Simple SQL for complex analytic queries no joins or GROUP-BY clauses necessary Optimize query performance Smart query transformation engine Simple aggregate management

  4. Analytic View Layers and Features

  5. Oracle Analytic Views Easier Access To Your Data SQL Analytic View CSV MDX / OLE DB for OLAP Organized, Enhanced &Optimized Simple SQL &MDX Your Applications Your Data

  6. Analytic Views Something for Everyone For the data warehouse architect and developer Easily extend star schema with aggregate data and calculations Performance optimization For the application developer Simplifies metadata management and SQL generation Easily build applications in Oracle Application Express For the business user Built-in, browser-based data visualization via APEX application Excel Pivot Table interface

  7. Analytic Views • How would you build this application? • Analysis of health insurance coverage rates in the United States • Coverage rates by time, counties and states • Geographic comparisons • Measure improvement over time • Interactive data visualization tools for end users Health Insurance Coverage Rates by State, 2014

  8. Analytic Views • This application can be built with 5 SQL statements • Create 2 hierarchies (4 SQL statements) • Create 1 analytic view (1 SQL statement) • Is instantly accessible via APEX based application • Is all in the Database Simple SQL Analytic View Data Tables, Views, etc.

  9. Analytic Views Simple SQL SELECTtime_hier.member_nameAS TIME, geog_hier.member_name AS GEOGRAPHY, pct_insured FROM insured_avHIERARCHIES(time_hier,geog_hier) WHERE time_hier.level_name= 'YEAR' AND geog_hier.level_name= 'STATE') ORDER BY time_hier.hier_order, geog_hier.hier_order; Fact data is selected from analytic views using SQL Analytic views are views on top of a star schema. No storage structures

  10. Analytic Views Simple SQL SELECTtime_hier.member_nameAS TIME, geog_hier.member_name AS GEOGRAPHY, pct_insured FROM insured_avHIERARCHIES(time_hier,geog_hier) WHERE time_hier.level_name= 'YEAR' AND geog_hier.level_name= 'STATE' ORDER BY time_hier.hier_order, geog_hier.hier_order; The HIERARCHIES clause specifies the dimensions and hierarchies for this query No JOIN or GROUP BY clauses in analytic view queries

  11. Analytic Views Simple SQL SELECTtime_hier.member_nameAS TIME, geog_hier.member_name AS GEOGRAPHY, pct_insured FROM insured_av HIERARCHIES(time_hier,geog_hier) WHERE time_hier.level_name= 'YEAR' AND geog_hier.level_name= 'STATE' ORDER BY time_hier.hier_order, geog_hier.hier_order; Standardized columns such as ‘member_name’ are selected from the hierarchies Standardized columns such as ‘member_name’ are selected from the hierarchies

  12. Analytic Views Simple SQL SELECTtime_hier.member_nameAS TIME, geog_hier.member_name AS GEOGRAPHY, pct_insured FROM insured_av HIERARCHIES(time_hier,geog_hier) WHERE time_hier.level_name= 'YEAR' AND geog_hier.level_name= 'STATE' ORDER BY time_hier.hier_order, geog_hier.hier_order; Levels of aggregation are specified in the WHERE clause When filtering on the level ‘State’ for the time hierarchy, the member named will include California, New York, etc

  13. Analytic Views Simple SQL SELECTtime_hier.member_nameAS TIME, geog_hier.member_name AS GEOGRAPHY, pct_insured FROM insured_av HIERARCHIES(time_hier,geog_hier) WHERE time_hier.level_name= 'YEAR' AND geog_hier.level_name= 'COUNTY' ORDER BY time_hier.hier_order, geog_hier.hier_order; To drill, just update the WHERE clause. Everything else remains the same. The calculations automatically use new hierarchy levels.

  14. Analytic Views Simple SQL SELECTtime_hier.member_nameAS TIME, geog_hier.member_name AS GEOGRAPHY, pct_insured_diff_us_avg FROM insured_av HIERARCHIES(time_hier,geog_hier) WHERE time_hier.level_name= 'YEAR' AND geog_hier.level_name= 'COUNTY' ORDER BY time_hier.hier_order, geog_hier.hier_order; To select a calculation, just select columns Calculations are express in the analytic view so they can just be selected in the query

  15. Analytic Views Embedded Calculations Easily create new measures Simplified syntax based on business model Includes dimensional and hierarchical functions Add Percent Uninsured Difference from US Average with a single line of code SHARE_OF(pct_uninsuredHIERARCHY geog_hier MEMBER country ['USA']) – 1)

  16. Analytic Views Embedded Calculations Add time series calculations with a single line of code LAG_DIFF_PERCENT(pct_insured) OVER (HIERARCHY time_hier OFFSET 1ACROSS ANCESTOR AT LEVEL year)

  17. Analytic Views Descriptive Metadata Descriptive metadata available in data dictionary Descriptive names and descriptions Translatable Measure formatting User/application extensible

  18. “Standard” and Analytic Views

  19. Learn More at LiveSQL.Oracle.com

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