Analytic Views: Einsatzgebiete im Data Warehouse. Dani Schnider, Trivadis AG DOAG Konferenz, 21. November 2017

Size: px
Start display at page:

Download "Analytic Views: Einsatzgebiete im Data Warehouse. Dani Schnider, Trivadis AG DOAG Konferenz, 21. November 2017"

Transcription

1 Analytic Views: Einsatzgebiete im Data Warehouse Dani Schnider, Trivadis AG DOAG Konferenz, 21. November DOAG2017

2 Unser Unternehmen. Trivadis ist führend bei der IT-Beratung, der Systemintegration, dem Solution Engineering und der Erbringung von IT-Services mit Fokussierung auf - und -Technologien in der Schweiz, Deutschland, Österreich und Dänemark. Trivadis erbringt ihre Leistungen aus den strategischen Geschäftsfeldern: B E T R I E B Trivadis Services übernimmt den korrespondierenden Betrieb Ihrer IT Systeme

3 Mit über 600 IT- und Fachexperten bei Ihnen vor Ort. KOPENHAGEN HAMBURG 14 Trivadis Niederlassungen mit über 600 Mitarbeitenden. Über 200 Service Level Agreements. Mehr als 4'000 Trainingsteilnehmer. DÜSSELDORF Forschungs- und Entwicklungsbudget: CHF 5.0 Mio. / EUR 4.0 Mio. FRANKFURT Finanziell unabhängig und nachhaltig profitabel. BASEL FREIBURG BRUGG ZÜRICH STUTTGART MÜNCHEN WIEN Erfahrung aus mehr als 1'900 Projekten pro Jahr bei über 800 Kunden. GENF BERN LAUSANNE

4 Dani Schnider Working for Trivadis in Glattbrugg/Zurich Senior Principal Consultant Data Warehouse Lead Architect Trainer of several Courses Co-Author of the books Data Warehousing mit Oracle Data Warehouse Blueprints Certified Data Vault Data danischnider.wordpress.com

5 What are Analytic Views?

6 Overview Attribute Dimensions Hierarchies Dim Dim Analytic View Facts Dim Dim

7 Dimensions and Hierarchies

8 Attribute Dimension Data source: Dimension table (for star schemas) View on multiple dimension tables (for snowflake schemas) Member Attributes (columns of a dimension table or view) Caption and Description Hierarchy levels (incl. implicit level ALL ) Level Key Sort Order within hierarchy level Caption and Description Dimension type (STANDARD or TIME)

9 Attribute Dimension Example CREATE OR REPLACE ATTRIBUTE DIMENSION sh_products_attr_dim USING sh.products ATTRIBUTES ( prod_id CLASSIFICATION caption VALUE 'Product' CLASSIFICATION description VALUE 'Product', prod_name CLASSIFICATION caption VALUE 'Product' CLASSIFICATION description VALUE 'Product', prod_subcategory CLASSIFICATION caption VALUE 'Subcategory' CLASSIFICATION description VALUE 'Subcategory', prod_category CLASSIFICATION caption VALUE 'Category' CLASSIFICATION description VALUE 'Category' ) LEVEL PRODUCT CLASSIFICATION caption VALUE 'Product' CLASSIFICATION description VALUE 'Product' KEY prod_id MEMBER NAME prod_name MEMBER CAPTION prod_name MEMBER DESCRIPTION prod_name ORDER BY prod_name DETERMINES (prod_subcategory)

10 Hierarchy Data source: Attribute Dimension Hierarchical Ordering of Levels Parent-child relationships between levels of an Attribute Dimension Aggregation Rows A row for each member of each level of the hierarchy Can be used in SELECT statements Multiple Hierarchies can be defined for one Attribute Dimension { } { } { } { } { } { } { }

11 Hierarchy Example CREATE OR REPLACE HIERARCHY sh_products_hier CLASSIFICATION caption VALUE 'Products' CLASSIFICATION description VALUE 'Products' USING sh_products_attr_dim (product CHILD OF subcategory CHILD OF category) CREATE OR REPLACE HIERARCHY sh_times_calendar_hier CLASSIFICATION caption VALUE 'Calendar Year' CLASSIFICATION description VALUE 'Calendar Year' USING sh_times_attr_dim (day CHILD OF calendar_month CHILD OF calendar_quarter CHILD OF calendar_year) CREATE OR REPLACE HIERARCHY sh_times_fiscal_hier CLASSIFICATION caption VALUE 'Fiscal Year' CLASSIFICATION description VALUE 'Fiscal Year' USING sh_times_attr_dim (day CHILD OF fiscal_month CHILD OF fiscal_quarter CHILD OF fiscal_year)

12 Analytic View Data source: Fact table of a star or snowflake schema References to Attribute Dimensions Key of fact table that references the dimension Hierarchies used in the dimension Base Measures Columns of the fact table Calculated Measures Expressions on base measures

13 Analytic View Example (1) CREATE OR REPLACE ANALYTIC VIEW sh_sales_history_av USING sh.sales DIMENSION BY ( sh_times_attr_dim KEY time_id REFERENCES time_id HIERARCHIES (sh_times_calendar_hier DEFAULT, sh_times_fiscal_hier), sh_products_attr_dim KEY prod_id REFERENCES prod_id HIERARCHIES (sh_products_hier DEFAULT), sh_customers_attr_dim KEY cust_id REFERENCES cust_id HIERARCHIES (sh_customers_hier DEFAULT), sh_channels_attr_dim KEY channel_id REFERENCES channel_id HIERARCHIES (sh_channels_hier DEFAULT), sh_promotions_attr_dim KEY promo_id REFERENCES promo_id HIERARCHIES (sh_promotions_hier DEFAULT) ) MEASURES ( amount_sold FACT amount_sold, quantity_sold FACT quantity_sold )

14 Analytic View Example (2) CREATE OR REPLACE ANALYTIC VIEW sh_sales_history_av USING sh.sales DIMENSION BY (...) MEASURES ( -- Base Measures amount_sold FACT amount_sold, quantity_sold FACT quantity_sold, -- Calculated Measures amt_sold_shr_parent_prod AS (SHARE_OF(amount_sold HIERARCHY sh_products_hier PARENT)), sales_cal_ytd AS (SUM(amount_sold) OVER (HIERARCHY sh_times_calendar_hier BETWEEN UNBOUNDED PRECEDING AND CURRENT MEMBER WITHIN ANCESTOR AT LEVEL calendar_year)), sales_cal_year_ago AS (LAG(amount_sold) OVER (HIERARCHY sh_times_calendar_hier OFFSET 1 ACROSS ANCESTOR AT LEVEL calendar_year)) ) DEFAULT MEASURE amount_sold

15 Demo 1 a) Creating Attribute Dimensions b) Creating Hierarchies c) Creating Analytic Views

16 Typical Use Cases

17 SQL Queries in Star Schema Dim Dim SQL Query Facts SQL Query Dim Dim

18 SQL Queries in Star Schema Classical: Joins on Star Schema With Analytic View: SELECT d1,d2,d3, SUM(f1), SUM(f2) FROM fact f JOIN dim1 d1 ON ( ) JOIN dim2 d2 ON ( ) JOIN dim3 d3 ON ( ) WHERE (filter on dim1) AND (filter on dim2) GROUP BY d1,d2,d3 ORDER BY d1,d2,d3 SELECT h1,h2,h3, f1, f2 FROM analytic_view HIERARCHIES (h1,h2,h3) WHERE (filter on hierarchy1) AND (filter on hierarchy2) ORDER BY h1,h2,h

19 Query on Analytic View Example SELECT sh_times_calendar_hier.member_name AS calendar_hier, RPAD(' ', sh_products_hier.depth * 2) sh_products_hier.member_name AS products_hier, amount_sold, quantity_sold FROM sh_sales_history_av HIERARCHIES ( sh_times_calendar_hier, sh_products_hier) WHERE sh_times_calendar_hier.level_name = 'CALENDAR_YEAR' AND sh_products_hier.prod_category = 'Electronics' ORDER BY sh_times_calendar_hier.hier_order, sh_products_hier.hier_order, sh_customers_hier.hier_order

20 Query on Analytic View Result CALENDAR_HIER PRODUCTS_HIER AMOUNT_SOLD QUANTITY_SOLD Electronics Game Consoles Y Box Home Audio Minitower Speaker Home Theatre Package with DVD-Audio/Video Play Y Box Accessories Extension Cable Xtend Memory Y Box Games Adventures with Numbers Endurance Racing Electronics Game Consoles Y Box Fly Fishing Martial Arts Champions Smash up Boxing rows selected

21 Analytic Views and BI Tools Example OBIEE Metadata Layer is part of BI Tool: OBIEE Business Model and Mapping SAP BusinessObjects Universe IBM Cognos Framework Manager

22 Analytic Views and BI Tools Example Tableau

23 Analytic Views and BI Tools For BI tools with metadata layer (e.g. OBIEE): No benefits with Analytic Views Import functionality would be useful For BI tools without metadata layer (e.g. Tableau, QlikView): Metadata definition in database Simplification of user queries ev. Views on top of Analytic Views required

24 Analytic Views and ETL Analytic View can be Source for ETL Job Source should be Star Schema Physical (tables) or Virtual (views) Useful for Complex Calculations of Derived Measures Exports to Flat Structures (e.g. Standard Reports)

25 Analytic Views and ETL Dim Dim Facts Analytic View Report Table Dim Dim

26 Demo 2 a) Queries on Hierarchies b) Queries on Analytic Views c) A View behind the Scenes

27 Conclusion

28 Conclusion: Analytic Views are A Powerful Extension of Oracle SQL Very flexible for Analytic Queries on Star Schemas Useful for Ad-hoc Queries in SQL Not (yet) supported by any BI Tools Not a Replacement of a Star Schema

29 Oracle Documentation Oracle Database 12c Release 2, Data Warehousing Guide 24 Overview of Analytic Views 25 Attribute Dimension and Hierarchy Objects 26 Analytic View Objects Oracle Database 12c Release 2, SQL Language Reference CREATE ANALYTIC VIEW Calculated Measures Expressions Oracle Live SQL Creating an Analytic View for the Sales History (SH) Sample Schema Querying Analytic Views

30 Additional Information Attribute Dimensions and Hierarchies in Oracle 12.2 Analytic Views: Powerful Oracle 12.2 Feature for Business Intelligence Analytic Views: A Performance Deep Dive Analysis danischnider.wordpress.com

31 DOAG 2017 #opencompany Stand: 3. Stock, direkt an der Rolltreppe Wir teilen unser Knowhow! Einfach vorbei kommen, Live-Präsentationen und Dokumentenarchiv T-Shirts, Gewinnspiel und mehr Wir freuen uns wenn Sie vorbei schauen

Analytic Views: Use Cases in Data Warehouse. Dani Schnider, Trivadis AG DOAG Conference, 21 November 2017

Analytic Views: Use Cases in Data Warehouse. Dani Schnider, Trivadis AG DOAG Conference, 21 November 2017 Analytic Views: Use Cases in Data Warehouse Dani Schnider, Trivadis AG DOAG Conference, 21 November 2017 @dani_schnider DOAG2017 Our company. Trivadis is a market leader in IT consulting, system integration,

More information

Partitionierungsstrategien für Data Vault. Dani Schnider, Trivadis AG DOAG Konferenz, 23. November 2017

Partitionierungsstrategien für Data Vault. Dani Schnider, Trivadis AG DOAG Konferenz, 23. November 2017 Partitionierungsstrategien für Data Vault Dani Schnider, Trivadis AG DOAG Konferenz, 23. November 2017 @dani_schnider DOAG2017 Unser Unternehmen. Trivadis ist führend bei der IT-Beratung, der Systemintegration,

More information

Data Vault Partitioning Strategies. Dani Schnider, Trivadis AG DOAG Conference, 23 November 2017

Data Vault Partitioning Strategies. Dani Schnider, Trivadis AG DOAG Conference, 23 November 2017 Data Vault Partitioning Strategies Dani Schnider, Trivadis AG DOAG Conference, 23 November 2017 @dani_schnider DOAG2017 Our company. Trivadis is a market leader in IT consulting, system integration, solution

More information

1 25/07/2017 Big-Data- and Data-Science-Day 2017

1 25/07/2017 Big-Data- and Data-Science-Day 2017 1 25/07/2017 How to enable smooth Business on Big Data considering Governance - Hochschule der Medien Stuttgart - Ralf Leipner - Principal Consultant - BASLE BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG

More information

Exadata with In-Memory Option the best of all?!?

Exadata with In-Memory Option the best of all?!? Exadata with In-Memory Option the best of all?!? Konrad HÄFELI Senior Solution Manager Infrastructure Engineering BASEL BERN BRUGG LAUSANNE ZUERICH DUESSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MUNICH

More information

Welcome. Oracle SOA Suite meets Java The best of both worlds. Guido Schmutz DOAG Konferenz 2013 Nürnberg,

Welcome. Oracle SOA Suite meets Java The best of both worlds. Guido Schmutz DOAG Konferenz 2013 Nürnberg, Welcome Oracle SOA Suite meets Java The best of both worlds Guido Schmutz DOAG Konferenz 2013 Nürnberg, BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MÜNCHEN STUTTGART WIEN

More information

Exadata Resource Management. teile und herrsche!

Exadata Resource Management. teile und herrsche! Exadata Resource Management Konrad HÄFELI Senior Solution Manager Infrastructure Engineering teile und herrsche! BASEL BERN BRUGG LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MÜNCHEN

More information

Oracle In-Memory & Data Warehouse: The Perfect Combination?

Oracle In-Memory & Data Warehouse: The Perfect Combination? : The Perfect Combination? UKOUG Tech17, 6 December 2017 Dani Schnider, Trivadis AG @dani_schnider danischnider.wordpress.com BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN

More information

WebLogic JMS System Best Practices

WebLogic JMS System Best Practices WebLogic JMS System Best Practices Daniel Joray BASEL BERN BRUGG LAUSANNE ZUERICH DUESSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MUNICH STUTTGART VIENNA 1 View > Header and footer Date Unser Unternehmen

More information

Sonnenstrahlen am Wolkenhimmel Oracle in der Infrastruktur Cloud

Sonnenstrahlen am Wolkenhimmel Oracle in der Infrastruktur Cloud Sonnenstrahlen am Wolkenhimmel Oracle in der Infrastruktur Cloud Konrad HÄFELI Senior Solution Manager Infrastructure Engineering BASEL BERN BRUGG LAUSANNE ZUERICH DUESSELDORF FRANKFURT A.M. FREIBURG I.BR.

More information

Die Wundertüte DBMS_STATS: Überraschungen in der Praxis

Die Wundertüte DBMS_STATS: Überraschungen in der Praxis Die Wundertüte DBMS_STATS: Überraschungen in der Praxis, 14. Mai 2018 Dani Schnider, Trivadis AG @dani_schnider danischnider.wordpress.com BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA

More information

Pitfalls & Surprises with DBMS_STATS: How to Solve Them

Pitfalls & Surprises with DBMS_STATS: How to Solve Them Pitfalls & Surprises with DBMS_STATS: How to Solve Them Dani Schnider, Trivadis AG @dani_schnider danischnider.wordpress.com BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN

More information

GoldenGate. How to start such a project? Mathias Zarick Nuremberg, Nov. 17 th 2015

GoldenGate. How to start such a project? Mathias Zarick Nuremberg, Nov. 17 th 2015 How to start such a project? Mathias Zarick Nuremberg, Nov. 17 th 2015 BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH Introduction

More information

Continuous Integration im Umfeld der Oracle SOA Suite 11g

Continuous Integration im Umfeld der Oracle SOA Suite 11g Continuous Integration im Umfeld der Oracle SOA Suite 11g DOAG Konferenz 2011 Markus Heinisch Markus Zehnder Trivadis GmbH Nov. 2011, Nürnberg BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG

More information

Empfehlungen vom BigData Admin

Empfehlungen vom BigData Admin Empfehlungen vom BigData Admin an den Oracle DBA Florian Feicht, Alexander Hofstetter @FlorianFeicht @lxdba doag2017 Our company. Trivadis is a market leader in IT consulting, system integration, solution

More information

REALTIME WEB APPLICATIONS WITH ORACLE APEX

REALTIME WEB APPLICATIONS WITH ORACLE APEX REALTIME WEB APPLICATIONS WITH ORACLE APEX DOAG Conference 2012 Johannes Mangold Senior Consultant, Trivadis AG BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MÜNCHEN STUTTGART

More information

Query Optimizer MySQL vs. PostgreSQL

Query Optimizer MySQL vs. PostgreSQL Percona Live, Frankfurt (DE), 7 November 2018 Christian Antognini @ChrisAntognini antognini.ch/blog BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART

More information

Oracle Database New Performance Features

Oracle Database New Performance Features Oracle Database 12.1.0.2 New Performance Features DOAG 2014, Nürnberg (DE) Christian Antognini BASEL BERN BRUGG LAUSANNE ZUERICH DUESSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MUNICH STUTTGART VIENNA

More information

Bloom Filters DOAG Webinar, 12 August 2016 Christian Antognini Senior Principal Consultant

Bloom Filters DOAG Webinar, 12 August 2016 Christian Antognini Senior Principal Consultant DOAG Webinar, 12 August 2016 Christian Antognini Senior Principal Consultant BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH

More information

Service discovery in Kubernetes with Fabric8

Service discovery in Kubernetes with Fabric8 Service discovery in Kubernetes with Fabric8 Andy Moncsek Senior Consultant Andy.Moncsek@trivadis.com Twitter: @AndyAHCP BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENF HAMBURG KOPENHAGEN

More information

Best Practices for Testing SOA Suite 11g based systems

Best Practices for Testing SOA Suite 11g based systems Best Practices for Testing SOA Suite 11g based systems ODTUG 2010 Guido Schmutz, Technology Manager / Partner Trivadis AG 29.06.2010, Washington Basel Baden Bern Lausanne Zürich Düsseldorf Frankfurt/M.

More information

Query Optimizer MySQL vs. PostgreSQL

Query Optimizer MySQL vs. PostgreSQL Percona Live, Santa Clara (USA), 24 April 2018 Christian Antognini @ChrisAntognini antognini.ch/blog BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH

More information

Upload, Model, Analyze, and Report

Upload, Model, Analyze, and Report May / June 2016 Upload, Model, Analyze, and Report by Mark Rittman Quickly load information to Oracle Business Intelligence Cloud Service and share the reporting with your coworkers. Oracle Business Intelligence

More information

Exploring Oracle Database 11g/12c Partitioning New Features and Best Practices. Ami Aharonovich Oracle ACE & OCP

Exploring Oracle Database 11g/12c Partitioning New Features and Best Practices. Ami Aharonovich Oracle ACE & OCP Exploring Oracle Database 11g/12c Partitioning New Features and Best Practices Ami Aharonovich Oracle ACE & OCP Ami@DBAces.com About Me Oracle ACE Oracle Certified Professional DBA (OCP) Founder and CEO,

More information

Scripting OBIEE Is UDML and XML all you need?

Scripting OBIEE Is UDML and XML all you need? Scripting OBIEE Is UDML and XML all you need? Andreas Nobbmann Consultant Business Intelligence Andreas.Nobbmann@trivadis.com Brighton, May 14th, 2009 Basel Baden Bern Lausanne Zürich Düsseldorf Frankfurt/M.

More information

Oracle 12.2 Analytic Views:

Oracle 12.2 Analytic Views: Oracle 12.2 Analytic Views: Worth A Look Karen Cannell kcannell@thtechnology.com TH Technology About Me Mechanical/SW Engineer - Analyzed, designed, developed, converted, upgraded, enhanced legacy & database

More information

Cognos also provides you an option to export the report in XML or PDF format or you can view the reports in XML format.

Cognos also provides you an option to export the report in XML or PDF format or you can view the reports in XML format. About the Tutorial IBM Cognos Business intelligence is a web based reporting and analytic tool. It is used to perform data aggregation and create user friendly detailed reports. IBM Cognos provides a wide

More information

Appendix B: Table Descriptions

Appendix B: Table Descriptions Appendix B: Table Descriptions Schema Descriptions Overall Description Oracle Database sample schemas portray a sample company that operates worldwide to fill orders for several different products. The

More information

Business Analytics in the Oracle 12.2 Database: Analytic Views. Event: BIWA 2017 Presenter: Dan Vlamis and Cathye Pendley Date: January 31, 2017

Business Analytics in the Oracle 12.2 Database: Analytic Views. Event: BIWA 2017 Presenter: Dan Vlamis and Cathye Pendley Date: January 31, 2017 Business Analytics in the Oracle 12.2 Database: Analytic Views Event: BIWA 2017 Presenter: Dan Vlamis and Cathye Pendley Date: January 31, 2017 Vlamis Software Solutions Vlamis Software founded in 1992

More information

Exadata Database Machine Resource Management teile und herrsche!

Exadata Database Machine Resource Management teile und herrsche! Exadata Database Machine Resource Management teile und herrsche! DOAG Conference 2011 Konrad Häfeli Senior Technology Manager Trivadis AG BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR.

More information

Cloud Acceleration. Performance comparison of Cloud vendors. Tobias Deml DOAG2017

Cloud Acceleration. Performance comparison of Cloud vendors. Tobias Deml DOAG2017 Performance comparison of Cloud vendors Tobias Deml Consultant @TobiasDemlDBA DOAG2017 About Consultant, Trivadis GmbH, Munich Since more than 9 years working in Oracle environment Focus areas Cloud Computing

More information

Call: SAS BI Course Content:35-40hours

Call: SAS BI Course Content:35-40hours SAS BI Course Content:35-40hours Course Outline SAS Data Integration Studio 4.2 Introduction * to SAS DIS Studio Features of SAS DIS Studio Tasks performed by SAS DIS Studio Navigation to SAS DIS Studio

More information

How Autonomous is the Oracle Autonomous Data Warehouse?

How Autonomous is the Oracle Autonomous Data Warehouse? How Autonomous is the Oracle Autonomous Data Warehouse? Christian Antognini / Dani Schnider @chrisantognini @dani_schnider antognini.ch/blog danischnider.wordpress.com BASLE BERN BRUGG DÜSSELDORF FRANKFURT

More information

Create Cube From Star Schema Grouping Framework Manager

Create Cube From Star Schema Grouping Framework Manager Create Cube From Star Schema Grouping Framework Manager Create star schema groupings to provide authors with logical groupings of query Connect to an OLAP data source (cube) in a Framework Manager project

More information

Designing for Performance: Database Related Worst Practices ITOUG Tech Day, 11 November 2016, Milano (I) Christian Antognini

Designing for Performance: Database Related Worst Practices ITOUG Tech Day, 11 November 2016, Milano (I) Christian Antognini Designing for Performance: Database Related Worst Practices ITOUG Tech Day, 11 November 2016, Milano (I) Christian Antognini BASLE BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN

More information

Edition-Based Redefinition

Edition-Based Redefinition Edition-Based Redefinition Janina Patolla Trivadis AG, Basel Basel Baden Bern Brugg Lausanne Zurich Düsseldorf Frankfurt/M. Freiburg i. Br. Hamburg Munich Stuttgart Vienna Introduction Upgrading critical

More information

Oracle Database 11g: Data Warehousing Fundamentals

Oracle Database 11g: Data Warehousing Fundamentals Oracle Database 11g: Data Warehousing Fundamentals Duration: 3 Days What you will learn This Oracle Database 11g: Data Warehousing Fundamentals training will teach you about the basic concepts of a data

More information

Aggregating Knowledge in a Data Warehouse and Multidimensional Analysis

Aggregating Knowledge in a Data Warehouse and Multidimensional Analysis Aggregating Knowledge in a Data Warehouse and Multidimensional Analysis Rafal Lukawiecki Strategic Consultant, Project Botticelli Ltd rafal@projectbotticelli.com Objectives Explain the basics of: 1. Data

More information

CRI Event-Driven BI. Peter Welkenbach Principal Consultant Trivadis GmbH. Düsseldorf,

CRI Event-Driven BI. Peter Welkenbach Principal Consultant Trivadis GmbH. Düsseldorf, CRI Event-Driven BI Peter Welkenbach Principal Consultant Trivadis GmbH Düsseldorf, 11.03.2008 Basel Baden Bern Lausanne Zurich Düsseldorf Frankfurt/M. Freiburg i. Br. Hamburg Munich Stuttgart Vienna The

More information

Analytic views in Oracle 12.2

Analytic views in Oracle 12.2 The virtual cube Kim Berg Hansen Senior Consultant BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENF HAMBURG KOPENHAGEN LAUSANNE MÜNCHEN STUTTGART WIEN ZÜRICH About me Danish geek SQL & PL/SQL

More information

WELCOME. Unterstützung von Tuning- Maßnahmen mit Hilfe von Capacity Management. DOAG SIG Database

WELCOME. Unterstützung von Tuning- Maßnahmen mit Hilfe von Capacity Management. DOAG SIG Database WELCOME Unterstützung von Tuning- Maßnahmen mit Hilfe von Capacity Management DOAG SIG Database 28.02.2013 Robert Kruzynski Principal Consultant Partner Trivadis GmbH München BASEL BERN LAUSANNE ZÜRICH

More information

SSAS 2008 Tutorial: Understanding Analysis Services

SSAS 2008 Tutorial: Understanding Analysis Services Departamento de Engenharia Informática Sistemas de Informação e Bases de Dados Online Analytical Processing (OLAP) This tutorial has been copied from: https://www.accelebrate.com/sql_training/ssas_2008_tutorial.htm

More information

Microservices with Kafka Ecosystem. Guido Schmutz

Microservices with Kafka Ecosystem. Guido Schmutz Microservices with Kafka Ecosystem Guido Schmutz @gschmutz doag2017 Guido Schmutz Working at Trivadis for more than 20 years Oracle ACE Director for Fusion Middleware and SOA Consultant, Trainer Software

More information

Integration of Oracle BI EE and Oracle Analytic Workspaces

Integration of Oracle BI EE and Oracle Analytic Workspaces Integration of Oracle BI EE and Oracle Analytic Workspaces Mark Thompson Vlamis Software Solutions Session 208 Speaker Information Mark Thompson, Senior Consultant, Vlamis Software Solutions 23 years designing

More information

Top 24 Obiee Interview Questions & Answers

Top 24 Obiee Interview Questions & Answers Top 24 Obiee Interview Questions & Answers 1) Mention what is Obiee? Obiee stands for Oracle Business Intelligence Enterprise Edition (OBIEE). It is a business intelligence system for the enterprise that

More information

Identifying Performance Problems in a Multitenant Environment

Identifying Performance Problems in a Multitenant Environment Identifying Performance Problems in a Multitenant Environment Christian Antognini @ChrisAntognini antognini.ch/blog BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE

More information

ETL TESTING TRAINING

ETL TESTING TRAINING ETL TESTING TRAINING Retrieving Data using the SQL SELECT Statement Capabilities of the SELECT statement Arithmetic expressions and NULL values in the SELECT statement Column aliases Use of concatenation

More information

Decision Guidance. Data Vault in Data Warehousing

Decision Guidance. Data Vault in Data Warehousing Decision Guidance Data Vault in Data Warehousing DATA VAULT IN DATA WAREHOUSING Today s business environment requires data models, which are resilient to change and enable the integration of multiple data

More information

Application Containers an Introduction

Application Containers an Introduction Application Containers an Introduction Oracle Database 12c Release 2 Multitenancy for Applications Markus Flechtner @markusdba doag2017 Our company. Trivadis is a market leader in IT consulting, system

More information

Integration of Oracle VM 3 in Enterprise Manager 12c

Integration of Oracle VM 3 in Enterprise Manager 12c Integration of Oracle VM 3 in Enterprise Manager 12c DOAG SIG Infrastruktur Martin Bracher Senior Consultant Trivadis AG 8. März 2012 BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR.

More information

Apache Tamaya Configuring your Containers...

Apache Tamaya Configuring your Containers... Apache Tamaya Configuring your Containers... BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENF HAMBURG KOPENHAGEN LAUSANNE MÜNCHEN STUTTGART WIEN ZÜRICH About Me Anatole Tresch Principal Consultant,

More information

SAP CERTIFIED APPLICATION ASSOCIATE - SAP HANA 2.0 (SPS01)

SAP CERTIFIED APPLICATION ASSOCIATE - SAP HANA 2.0 (SPS01) SAP EDUCATION SAMPLE QUESTIONS: C_HANAIMP_13 SAP CERTIFIED APPLICATION ASSOCIATE - SAP HANA 2.0 (SPS01) Disclaimer: These sample questions are for self-evaluation purposes only and do not appear on the

More information

CON Apache Kafka

CON Apache Kafka CON6156 - Apache Kafka Scalable Message Processing and more! Guido Schmutz 2.10.2017 @gschmutz guidoschmutz.wordpress.com BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENF HAMBURG KOPENHAGEN

More information

Key Data Warehousing Features in Oracle10g: A Comparative Performance Analysis. An Oracle White Paper April 2005

Key Data Warehousing Features in Oracle10g: A Comparative Performance Analysis. An Oracle White Paper April 2005 Key Data Warehousing Features in Oracle10g: A Comparative Performance Analysis An Oracle White Paper April 2005 Key Data Warehousing Features in Oracle10g: A Comparative Performance Analysis Executive

More information

Oracle Audit in a Nutshell - Database Audit but how?

Oracle Audit in a Nutshell - Database Audit but how? Oracle Audit in a Nutshell - Database Audit but how? DOAG + SOUG Security-Lounge Stefan Oehrli Senior Consultant Discipline Manager Trivadis AG Basel 24. April 2012 BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF

More information

Proceedings of the IE 2014 International Conference AGILE DATA MODELS

Proceedings of the IE 2014 International Conference  AGILE DATA MODELS AGILE DATA MODELS Mihaela MUNTEAN Academy of Economic Studies, Bucharest mun61mih@yahoo.co.uk, Mihaela.Muntean@ie.ase.ro Abstract. In last years, one of the most popular subjects related to the field of

More information

Data Warehouse and Data Mining

Data Warehouse and Data Mining Data Warehouse and Data Mining Lecture No. 04-06 Data Warehouse Architecture Naeem Ahmed Email: naeemmahoto@gmail.com Department of Software Engineering Mehran Univeristy of Engineering and Technology

More information

Adaptive

Adaptive Christian Antognini @ChrisAntognini antognini.ch/blog BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH @ChrisAntognini Senior

More information

PrepAwayExam. High-efficient Exam Materials are the best high pass-rate Exam Dumps

PrepAwayExam.   High-efficient Exam Materials are the best high pass-rate Exam Dumps PrepAwayExam http://www.prepawayexam.com/ High-efficient Exam Materials are the best high pass-rate Exam Dumps Exam : C_HANAIMP142 Title : SAP Certified Application Associate - SAP HANA (Edition 2014)

More information

Techno Expert Solutions An institute for specialized studies!

Techno Expert Solutions An institute for specialized studies! Getting Started Course Content of IBM Cognos Data Manger Identify the purpose of IBM Cognos Data Manager Define data warehousing and its key underlying concepts Identify how Data Manager creates data warehouses

More information

Database Sharding with Oracle RDBMS

Database Sharding with Oracle RDBMS Database Sharding with Oracle RDBMS First Impressions Robert Bialek Principal Consultant BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA

More information

Oracle Database Failover Cluster with Grid Infrastructure 11g Release 2

Oracle Database Failover Cluster with Grid Infrastructure 11g Release 2 Oracle Database Failover Cluster with Grid Infrastructure 11g Release 2 DOAG Conference 2011 Robert Bialek Principal Consultant Trivadis GmbH BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG

More information

CHERRY GSP TEAM

CHERRY GSP TEAM CHERRY GSP TEAM 2017 1 THE COMPANY CHERRY GSP TEAM 2017 2 COMPANY THE CHERRY HISTORY Walter L. Cherry, founder of CHERRY Corporation. In 1953 he laid the foundation for a classic American success story,

More information

Backup Methods from Practice

Backup Methods from Practice Backup Methods from Practice Optimized and Intelligent Roland Stirnimann @rstirnimann_ch BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA

More information

Oracle Database 18c New Performance Features

Oracle Database 18c New Performance Features Oracle Database 18c New Performance Features Christian Antognini @ChrisAntognini antognini.ch/blog BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART

More information

Oracle BI 11g R1: Build Repositories

Oracle BI 11g R1: Build Repositories Oracle University Contact Us: 02 6968000 Oracle BI 11g R1: Build Repositories Duration: 5 Days What you will learn This course provides step-by-step procedures for building and verifying the three layers

More information

Big Data Infrastructure The Oracle Way. Daniel Steiger

Big Data Infrastructure The Oracle Way. Daniel Steiger Big Data Infrastructure The Oracle Way. Daniel Steiger BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA ZURICH About... Daniel Steiger

More information

InfoSphere Warehouse V9.5 Exam.

InfoSphere Warehouse V9.5 Exam. IBM 000-719 InfoSphere Warehouse V9.5 Exam TYPE: DEMO http://www.examskey.com/000-719.html Examskey IBM 000-719 exam demo product is here for you to test the quality of the product. This IBM 000-719 demo

More information

Fast Complex BI Analysis with Oracle OLAP. Oracle OpenWorld 2011

Fast Complex BI Analysis with Oracle OLAP. Oracle OpenWorld 2011 Copyright 2011, Vlamis Software Solutions, Inc. Fast Complex BI Analysis with Oracle OLAP Oracle OpenWorld 2011 Dan Vlamis Vlamis Software Solutions 816-781-2880 http://www.vlamis.com Copyright 2011, Vlamis

More information

DEEP DIVE. Leave IT Alone: The Vast Value of Self-Service. #DMRadio

DEEP DIVE. Leave IT Alone: The Vast Value of Self-Service. #DMRadio DEEP DIVE Leave IT Alone: The Vast Value of Self-Service #DMRadio Featured Speakers The Long-Standing Data Warehousing Models The Reliance on ETL Must Subside! Trust is the Cornerstone of Data-Driven

More information

Analytic Workspace Manager and Oracle OLAP 10g. An Oracle White Paper November 2004

Analytic Workspace Manager and Oracle OLAP 10g. An Oracle White Paper November 2004 Analytic Workspace Manager and Oracle OLAP 10g An Oracle White Paper November 2004 Analytic Workspace Manager and Oracle OLAP 10g Introduction... 3 Oracle Database Incorporates OLAP... 4 Oracle Business

More information

Teradata Aggregate Designer

Teradata Aggregate Designer Data Warehousing Teradata Aggregate Designer By: Sam Tawfik Product Marketing Manager Teradata Corporation Table of Contents Executive Summary 2 Introduction 3 Problem Statement 3 Implications of MOLAP

More information

IBM KM423G - IBM INFOSPHERE DATASTAGE V ADVANCED DATA PROCESSING

IBM KM423G - IBM INFOSPHERE DATASTAGE V ADVANCED DATA PROCESSING IBM KM423G - IBM INFOSPHERE DATASTAGE V11.5 - ADVANCED DATA PROCESSING Dauer: 2 Tage Durchführungsart: Präsenztraining Zielgruppe: Experienced DataStage developers seeking training in more advanced DataStage

More information

ITdumpsFree. Get free valid exam dumps and pass your exam test with confidence

ITdumpsFree.  Get free valid exam dumps and pass your exam test with confidence ITdumpsFree http://www.itdumpsfree.com Get free valid exam dumps and pass your exam test with confidence Exam : C_HANAIMP_12 Title : SAP Certified Application Associate - SAP HANA (Edition 2016 - SPS12)

More information

Oracle Hyperion Financial Management Instructor-led Live Online Training Program

Oracle Hyperion Financial Management Instructor-led Live Online Training Program 1. Introduction to Financial Management About Oracle's Enterprise Performance Management Suite Financial Management Solution Financial Consolidation, Reporting, Analysis and Product Components Financial

More information

Hyperion Interactive Reporting Reports & Dashboards Essentials

Hyperion Interactive Reporting Reports & Dashboards Essentials Oracle University Contact Us: +27 (0)11 319-4111 Hyperion Interactive Reporting 11.1.1 Reports & Dashboards Essentials Duration: 5 Days What you will learn The first part of this course focuses on two

More information

Database Rolling Upgrade with Transient Logical Standby Database DOAG Day High Availability Robert Bialek Principal Consultant

Database Rolling Upgrade with Transient Logical Standby Database DOAG Day High Availability Robert Bialek Principal Consultant Database Rolling Upgrade with Transient Logical Standby Database DOAG Day High Availability Robert Bialek Principal Consultant BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENF HAMBURG KOPENHAGEN

More information

SAS Data Integration Studio 3.3. User s Guide

SAS Data Integration Studio 3.3. User s Guide SAS Data Integration Studio 3.3 User s Guide The correct bibliographic citation for this manual is as follows: SAS Institute Inc. 2006. SAS Data Integration Studio 3.3: User s Guide. Cary, NC: SAS Institute

More information

Domain Services Clusters Centralized Management & Storage for an Oracle Cluster Environment Markus Flechtner

Domain Services Clusters Centralized Management & Storage for an Oracle Cluster Environment Markus Flechtner s Centralized Management & Storage for an Oracle Cluster Environment Markus Flechtner BASLE BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE MUNICH STUTTGART VIENNA

More information

DSS Performance in Oracle Database 10g Release 2. An Oracle White Paper July 2005

DSS Performance in Oracle Database 10g Release 2. An Oracle White Paper July 2005 DSS Performance in Oracle Database 10g Release 2 An Oracle White Paper July 2005 DSS Performance in Oracle Database 10g Release 2 Executive Overview... 3 Introduction... 3 Test Environment... 4 In Memory

More information

A Road Map for Advancing Your Career

A Road Map for Advancing Your Career CERTIFIED BUSINESS INTELLIGENCE PROFESSIONAL TDWI CERTIFICATION A Road Map for Advancing Your Career Get recognized as an industry leader. Get ahead of the competition. Advance your career with CBIP. Professionals

More information

Fast Complex BI Analysis with Oracle OLAP. NEOOUG September 16, 2011

Fast Complex BI Analysis with Oracle OLAP. NEOOUG September 16, 2011 Fast Complex BI Analysis with Oracle OLAP NEOOUG September 16, 2011 Dan Vlamis Vlamis Software Solutions 816-781-2880 http://www.vlamis.com Vlamis Software Solutions, Inc. Founded in 1992 in Kansas City,

More information

Big Data Big Mess? Ein Versuch einer Positionierung

Big Data Big Mess? Ein Versuch einer Positionierung Big Data Big Mess? Ein Versuch einer Positionierung Autor: Daniel Liebhart (Peter Welkenbach) Datum: 10. Oktober 2012 Ort: DBTA Workshop on Big Data, Cloud Data Management and NoSQL BASEL BERN LAUSANNE

More information

Data Warehouse and Data Mining

Data Warehouse and Data Mining Data Warehouse and Data Mining Lecture No. 03 Architecture of DW Naeem Ahmed Email: naeemmahoto@gmail.com Department of Software Engineering Mehran Univeristy of Engineering and Technology Jamshoro Basic

More information

COGNOS DYNAMIC CUBES: SET TO RETIRE TRANSFORMER? Update: Pros & Cons

COGNOS DYNAMIC CUBES: SET TO RETIRE TRANSFORMER? Update: Pros & Cons COGNOS DYNAMIC CUBES: SET TO RETIRE TRANSFORMER? 10.2.2 Update: Pros & Cons GoToWebinar Control Panel Submit questions here Click arrow to restore full control panel Copyright 2015 Senturus, Inc. All Rights

More information

Dallas Marks - Session 5010

Dallas Marks - Session 5010 [ Delivering Personalized and Secure Business Intelligence With the SAP BusinessObjects Business Intelligence 4.0 Information Design Tool Chicago BusinessObjects User Group (CHIBOUG) Friday, November 18,

More information

Oracle BI 12c: Build Repositories

Oracle BI 12c: Build Repositories Oracle University Contact Us: Local: 1800 103 4775 Intl: +91 80 67863102 Oracle BI 12c: Build Repositories Duration: 5 Days What you will learn This Oracle BI 12c: Build Repositories training teaches you

More information

Oracle 1Z0-515 Exam Questions & Answers

Oracle 1Z0-515 Exam Questions & Answers Oracle 1Z0-515 Exam Questions & Answers Number: 1Z0-515 Passing Score: 800 Time Limit: 120 min File Version: 38.7 http://www.gratisexam.com/ Oracle 1Z0-515 Exam Questions & Answers Exam Name: Data Warehousing

More information

Oracle Access Management

Oracle Access Management Oracle Access Management Needful things to survive Michael Mühlbeyer, Trivadis GmbH BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENF HAMBURG KOPENHAGEN LAUSANNE MÜNCHEN STUTTGART WIEN ZÜRICH

More information

MICROSOFT BUSINESS INTELLIGENCE (MSBI: SSIS, SSRS and SSAS)

MICROSOFT BUSINESS INTELLIGENCE (MSBI: SSIS, SSRS and SSAS) MICROSOFT BUSINESS INTELLIGENCE (MSBI: SSIS, SSRS and SSAS) Microsoft's Business Intelligence (MSBI) Training with in-depth Practical approach towards SQL Server Integration Services, Reporting Services

More information

Instant Data Warehousing with SAP data

Instant Data Warehousing with SAP data Instant Data Warehousing with SAP data» Extracting your SAP data to any destination environment» Fast, simple, user-friendly» 8 different SAP interface technologies» Graphical user interface no previous

More information

Application Containers an Introduction

Application Containers an Introduction Application Containers an Introduction Oracle Database 12c Release 2 Multitenancy for Applications Markus Flechtner BASLE BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE

More information

Course Contents: 1 Datastage Online Training

Course Contents: 1 Datastage Online Training IQ Online training facility offers Data stage online training by trainers who have expert knowledge in the Data stage and proven record of training hundreds of students. Our Data stage training is regarded

More information

Guide to Managing Common Metadata

Guide to Managing Common Metadata IBM InfoSphere Information Serer Version 11 Release 3 Guide to Managing Common Metadata SC19-4297-01 IBM InfoSphere Information Serer Version 11 Release 3 Guide to Managing Common Metadata SC19-4297-01

More information

Safe Harbor Statement

Safe Harbor Statement Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment

More information

Data Warehouses. Yanlei Diao. Slides Courtesy of R. Ramakrishnan and J. Gehrke

Data Warehouses. Yanlei Diao. Slides Courtesy of R. Ramakrishnan and J. Gehrke Data Warehouses Yanlei Diao Slides Courtesy of R. Ramakrishnan and J. Gehrke Introduction v In the late 80s and early 90s, companies began to use their DBMSs for complex, interactive, exploratory analysis

More information

Page 1. Oracle9i OLAP. Agenda. Mary Rehus Sales Consultant Patrick Larkin Vice President, Oracle Consulting. Oracle Corporation. Business Intelligence

Page 1. Oracle9i OLAP. Agenda. Mary Rehus Sales Consultant Patrick Larkin Vice President, Oracle Consulting. Oracle Corporation. Business Intelligence Oracle9i OLAP A Scalable Web-Base Business Intelligence Platform Mary Rehus Sales Consultant Patrick Larkin Vice President, Oracle Consulting Agenda Business Intelligence Market Oracle9i OLAP Business

More information

Logical Design A logical design is conceptual and abstract. It is not necessary to deal with the physical implementation details at this stage.

Logical Design A logical design is conceptual and abstract. It is not necessary to deal with the physical implementation details at this stage. Logical Design A logical design is conceptual and abstract. It is not necessary to deal with the physical implementation details at this stage. You need to only define the types of information specified

More information

Recovery without Backup. All Data Lost?

Recovery without Backup. All Data Lost? An Overview and Field Report Igor Romansky Peter Jensch Trivadis GmbH, Stuttgart DOAG Regio-Treffen Stuttgart, July 21th 2016 BASLE BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN

More information

Pimping up Industry Devices with Rasperry Pi, Vert.x und Java 8

Pimping up Industry Devices with Rasperry Pi, Vert.x und Java 8 Pimping up Industry Devices with Rasperry Pi, Vert.x und Java 8 Anatole Tresch Principal Consultant @atsticks BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENEVA HAMBURG COPENHAGEN LAUSANNE

More information