CS Programming OLAP
|
|
- Blaze Adams
- 7 years ago
- Views:
Transcription
1 CS Programming OLAP DANIEL LEMIRE Research Officer, NRC Adjunct Professor, UNB
2 CS Programming OLAP DANIEL LEMIRE Research Officer, NRC Adjunct Professor, UNB These slides will be made available on the web.
3 Overview Review of the industry
4 Overview Review of the industry Course presentation
5 Overview Review of the industry Course presentation Homework Assignment
6 Overview Review of the industry Course presentation Homework Assignment Motivation through example
7 Overview Review of the industry Course presentation Homework Assignment Motivation through example Definitions!!!
8 OLAP is important? Source: OLAP Report as of July 7th 2003 (was revised with lower estimates recently)
9 Historical Perspective 1970 Codd proposes relational model 1980 SQL becomes a commercial success (Oracle, IBM) 1993 Codd coined OLAP, Excel offers Pivot Tables 1997 MOLAP vs ROLAP debate 1999 SQL-99 offers some OLAP functionality
10 Industry standards Name Status Platform Proponent OLE DB In use Wintel Microsoft XML Analysis Prototypical SOAP Microsoft, Hyperion JOLAP Prototypical Java (J2EE) IBM, Oracle, Hyperion, Sun
11 Who sells OLAP Microsoft 24% Hyperion 23% Cognos 13% BO 7% MicroStrategy 5% SAP 5% Oracle 5% PwC 3% Applix 3% Comshare 2% IBM 2%
12 Course Presentation Look at print-out NOW!
13 Course Presentation Look at print-out NOW! On-line Analytical Processing
14 Course Presentation Look at print-out NOW! On-line Analytical Processing or OLAP
15 Course Presentation Look at print-out NOW! On-line Analytical Processing or OLAP Programming OLAP:
16 Course Presentation Look at print-out NOW! On-line Analytical Processing or OLAP Programming OLAP: under the hood
17 Course Presentation Look at print-out NOW! On-line Analytical Processing or OLAP Programming OLAP: under the hood Dark art of designing multidimensional database!
18 This lecture? What kinds of problems can OLAP help me solve?
19 This lecture? What kinds of problems can OLAP help me solve? Can it help me figure out which products or customers are profitable?
20 This lecture? What kinds of problems can OLAP help me solve? Can it help me figure out which products or customers are profitable? Can it help me pick better stocks?
21 Amazon CEO You are Amazon s CEO. You ve been told that cheaper items sell more. Is it true?
22 Amazon CEO You are Amazon s CEO. You ve been told that cheaper items sell more. Is it true? Used Amazon s SOAP API data cube online answer!
23 Amazon OLAP Results
24 Amazon CEO (part 2) Ah. Yes. Well, this is nice. says the CEO
25 Amazon CEO (part 2) Ah. Yes. Well, this is nice. says the CEO Maybe price doesn t impact sales for items that are highly rated?
26 Amazon OLAP Results (part 2)
27 Amazon CEO (part 3) Ok. I was wrong. Very nice. says the CEO
28 Amazon CEO (part 3) Ok. I was wrong. Very nice. says the CEO (CEO is now buying into the OLAP frame of mind.)
29 Amazon CEO (part 3) Ok. I was wrong. Very nice. says the CEO (CEO is now buying into the OLAP frame of mind.) Maybe price doesn t impact sales for items that are poorly rated?
30 Amazon OLAP Results (part 3)
31 Amazon CEO (part 4) Ok. Something different is happening with poorly rated items. says the CEO
32 Amazon CEO (part 4) Ok. Something different is happening with poorly rated items. says the CEO (CEO thinks for a second or two.)
33 Amazon CEO (part 4) Ok. Something different is happening with poorly rated items. says the CEO (CEO thinks for a second or two.) How many poorly rated items are there compared to highly rated?
34 Amazon OLAP Results (part 4)
35 Convenience? This was all computed in a few seconds using our very own web interface (HOWLER). OLAP should be sexy, responsive, and convenient.
36 Convenience? This was all computed in a few seconds using our very own web interface (HOWLER). OLAP should be sexy, responsive, and convenient. Meant for business people.
37 Howler
38 But what is OLAP exactly? Short answer: a marketing term more catchy than multidimensional database.
39 But what is OLAP exactly? Short answer: a marketing term more catchy than multidimensional database. Providing OLAP (On-Line Analytical Processing) to User-Analysts: An IT Mandate. 1993
40 But what is OLAP exactly? Short answer: a marketing term more catchy than multidimensional database. Providing OLAP (On-Line Analytical Processing) to User-Analysts: An IT Mandate
41 Some of Codd s definining conditions Multidimensional Conceptual View
42 Some of Codd s definining conditions Multidimensional Conceptual View Generic Dimensionality
43 Some of Codd s definining conditions Multidimensional Conceptual View Generic Dimensionality Unlimited Dimensions and Aggregation Levels
44 Some of Codd s definining conditions Multidimensional Conceptual View Generic Dimensionality Unlimited Dimensions and Aggregation Levels
45 Some of Codd s definining conditions Unrestricted Cross-Dimensional Operations
46 Some of Codd s definining conditions Unrestricted Cross-Dimensional Operations Consistent Reporting Performance
47 Some of Codd s definining conditions Unrestricted Cross-Dimensional Operations Consistent Reporting Performance Dynamic Sparse Matrix Hadling
48 Some of Codd s definining conditions Unrestricted Cross-Dimensional Operations Consistent Reporting Performance Dynamic Sparse Matrix Hadling
49 Other catchy names DOLAP: Database OLAP or Desktop OLAP
50 Other catchy names DOLAP: Database OLAP or Desktop OLAP MOLAP: Multidimensional OLAP
51 Other catchy names DOLAP: Database OLAP or Desktop OLAP MOLAP: Multidimensional OLAP ROLAP: Relational OLAP
52 Other catchy names DOLAP: Database OLAP or Desktop OLAP MOLAP: Multidimensional OLAP ROLAP: Relational OLAP HOLAP: Hybrid OLAP
53 Other catchy names DOLAP: Database OLAP or Desktop OLAP MOLAP: Multidimensional OLAP ROLAP: Relational OLAP HOLAP: Hybrid OLAP WOLAP: Web OLAP
54 Other catchy names DOLAP: Database OLAP or Desktop OLAP MOLAP: Multidimensional OLAP ROLAP: Relational OLAP HOLAP: Hybrid OLAP WOLAP: Web OLAP
55 Definitions Array Storage method where the elements of the array are placed sequentially in a contiguous region of storage (disk or RAM)
56 Definitions Array Storage method where the elements of the array are placed sequentially in a contiguous region of storage (disk or RAM) Index A structure used to locate values.
57 Definitions Variable A unit-bearing data type, either measured or derived.
58 Definitions Variable A unit-bearing data type, either measured or derived. Attribute Information associated with an object.
59 Definitions Variable A unit-bearing data type, either measured or derived. Attribute Information associated with an object. Dimension Collection of objects of the same type. For our purposes, Variable = Attribute.
60 Dimension versus Variable weight height John 160lbs 1.8m Maggy 125lbs 1.4m
61 Definitions To Aggregate The process of combining two or more data items into a single item.
62 Definitions To Aggregate The process of combining two or more data items into a single item. Measure A unit-bearing data type.
63 Definitions To Aggregate The process of combining two or more data items into a single item. Measure A unit-bearing data type. Cell A measure associated with one and only one member from each of multiple dimensions.
64 Definitions To Aggregate The process of combining two or more data items into a single item. Measure A unit-bearing data type. Cell A measure associated with one and only one member from each of multiple dimensions. Hypercube or Data Cube A multi-dimensional schema formed from the cross-product of a number of dimensions.
Data W a Ware r house house and and OLAP II Week 6 1
Data Warehouse and OLAP II Week 6 1 Team Homework Assignment #8 Using a data warehousing tool and a data set, play four OLAP operations (Roll up (drill up), Drill down (roll down), Slice and dice, Pivot
More informationAnwendersoftware Anwendungssoftwares a. Data-Warehouse-, Data-Mining- and OLAP-Technologies. Online Analytic Processing
Anwendungssoftwares a Data-Warehouse-, Data-Mining- and OLAP-Technologies Online Analytic Processing Online Analytic Processing OLAP Online Analytic Processing Technologies and tools that support (ad-hoc)
More informationCS2032 Data warehousing and Data Mining Unit II Page 1
UNIT II BUSINESS ANALYSIS Reporting Query tools and Applications The data warehouse is accessed using an end-user query and reporting tool from Business Objects. Business Objects provides several tools
More informationBUSINESS ANALYTICS AND DATA VISUALIZATION. ITM-761 Business Intelligence ดร. สล ล บ ญพราหมณ
1 BUSINESS ANALYTICS AND DATA VISUALIZATION ITM-761 Business Intelligence ดร. สล ล บ ญพราหมณ 2 การท าความด น น ยากและเห นผลช า แต ก จ าเป นต องท า เพราะหาไม ความช วซ งท าได ง ายจะเข ามาแทนท และจะพอกพ นข
More informationUnit -3. Learning Objective. Demand for Online analytical processing Major features and functions OLAP models and implementation considerations
Unit -3 Learning Objective Demand for Online analytical processing Major features and functions OLAP models and implementation considerations Demand of On Line Analytical Processing Need for multidimensional
More informationBussiness Intelligence and Data Warehouse. Tomas Bartos CIS 764, Kansas State University
Bussiness Intelligence and Data Warehouse Schedule Bussiness Intelligence (BI) BI tools Oracle vs. Microsoft Data warehouse History Tools Oracle vs. Others Discussion Business Intelligence (BI) Products
More informationUNIT-3 OLAP in Data Warehouse
UNIT-3 OLAP in Data Warehouse Bharati Vidyapeeth s Institute of Computer Applications and Management, New Delhi-63, by Dr.Deepali Kamthania U2.1 OLAP Demand for Online analytical processing Major features
More information14. Data Warehousing & Data Mining
14. Data Warehousing & Data Mining Data Warehousing Concepts Decision support is key for companies wanting to turn their organizational data into an information asset Data Warehouse "A subject-oriented,
More informationDATA WAREHOUSING - OLAP
http://www.tutorialspoint.com/dwh/dwh_olap.htm DATA WAREHOUSING - OLAP Copyright tutorialspoint.com Online Analytical Processing Server OLAP is based on the multidimensional data model. It allows managers,
More informationOLAP and Data Mining. Data Warehousing and End-User Access Tools. Introducing OLAP. Introducing OLAP
Data Warehousing and End-User Access Tools OLAP and Data Mining Accompanying growth in data warehouses is increasing demands for more powerful access tools providing advanced analytical capabilities. Key
More informationLearning Objectives. Definition of OLAP Data cubes OLAP operations MDX OLAP servers
OLAP Learning Objectives Definition of OLAP Data cubes OLAP operations MDX OLAP servers 2 What is OLAP? OLAP has two immediate consequences: online part requires the answers of queries to be fast, the
More informationData Warehouses & OLAP
Riadh Ben Messaoud 1. The Big Picture 2. Data Warehouse Philosophy 3. Data Warehouse Concepts 4. Warehousing Applications 5. Warehouse Schema Design 6. Business Intelligence Reporting 7. On-Line Analytical
More informationMain Memory & Near Main Memory OLAP Databases. Wo Shun Luk Professor of Computing Science Simon Fraser University
Main Memory & Near Main Memory OLAP Databases Wo Shun Luk Professor of Computing Science Simon Fraser University 1 Outline What is OLAP DB? How does it work? MOLAP, ROLAP Near Main Memory DB Partial Pre
More informationOLAP Systems and Multidimensional Expressions I
OLAP Systems and Multidimensional Expressions I Krzysztof Dembczyński Intelligent Decision Support Systems Laboratory (IDSS) Poznań University of Technology, Poland Software Development Technologies Master
More informationOLAP OLAP. Data Warehouse. OLAP Data Model: the Data Cube S e s s io n
OLAP OLAP On-Line Analytical Processing In contrast to on-line transaction processing (OLTP) Mostly ad hoc queries involving aggregation Response time rather than throughput is the main performance measure.
More informationEssbase Integration Services Release 7.1 New Features
New Features Essbase Integration Services Release 7.1 New Features Congratulations on receiving Essbase Integration Services Release 7.1. Essbase Integration Services enables you to transfer the relevant
More informationHybrid OLAP, An Introduction
Hybrid OLAP, An Introduction Richard Doherty SAS Institute European HQ Agenda Hybrid OLAP overview Building your data model Architectural decisions Metadata creation Report definition Hybrid OLAP overview
More information1. OLAP is an acronym for a. Online Analytical Processing b. Online Analysis Process c. Online Arithmetic Processing d. Object Linking and Processing
1. OLAP is an acronym for a. Online Analytical Processing b. Online Analysis Process c. Online Arithmetic Processing d. Object Linking and Processing 2. What is a Data warehouse a. A database application
More informationA Technical Review on On-Line Analytical Processing (OLAP)
A Technical Review on On-Line Analytical Processing (OLAP) K. Jayapriya 1., E. Girija 2,III-M.C.A., R.Uma. 3,M.C.A.,M.Phil., Department of computer applications, Assit.Prof,Dept of M.C.A, Dhanalakshmi
More informationCHAPTER 4 Data Warehouse Architecture
CHAPTER 4 Data Warehouse Architecture 4.1 Data Warehouse Architecture 4.2 Three-tier data warehouse architecture 4.3 Types of OLAP servers: ROLAP versus MOLAP versus HOLAP 4.4 Further development of Data
More informationOBIEE vs Hyperion Financial Reports: Oracle's Future in EPM Reporting
OBIEE vs Hyperion Financial Reports: Oracle's Future in EPM Reporting Alex Ladd Sr. Partner MindStream Analytics The Webinar will start at 12:05pm Agenda Introduction Audience Participation Today s Goals
More informationM2074 - Designing and Implementing OLAP Solutions Using Microsoft SQL Server 2000 5 Day Course
Module 1: Introduction to Data Warehousing and OLAP Introducing Data Warehousing Defining OLAP Solutions Understanding Data Warehouse Design Understanding OLAP Models Applying OLAP Cubes At the end of
More information2074 : Designing and Implementing OLAP Solutions Using Microsoft SQL Server 2000
2074 : Designing and Implementing OLAP Solutions Using Microsoft SQL Server 2000 Introduction This course provides students with the knowledge and skills necessary to design, implement, and deploy OLAP
More informationA Critical Review of Data Warehouse
Global Journal of Business Management and Information Technology. Volume 1, Number 2 (2011), pp. 95-103 Research India Publications http://www.ripublication.com A Critical Review of Data Warehouse Sachin
More informationA2: Enterprise Business Intelligence with Open Source DRAFT
A2: Enterprise Business Intelligence with Open Source DRAFT Speakers: Christopher Lavigne, Partner, Breadboard BI. Zachary Zeus, Principal, BizCubed. Agenda Introductions Overview Components of Enterprise
More informationMonitoring Genebanks using Datamarts based in an Open Source Tool
Monitoring Genebanks using Datamarts based in an Open Source Tool April 10 th, 2008 Edwin Rojas Research Informatics Unit (RIU) International Potato Center (CIP) GPG2 Workshop 2008 Datamarts Motivation
More informationData Warehouse: Introduction
Base and Mining Group of Base and Mining Group of Base and Mining Group of Base and Mining Group of Base and Mining Group of Base and Mining Group of Base and Mining Group of base and data mining group,
More informationAn Architectural Review Of Integrating MicroStrategy With SAP BW
An Architectural Review Of Integrating MicroStrategy With SAP BW Manish Jindal MicroStrategy Principal HCL Objectives To understand how MicroStrategy integrates with SAP BW Discuss various Design Options
More informationWeb Log Data Sparsity Analysis and Performance Evaluation for OLAP
Web Log Data Sparsity Analysis and Performance Evaluation for OLAP Ji-Hyun Kim, Hwan-Seung Yong Department of Computer Science and Engineering Ewha Womans University 11-1 Daehyun-dong, Seodaemun-gu, Seoul,
More informationData Warehousing: Data Models and OLAP operations. By Kishore Jaladi kishorejaladi@yahoo.com
Data Warehousing: Data Models and OLAP operations By Kishore Jaladi kishorejaladi@yahoo.com Topics Covered 1. Understanding the term Data Warehousing 2. Three-tier Decision Support Systems 3. Approaches
More informationWhen to consider OLAP?
When to consider OLAP? Author: Prakash Kewalramani Organization: Evaltech, Inc. Evaltech Research Group, Data Warehousing Practice. Date: 03/10/08 Email: erg@evaltech.com Abstract: Do you need an OLAP
More informationUniversity of Gaziantep, Department of Business Administration
University of Gaziantep, Department of Business Administration The extensive use of information technology enables organizations to collect huge amounts of data about almost every aspect of their businesses.
More informationReporting trends and pain points of current and new customers. 2013 IBM Corporation
Reporting trends and pain points of current and new customers 2013 IBM Corporation Three main area of problems 1. Slow reporting performance But it is about the data source, not about reporting tool 2.
More informationCopyright 2007 Ramez Elmasri and Shamkant B. Navathe. Slide 29-1
Slide 29-1 Chapter 29 Overview of Data Warehousing and OLAP Chapter 29 Outline Purpose of Data Warehousing Introduction, Definitions, and Terminology Comparison with Traditional Databases Characteristics
More informationBusiness Intelligence: Multidimensional Data Analysis
Business Intelligence: Multidimensional Data Analysis Per Westerlund August 20, 2008 Master Thesis in Computing Science 30 ECTS Credits Abstract The relational database model is probably the most frequently
More informationBUILDING OLAP TOOLS OVER LARGE DATABASES
BUILDING OLAP TOOLS OVER LARGE DATABASES Rui Oliveira, Jorge Bernardino ISEC Instituto Superior de Engenharia de Coimbra, Polytechnic Institute of Coimbra Quinta da Nora, Rua Pedro Nunes, P-3030-199 Coimbra,
More informationOverview. DW Source Integration, Tools, and Architecture. End User Applications (EUA) EUA Concepts. DW Front End Tools. Source Integration
DW Source Integration, Tools, and Architecture Overview DW Front End Tools Source Integration DW architecture Original slides were written by Torben Bach Pedersen Aalborg University 2007 - DWML course
More informationOLAP Systems and Multidimensional Queries II
OLAP Systems and Multidimensional Queries II Krzysztof Dembczyński Intelligent Decision Support Systems Laboratory (IDSS) Poznań University of Technology, Poland Software Development Technologies Master
More informationDATA CUBES E0 261. Jayant Haritsa Computer Science and Automation Indian Institute of Science. JAN 2014 Slide 1 DATA CUBES
E0 261 Jayant Haritsa Computer Science and Automation Indian Institute of Science JAN 2014 Slide 1 Introduction Increasingly, organizations are analyzing historical data to identify useful patterns and
More informationData Warehousing OLAP
Data Warehousing OLAP References Wei Wang. A Brief MDX Tutorial Using Mondrian. School of Computer Science & Engineering, University of New South Wales. Toon Calders. Querying OLAP Cubes. Wolf-Tilo Balke,
More informationData Warehousing Systems: Foundations and Architectures
Data Warehousing Systems: Foundations and Architectures Il-Yeol Song Drexel University, http://www.ischool.drexel.edu/faculty/song/ SYNONYMS None DEFINITION A data warehouse (DW) is an integrated repository
More informationDatabase Applications. Advanced Querying. Transaction Processing. Transaction Processing. Data Warehouse. Decision Support. Transaction processing
Database Applications Advanced Querying Transaction processing Online setting Supports day-to-day operation of business OLAP Data Warehousing Decision support Offline setting Strategic planning (statistics)
More informationEnterprise Solutions. Data Warehouse & Business Intelligence Chapter-8
Enterprise Solutions Data Warehouse & Business Intelligence Chapter-8 Learning Objectives Concepts of Data Warehouse Business Intelligence, Analytics & Big Data Tools for DWH & BI Concepts of Data Warehouse
More informationData analysis: tools and methods
Data analysis: tools and methods PROKOPOVA ZDENKA, SILHAVY PETR, SILHAVY RADEK Department of Computer and Communication Systems Faculty of Applied Informatics Tomas Bata University in Zlin nám. T. G. Masaryka
More informationData Warehousing and Decision Support. Introduction. Three Complementary Trends. Chapter 23, Part A
Data Warehousing and Decision Support Chapter 23, Part A Database Management Systems, 2 nd Edition. R. Ramakrishnan and J. Gehrke 1 Introduction Increasingly, organizations are analyzing current and historical
More informationPart 22. Data Warehousing
Part 22 Data Warehousing The Decision Support System (DSS) Tools to assist decision-making Used at all levels in the organization Sometimes focused on a single area Sometimes focused on a single problem
More informationSAS BI Course Content; Introduction to DWH / BI Concepts
SAS BI Course Content; Introduction to DWH / BI Concepts SAS Web Report Studio 4.2 SAS EG 4.2 SAS Information Delivery Portal 4.2 SAS Data Integration Studio 4.2 SAS BI Dashboard 4.2 SAS Management Console
More informationCognos 8 Best Practices
Northwestern University Business Intelligence Solutions Cognos 8 Best Practices Volume 2 Dimensional vs Relational Reporting Reporting Styles Relational Reports are composed primarily of list reports,
More informationConcepts of Database Management Seventh Edition. Chapter 9 Database Management Approaches
Concepts of Database Management Seventh Edition Chapter 9 Database Management Approaches Objectives Describe distributed database management systems (DDBMSs) Discuss client/server systems Examine the ways
More informationOracle OLAP What's All This About?
Oracle OLAP What's All This About? IOUG Live! 2006 Dan Vlamis dvlamis@vlamis.com Vlamis Software Solutions, Inc. 816-781-2880 http://www.vlamis.com Vlamis Software Solutions, Inc. Founded in 1992 in Kansas
More informationPREFACE INTRODUCTION MULTI-DIMENSIONAL MODEL. Chris Claterbos, Vlamis Software Solutions, Inc. dvlamis@vlamis.com
BUILDING CUBES AND ANALYZING DATA USING ORACLE OLAP 11G Chris Claterbos, Vlamis Software Solutions, Inc. dvlamis@vlamis.com PREFACE As of this writing, Oracle Business Intelligence and Oracle OLAP are
More informationData Warehouse design
Data Warehouse design Design of Enterprise Systems University of Pavia 21/11/2013-1- Data Warehouse design DATA PRESENTATION - 2- BI Reporting Success Factors BI platform success factors include: Performance
More informationWeek 3 lecture slides
Week 3 lecture slides Topics Data Warehouses Online Analytical Processing Introduction to Data Cubes Textbook reference: Chapter 3 Data Warehouses A data warehouse is a collection of data specifically
More informationOpen Source Business Intelligence Intro
Open Source Business Intelligence Intro Stefano Scamuzzo Senior Technical Manager Architecture & Consulting Research & Innovation Division Engineering Ingegneria Informatica The Open Source Question In
More informationWhitepaper. Innovations in Business Intelligence Database Technology. www.sisense.com
Whitepaper Innovations in Business Intelligence Database Technology The State of Database Technology in 2015 Database technology has seen rapid developments in the past two decades. Online Analytical Processing
More informationDecision Support. Chapter 23. Database Management Systems, 2 nd Edition. R. Ramakrishnan and J. Gehrke 1
Decision Support Chapter 23 Database Management Systems, 2 nd Edition. R. Ramakrishnan and J. Gehrke 1 Introduction Increasingly, organizations are analyzing current and historical data to identify useful
More informationSAS Business Intelligence Online Training
SAS Business Intelligence Online Training IQ Training facility offers best online SAS Business Intelligence training. Our SAS Business Intelligence online training is regarded as the best training in Hyderabad
More informationOLAP Data Scalability
OLAP Data Scalability White Paper Ignore OLAP Data Explosion at great cost. many organisations will never know that they figuratively bought a very expensive rowing boat, when they could have traveled
More informationData Warehousing, OLAP, and Data Mining
Data Warehousing, OLAP, and Marek Rychly mrychly@strathmore.edu Strathmore University, @ilabafrica & Brno University of Technology, Faculty of Information Technology Advanced Databases and Enterprise Systems
More informationII. OLAP(ONLINE ANALYTICAL PROCESSING)
Association Rule Mining Method On OLAP Cube Jigna J. Jadav*, Mahesh Panchal** *( PG-CSE Student, Department of Computer Engineering, Kalol Institute of Technology & Research Centre, Gujarat, India) **
More informationBusiness Intelligence Solutions. Cognos BI 8. by Adis Terzić
Business Intelligence Solutions Cognos BI 8 by Adis Terzić Fairfax, Virginia August, 2008 Table of Content Table of Content... 2 Introduction... 3 Cognos BI 8 Solutions... 3 Cognos 8 Components... 3 Cognos
More informationThe Design and the Implementation of an HEALTH CARE STATISTICS DATA WAREHOUSE Dr. Sreèko Natek, assistant professor, Nova Vizija, srecko@vizija.
The Design and the Implementation of an HEALTH CARE STATISTICS DATA WAREHOUSE Dr. Sreèko Natek, assistant professor, Nova Vizija, srecko@vizija.si ABSTRACT Health Care Statistics on a state level is a
More informationKnowledge Discovery in Databases. Databases. date name surname street city account no. payment balance
Databases date name surname street city account no. payment balance 980103 Jan Novak Dlouha 5 Praha 1 9945371 100.00 100.00 980105 Jan Novak Dlouha 5 Praha 1 9945371 1500.00 1600.00 980106 Jan Novak Dlouha
More informationTurning your Warehouse Data into Business Intelligence: Reporting Trends and Visibility Michael Armanious; Vice President Sales and Marketing Datex,
Turning your Warehouse Data into Business Intelligence: Reporting Trends and Visibility Michael Armanious; Vice President Sales and Marketing Datex, Inc. Overview Introduction What is Business Intelligence?
More informationData Warehouse and OLAP. Methodologies, Algorithms, Trends
58 Data Warehouse and OLAP. Methodologies, Algorithms, Trends Radu LOVIN IT Consultant Tata Consultancy Services GE European Equipment Finance - Data Warehouse Project radu.lovin@ge.com On-Line Analytical
More informationOn-Line Application Processing. Warehousing Data Cubes Data Mining
On-Line Application Processing Warehousing Data Cubes Data Mining 1 Overview Traditional database systems are tuned to many, small, simple queries. Some new applications use fewer, more time-consuming,
More informationOLAP & DATA MINING CS561-SPRING 2012 WPI, MOHAMED ELTABAKH
OLAP & DATA MINING CS561-SPRING 2012 WPI, MOHAMED ELTABAKH 1 Online Analytic Processing OLAP 2 OLAP OLAP: Online Analytic Processing OLAP queries are complex queries that Touch large amounts of data Discover
More information<Insert Picture Here> Enhancing the Performance and Analytic Content of the Data Warehouse Using Oracle OLAP Option
Enhancing the Performance and Analytic Content of the Data Warehouse Using Oracle OLAP Option The following is intended to outline our general product direction. It is intended for
More informationReport Data Management in the Cloud: Limitations and Opportunities
Report Data Management in the Cloud: Limitations and Opportunities Article by Daniel J. Abadi [1] Report by Lukas Probst January 4, 2013 In this report I want to summarize Daniel J. Abadi's article [1]
More informationOracle BI, Oracle OLAP, Essbase Compared. ODTUG Kaleidoscope 2008
Oracle BI, Oracle OLAP, Essbase Compared ODTUG Kaleidoscope 2008 Wednesday June 18, 2:45 PM 3:45 PM Dan Vlamis dvlamis@vlamis.com Vlamis Software Solutions, Inc. 816-781-2880 http://www.vlamis.com Agenda
More informationBusiness Intelligence
Business Intelligence Data Mining and Data Warehousing Dominik Ślęzak slezak@infobright.com www.infobright.com Research Interests Data Warehouses, Knowledge Discovery, Rough Sets Machine Intelligence,
More informationIntro to BI. Mul0- dimensional Analysis
Intro to BI BI Vendor Landscape BI Roles & Responsibili0es Data Governance and Quality DW Architectures ETL Processes BI Capabili0es & Maturity Mul0- dimensional Analysis BI Vendors and Products Module
More informationCHAPTER 11: BUSINESS INTELLIGENCE - SUPPLEMENTAL MATERIAL
CHAPTER 11: BUSINESS INTELLIGENCE - SUPPLEMENTAL MATERIAL BRIAN P. MORGAN From the book The Next Wave of Technologies: Opportunities in Chaos by Phil Simon A Very Brief History of BI In his article A Democratic
More information(Week 10) A04. Information System for CRM. Electronic Commerce Marketing
(Week 10) A04. Information System for CRM Electronic Commerce Marketing Course Code: 166186-01 Course Name: Electronic Commerce Marketing Period: Autumn 2015 Lecturer: Prof. Dr. Sync Sangwon Lee Department:
More informationBuilding Data Cubes and Mining Them. Jelena Jovanovic Email: jeljov@fon.bg.ac.yu
Building Data Cubes and Mining Them Jelena Jovanovic Email: jeljov@fon.bg.ac.yu KDD Process KDD is an overall process of discovering useful knowledge from data. Data mining is a particular step in the
More informationOverview. Data Warehousing and Decision Support. Introduction. Three Complementary Trends. Data Warehousing. An Example: The Store (e.g.
Overview Data Warehousing and Decision Support Chapter 25 Why data warehousing and decision support Data warehousing and the so called star schema MOLAP versus ROLAP OLAP, ROLLUP AND CUBE queries Design
More informationBusiness Terms as a Critical Success Factor for Data Warehousing
Business Terms as a Critical Success Factor for Data Warehousing Peter Lehmann Lawson Mardon Singen Alusingen-Platz 1 D-78221 Singen peter.lehmann@lawsonmardon.com Johann Jaszewski Otto-von-Guericke-Universität
More informationCX-044 Description of the Business Process within the supervision of banking related to XBRL processing Internal Draft updated 2005-08-31
CX-044 Description of the Business Process within the supervision of banking related to XBRL processing Internal Draft updated 2005-08-31 Documentation for software vendors Table of contents INTRODUCTION...
More informationOLAP. Business Intelligence OLAP definition & application Multidimensional data representation
OLAP Business Intelligence OLAP definition & application Multidimensional data representation 1 Business Intelligence Accompanying the growth in data warehousing is an ever-increasing demand by users for
More informationOLAP. Introduction. OLAP System Components. Sources. Adrienne H. Slaughter. Product Table. Feature Table
OLAP Adrienne H. Slaughter Introduction Product Table Feature Table A successful company today has many decisions to make. The better those decisions are made, the more successful, and profitable, the
More informationA very short talk about Apache Kylin Business Intelligence meets Big Data. Fabian Wilckens EMEA Solutions Architect
A very short talk about Apache Kylin Business Intelligence meets Big Data Fabian Wilckens EMEA Solutions Architect 1 The challenge today 2 Very quickly: OLAP Online Analytical Processing How many beers
More informationHow To Use A Business Intelligence Front-End (Bi) Tool
Chapter 3 The Business Intelligence Front-End If the business intelligence architecture is like the engine of the car, then the BI front-end tools are like the body: sporty, sleek, fast, and where the
More information70-467: Designing Business Intelligence Solutions with Microsoft SQL Server
70-467: Designing Business Intelligence Solutions with Microsoft SQL Server The following tables show where changes to exam 70-467 have been made to include updates that relate to SQL Server 2014 tasks.
More informationIntegrating GIS and BI: a Powerful Way to Unlock Geospatial Data for Decision-Making
Integrating GIS and BI: a Powerful Way to Unlock Geospatial Data for Decision-Making Professor Yvan Bedard, PhD, P.Eng. Centre for Research in Geomatics Laval Univ., Quebec, Canada National Technical University
More informationEstablish and maintain Center of Excellence (CoE) around Data Architecture
Senior BI Data Architect - Bensenville, IL The Company s Information Management Team is comprised of highly technical resources with diverse backgrounds in data warehouse development & support, business
More informationORACLE OLAP. Oracle OLAP is embedded in the Oracle Database kernel and runs in the same database process
ORACLE OLAP KEY FEATURES AND BENEFITS FAST ANSWERS TO TOUGH QUESTIONS EASILY KEY FEATURES & BENEFITS World class analytic engine Superior query performance Simple SQL access to advanced analytics Enhanced
More informationBuilding Cubes and Analyzing Data using Oracle OLAP 11g
Building Cubes and Analyzing Data using Oracle OLAP 11g Collaborate '08 Session 219 Chris Claterbos claterbos@vlamis.com Vlamis Software Solutions, Inc. 816-729-1034 http://www.vlamis.com Copyright 2007,
More informationData Warehouse Design
Data Warehouse Design Modern Principles and Methodologies Matteo Golfarelli Stefano Rizzi Translated by Claudio Pagliarani Mc Grauu Hill New York Chicago San Francisco Lisbon London Madrid Mexico City
More informationCourse 6234A: Implementing and Maintaining Microsoft SQL Server 2008 Analysis Services
Course 6234A: Implementing and Maintaining Microsoft SQL Server 2008 Analysis Services Length: Delivery Method: 3 Days Instructor-led (classroom) About this Course Elements of this syllabus are subject
More informationUnderstanding Data Warehousing. [by Alex Kriegel]
Understanding Data Warehousing 2008 [by Alex Kriegel] Things to Discuss Who Needs a Data Warehouse? OLTP vs. Data Warehouse Business Intelligence Industrial Landscape Which Data Warehouse: Bill Inmon vs.
More informationLEARNING SOLUTIONS website milner.com/learning email training@milner.com phone 800 875 5042
Course 20467A: Designing Business Intelligence Solutions with Microsoft SQL Server 2012 Length: 5 Days Published: December 21, 2012 Language(s): English Audience(s): IT Professionals Overview Level: 300
More informationDelivering Business Intelligence With Microsoft SQL Server 2005 or 2008 HDT922 Five Days
or 2008 Five Days Prerequisites Students should have experience with any relational database management system as well as experience with data warehouses and star schemas. It would be helpful if students
More informationHybrid Support Systems: a Business Intelligence Approach
Journal of Applied Business Information Systems, 2(2), 2011 57 Journal of Applied Business Information Systems http://www.jabis.ro Hybrid Support Systems: a Business Intelligence Approach Claudiu Brandas
More informationIntroducing Oracle Exalytics In-Memory Machine
Introducing Oracle Exalytics In-Memory Machine Jon Ainsworth Director of Business Development Oracle EMEA Business Analytics 1 Copyright 2011, Oracle and/or its affiliates. All rights Agenda Topics Oracle
More informationMicroStrategy Course Catalog
MicroStrategy Course Catalog 1 microstrategy.com/education 3 MicroStrategy course matrix 4 MicroStrategy 9 8 MicroStrategy 10 table of contents MicroStrategy course matrix MICROSTRATEGY 9 MICROSTRATEGY
More informationBusiness Intelligence & Product Analytics
2010 International Conference Business Intelligence & Product Analytics Rob McAveney www. 300 Brickstone Square Suite 904 Andover, MA 01810 [978] 691 8900 www. Copyright 2010 Aras All Rights Reserved.
More informationCSE 544 Principles of Database Management Systems. Magdalena Balazinska Winter 2009 Lecture 15 - Data Warehousing: Cubes
CSE 544 Principles of Database Management Systems Magdalena Balazinska Winter 2009 Lecture 15 - Data Warehousing: Cubes Final Exam Overview Open books and open notes No laptops and no other mobile devices
More informationData Warehousing and OLAP
1 Data Warehousing and OLAP Hector Garcia-Molina Stanford University Warehousing Growing industry: $8 billion in 1998 Range from desktop to huge: Walmart: 900-CPU, 2,700 disk, 23TB Teradata system Lots
More informationChris Claterbos claterbos@vlamis.com Vlamis Software Solutions, Inc. 816-729-1034 http://www.vlamis.com
Building Cubes and Analyzing Data using Oracle OLAP 11g Collaborate 09 Session 252 Chris Claterbos claterbos@vlamis.com Vlamis Software Solutions, Inc. 816-729-1034 http://www.vlamis.com Vlamis Software
More informationMicrosoft Excel, other vendors personal desktop reporting tools
Microsoft BI Semantic Models, SAP BO Universes, IBM Cognos Frameworks, Tableau TDEs Microsoft SharePoint, SAP Portal, IBM Cognos Connection, other vendors reporting portals Microsoft Excel, other vendors
More information