Thuyết trình OLAP USING SSAS TO ANALYZE OLAP CUBE IN RETAIL DATABASE

OLAP & USING SSAS TO ANALYZE OLAP CUBE IN RETAIL DATABASE Group 9: Number Four 1. THANG MAI HOANG 2. TRAM TRAN THANH 3. LINH NGUYEN THI THUY 4. NGUYEN BUI BA Advisor: Associate Professor Phuc Do INTRODUCTION Hey Employee, how much money we made last year? Employee: $1 billion dollars Sir ! How much did we make per year per quarter? Which products did well and which failed? What are the sales by region, country, by year, by quarter etc. Employee (thinking ) : Hmm What is the best way to this?? :=( ??? AGENDA 1. INTRODUCTION TO OLAP 2. OLAP CUBE 3. OLAP OPERATIONS 4. TYPE OF OLAP 5. OLAP ADVANTAGES & DISADVANTAGES 6. DATA WAREHOUSE 7. SQL SERVER ANALYSIS SERVICE 8. CASE STUDY 9. REFERENCES 10. Q/A 1. INTRODUCTION TO OLAP  History • The term OLAP was created as a slight modification of the traditional database term OLTP (Online Transaction Processing) • Databases configured for OLAP employ a multidimensional data model, allowing for complex analytical and adhoc queries with a rapid execution time • The first product that performed OLAP queries was Express, which was released in 1970 (and acquired by Oracle in 1995 from Information Resources). However, the term did not appear until 1993 when it was coined by Ted Codd, who has been described as "the father of the relational database 1. INTRODUCTION TO OLAP  What is OLAP? • OLAP (Online Analytical Processing) is computer processing that enables a user to easily and selectively extract and view data from different points of view • OLAP allows users to analyze database information from multiple database systems at one time • OLAP data is stored in multidimensional databases 1. INTRODUCTION TO OLAP  What is OLAP? • Some popular OLAP server software programs include: Oracle Express Server, Hyperion Solutions Essbase • • OLAP processing is often used for data mining OLAP products are typically designed for multiple-user environments, with the cost of the software based on the number of users 1. INTRODUCTION TO OLAP  Purpose of OLAP • • To derive summarized information from large volume database To generate automated reports for human view 1. INTRODUCTION TO OLAP 1. INTRODUCTION TO OLAP  Why we need OLAP ? • • • Increasing data storage Data versus Information Data layout 2. THE OLAP CUBE • • • An OLAP Cube is a data structure that allows fast analysis of data The arrangement of data into cubes overcomes a limitation of relational databases The OLAP cube consists of numeric facts called measures which are categorized by dimensions • A multidimensional cube can combine data from disparate data sources and store the information in a fashion that is logical for business users 10 3. OLAP OPERATIONS Slice and Dice: select and project on one or more dimensions ct customers pr od u  store customer = “Smith” 16 4. TYPE OF OLAP • • • Relational OLAP(ROLAP) Multidimensional OLAP(MOLAP) Hybrid Online Analytical Processing (HOLAP) 17 5. OLAP ADVANTAGES & DISADVANTAGES Advantages • • • • Offer quicker analysis Great reporting tool Improves decision making Flexible Disadvantages • • • Rely on data warehouse environment Complexity of the queries Result set be materialized in memory before returning to the client 18 6. DATA WAREHOUSE   Data warehouse (DW or DWH) is a system used for reporting and data analysis A data warehouse is a subject-oriented, integrated, time-varying, non-volatile collection of data that is used primarily in organizational decision making 19 6. DATA WAREHOUSE  Benefits  Provide a single common data model for all data of interest regardless of the data's source.  Present the organization's information consistently  Enabling a central view across the enterprise  Maintain data history  Restructure the data so that it delivers excellent query performance, even for complex analytic queries, without impacting the operational systems  Make decision–support queries easier to write 20 Data warehousing architecture Monitor other DBs OLAP Server Integrator sources Operational & Metadata Analysis Extract Transform Load Refresh Data Serve Query Reports Warehouse Data mining Data Marts Data Sources Data Storage OLAP Engine Front-End Tools 21 6. DATA WAREHOUSE  Applications of data warehouses  Data Mining  Web Mining  Decision Support Systems (DSS) 22 6. DATA WAREHOUSE  • • Data warehouse design Most data warehouses adopt a star schema to represent the multidimensional model Each dimension is represented by a dimension-table – – • LOCATION(location_key,store,street_address,city,state, country,region) dimension tables are not normalized Transactions are described through a fact-table – each tuple consists of a pointer to each of the dimension-tables (foreign-key) and a list of measures (e.g. sales $$$) 23 Star Schema Dimension Table Location ID Location Name Budget Storage Capacity State Dimension Table Item Number Item Name Description Category Subcategory Dimension Table Buyer Number Buyer Name Department Division City Region State Country Region Address Country Fact Table Dimension Table Time Period Date Month Year Quarter Fiscal Year Dimension Table Location Item Number Supplier Number Buyer Number Supplier Name Supplier Number Industry Category Time Period Subcategory Dollar Purchases State Unit Purchases Region Country Day Address At the center of the star is a single fact table that represents the most important variable of interest 24 7. SQL SERVER ANALYSIS SERVICE  Olap with SQL Server Analysis Service • Microsoft SQL Server Analysis Services, SSAS, is an online analytical processing (OLAP), data mining and reporting tool in Microsoft SQL Server. SSAS is used as a tool by organizations to analyze and make sense of information possibly spread out across multiple databases, or in disparate tables. Microsoft has included a number of services in SQL Server related to business intelligence and data warehousing. These services include Integration Services and Analysis Services. Analysis Services includes a group of OLAP and data mining capabilities 25 SSAS Clients Physical Architecture 26 8. OLAP CASE STUDY  Number Four Global is having different malls in different countries, where daily sales take place for various products. Higher management is facing an issue while decision making due to non availability of integrated data they can’t study on their data as per their requirement. So they asked us to design a system which can help them quickly in decision making. 27 8. OLAP CASE STUDY Solutions       Overview Shopping mall & report requirements Develop database / data warehouse Develop OLAP Cube Process the cube Analyze the cube Integrate OLAP Cube to the system 28 DEMO 29 REFERENCES [1] Himanshu Tiwari. Data Mining, Warehousing and OLAP Technology. Galgotia’s college of Engineering and technology Gr.Noida. 2014 [2] Siddhant Mehta, PoonamRawat, Prerna Malik. Overview of Multidimensional Data Model – OLAP. International Journal Of Research. 2014 [3] Dr Walid Qassim Qwaider. Apply Online Analytical Processing (OLAP) With Data Mining For Clinical Decision Support. International Journal Of Managing Information Technology. 2012 [4] Robert Wrembel & Christian Konci. Data Warehouses And OLAP – Concepts, Architectures and Solutions. Pozan University Of Technology, Poland. 2006 [4] How to Create OLAP Cube in Analysis Services, http://www.wikihow.com/Create-OLAP-Cube-in-Analysis-Services, View on 30 July 2015 [5] OLAP and Business Intelligence Tutorials, http://olap.com/learn-bi-olap/tutorials/, View on 26 July 2015 [6] Trần Vũ Hải. Áp Dụng Kỹ Thuật Phân Tích Dữ Liệu Trực Tuyến (OLAP) Phục Vụ Công Tác Quản Lý Điều Hành. Luận Văn Thạc Sĩ. Học Viện Công Nghệ Bưu Chính Viễn Thông, Hà Nội, 2011 [7] DSS course material provided by Associate Professor Phuc Do, 2015 30 31 [...]... which can help them quickly in decision making 27 8 OLAP CASE STUDY Solutions       Overview Shopping mall & report requirements Develop database / data warehouse Develop OLAP Cube Process the cube Analyze the cube Integrate OLAP Cube to the system 28 DEMO 29 REFERENCES [1] Himanshu Tiwari Data Mining, Warehousing and OLAP Technology Galgotia’s college of Engineering and technology Gr.Noida 2014... reporting tool in Microsoft SQL Server SSAS is used as a tool by organizations to analyze and make sense of information possibly spread out across multiple databases, or in disparate tables Microsoft has included a number of services in SQL Server related to business intelligence and data warehousing These services include Integration Services and Analysis Services Analysis Services includes a group of OLAP. .. impacting the operational systems  Make decision–support queries easier to write 20 Data warehousing architecture Monitor other DBs OLAP Server Integrator sources Operational & Metadata Analysis Extract Transform Load Refresh Data Serve Query Reports Warehouse Data mining Data Marts Data Sources Data Storage OLAP Engine Front-End Tools 21 6 DATA WAREHOUSE  Applications of data warehouses  Data Mining... – OLAP International Journal Of Research 2014 [3] Dr Walid Qassim Qwaider Apply Online Analytical Processing (OLAP) With Data Mining For Clinical Decision Support International Journal Of Managing Information Technology 2012 [4] Robert Wrembel & Christian Konci Data Warehouses And OLAP – Concepts, Architectures and Solutions Pozan University Of Technology, Poland 2006 [4] How to Create OLAP Cube in. .. month week day store 14 3 OLAP OPERATIONS  Pivoting: aggregate on selected dimensions ◦ usually 2 dims (cross-tabulation) 15 3 OLAP OPERATIONS Slice and Dice: select and project on one or more dimensions ct customers pr od u  store customer = “Smith” 16 4 TYPE OF OLAP • • • Relational OLAP( ROLAP) Multidimensional OLAP( MOLAP) Hybrid Online Analytical Processing (HOLAP) 17 5 OLAP ADVANTAGES & DISADVANTAGES... THE OLAP CUBE 11 2 THE OLAP CUBE 12 2 THE OLAP CUBE 13 3 OLAP OPERATIONS  Roll-up: move up the hierarchy ◦ e.g given total sales per city, we can roll-up to get sales per state  PRODUCT LOCATION TIME category region year product country quarter Drill-down: move down the hierarchy ◦ ◦ more fine-grained aggregation lowest level can be the detail records (drill-through) state city month week day store... Number Industry Category Time Period Subcategory Dollar Purchases State Unit Purchases Region Country Day Address At the center of the star is a single fact table that represents the most important variable of interest 24 7 SQL SERVER ANALYSIS SERVICE  Olap with SQL Server Analysis Service • Microsoft SQL Server Analysis Services, SSAS, is an online analytical processing (OLAP) , data mining and reporting... OLAP and data mining capabilities 25 SSAS Clients Physical Architecture 26 8 OLAP CASE STUDY  Number Four Global is having different malls in different countries, where daily sales take place for various products Higher management is facing an issue while decision making due to non availability of integrated data they can’t do study on their data as per their requirement So they asked us to design a... Poland 2006 [4] How to Create OLAP Cube in Analysis Services, http://www.wikihow.com/Create -OLAP- Cube- in- Analysis-Services, View on 30 July 2015 [5] OLAP and Business Intelligence Tutorials, http:/ /olap. com/learn-bi -olap/ tutorials/, View on 26 July 2015 [6] Trần Vũ Hải Áp Dụng Kỹ Thuật Phân Tích Dữ Liệu Trực Tuyến (OLAP) Phục Vụ Công Tác Quản Lý Điều Hành Luận Văn Thạc Sĩ Học Viện Công Nghệ Bưu Chính Viễn... time-varying, non-volatile collection of data that is used primarily in organizational decision making 19 6 DATA WAREHOUSE  Benefits  Provide a single common data model for all data of interest regardless of the data's source  Present the organization's information consistently  Enabling a central view across the enterprise  Maintain data history  Restructure the data so that it delivers excellent query . is OLAP? 1. INTRODUCTION TO OLAP 7 • To derive summarized information from large volume database • To generate automated reports for human view  Purpose of OLAP 1. INTRODUCTION TO OLAP 8 1. INTRODUCTION. allows users to analyze database information from multiple database systems at one time • OLAP data is stored in multidimensional databases 1. INTRODUCTION TO OLAP 6 • Some popular OLAP server. OLAP & USING SSAS TO ANALYZE OLAP CUBE IN RETAIL DATABASE Group 9: Number Four 1. THANG MAI HOANG 2. TRAM TRAN THANH 3. LINH NGUYEN THI THUY 4. NGUYEN BUI