This portfolio contains examples of Carmen Faber's Microsoft Business Intelligence work using SSAS (SQL Server Analysis Services) and MDX (Multi-Dimensional Expressions). It includes cube structure, dimensions, hierarchies, calculations, KPIs (key performance indicators), and sample MDX queries analyzing data by measures, dimensions, and time periods.
Microsoft SQL Server Analysis Services (SSAS) - A Practical Introduction Mark Ginnebaugh
Patrick Sheehan of Microsoft covers platform architecture, data warehousing methodology, and multi-dimensional cube development.
You will learn:
* How to develop and deploy data cubes using SQL Server Analysis Services (SSAS)
* Optimal data warehouse methodology for use with SSAS
* Tips/tricks for designing & building cubes over no warehouse/suboptimal source system (it happens)
* Cube processing types - How/why to use each
* Cube design practices + How to build and deploy cubes!
This document discusses designing and developing OLAP cubes and multidimensional structures. It provides an introduction to OLAP and covers components of cubes like dimensions, measures, and data sources. It also outlines the steps to build a cube in SSAS including creating the data source view, dimensions, measures, and deploying the database. Calculations, KPIs, perspectives and other advanced features are also briefly mentioned.
This document discusses several topics related to SQL Server Analysis Services (SSAS) including:
- Best practices for SSAS design including dimensions, measures, partitioning and security.
- New features in the upcoming "Denali" release including the BI semantic model and PowerPivot integration.
- Performance tuning techniques such as distinct count optimization and scale out queries.
- Tools for analyzing SSAS queries and cube design best practices.
- Design considerations for large enterprise solutions including partitioning, hardware sizing and concurrency management.
OLAP – Creating Cubes with SQL Server Analysis ServicesPeter Gfader
This document provides information about a SQL Server 2008 for Business Intelligence short course. The course aims to help developers step to the next level by learning modern engineering practices using Visual Studio 2010, Team Foundation Server, and the Scrum framework. Certifications are available upon completion of assessments. Contact and resource details are provided for the course instructor Peter Gfader, including his areas of specialization and online profiles. An overview of the course schedule and topics is also given.
Developing with SQL Server Analysis Services 201310Mark Tabladillo
SQL Server Analysis Services (SSAS) allows for integrating cubes, tabular model databases, and data mining with your developed applications and services. This talk provides a developer’s framework for understanding SSAS and its core ADOMD .NET and AMO classes. These development options will be demonstrated through application demos. This session is great for developers already working with SQL Server, who want to take their development skills to the next level.
A Gentle Introduction to Microsoft SSASJohn Paredes
This document provides an overview of Analysis Services and how to create an OLAP cube. It discusses why data is stored in cubes rather than tables, including better query performance, efficient storage and calculations. It then outlines the steps to create an Analysis Services project, define data sources and dimensions, create and process the cube, and optimize query performance through partitioning and pre-aggregating data.
SSAS, MDX , Cube understanding, Browsing and Tools information Vishal Pawar
Why we need SSAS Cube
What is SSAS Cube
Way to access Cube
What is Dimension and Attributes
QHP Dimension and Attributes
Process Flow and QHP Cube Browsing
MDX Basics
MDX Tools
Comparison of Queries Written in T-SQL and MDX with Construct
MDX –How to add where condition
Microsoft SQL Server Analysis Services (SSAS) - A Practical Introduction Mark Ginnebaugh
Patrick Sheehan of Microsoft covers platform architecture, data warehousing methodology, and multi-dimensional cube development.
You will learn:
* How to develop and deploy data cubes using SQL Server Analysis Services (SSAS)
* Optimal data warehouse methodology for use with SSAS
* Tips/tricks for designing & building cubes over no warehouse/suboptimal source system (it happens)
* Cube processing types - How/why to use each
* Cube design practices + How to build and deploy cubes!
This document discusses designing and developing OLAP cubes and multidimensional structures. It provides an introduction to OLAP and covers components of cubes like dimensions, measures, and data sources. It also outlines the steps to build a cube in SSAS including creating the data source view, dimensions, measures, and deploying the database. Calculations, KPIs, perspectives and other advanced features are also briefly mentioned.
This document discusses several topics related to SQL Server Analysis Services (SSAS) including:
- Best practices for SSAS design including dimensions, measures, partitioning and security.
- New features in the upcoming "Denali" release including the BI semantic model and PowerPivot integration.
- Performance tuning techniques such as distinct count optimization and scale out queries.
- Tools for analyzing SSAS queries and cube design best practices.
- Design considerations for large enterprise solutions including partitioning, hardware sizing and concurrency management.
OLAP – Creating Cubes with SQL Server Analysis ServicesPeter Gfader
This document provides information about a SQL Server 2008 for Business Intelligence short course. The course aims to help developers step to the next level by learning modern engineering practices using Visual Studio 2010, Team Foundation Server, and the Scrum framework. Certifications are available upon completion of assessments. Contact and resource details are provided for the course instructor Peter Gfader, including his areas of specialization and online profiles. An overview of the course schedule and topics is also given.
Developing with SQL Server Analysis Services 201310Mark Tabladillo
SQL Server Analysis Services (SSAS) allows for integrating cubes, tabular model databases, and data mining with your developed applications and services. This talk provides a developer’s framework for understanding SSAS and its core ADOMD .NET and AMO classes. These development options will be demonstrated through application demos. This session is great for developers already working with SQL Server, who want to take their development skills to the next level.
A Gentle Introduction to Microsoft SSASJohn Paredes
This document provides an overview of Analysis Services and how to create an OLAP cube. It discusses why data is stored in cubes rather than tables, including better query performance, efficient storage and calculations. It then outlines the steps to create an Analysis Services project, define data sources and dimensions, create and process the cube, and optimize query performance through partitioning and pre-aggregating data.
SSAS, MDX , Cube understanding, Browsing and Tools information Vishal Pawar
Why we need SSAS Cube
What is SSAS Cube
Way to access Cube
What is Dimension and Attributes
QHP Dimension and Attributes
Process Flow and QHP Cube Browsing
MDX Basics
MDX Tools
Comparison of Queries Written in T-SQL and MDX with Construct
MDX –How to add where condition
Real-world BISM in SQL Server 2012 SSASLynn Langit
The document discusses the Business Intelligence Semantic Model (BISM) in SQL Server Analysis Services. It provides an overview of what BISM is, why it should be used, how to get started with it, and how to create and enhance BISM models. It also includes demonstrations of creating a BISM model in SQL Server Data Tools and deploying it to Analysis Services.
This document provides an overview of Microsoft SQL Server Analysis Services (SSAS) tabular models. It discusses the different modes in SSAS including multidimensional and tabular. The key differences between multidimensional and tabular models are described. Tabular models are better suited for tools like Power View, Power BI, and SQL Server Reporting Services. The document demonstrates how to build a sample tabular model in SQL Server Management Studio and Analysis Services including adding data, measures, columns, and other model elements. New features of tabular models in SQL Server 2017 like the user interface and DAX functions are also summarized.
This document introduces Cortana Analytics, a suite of Microsoft technologies for data management, analytics, and visualization. It discusses Azure Data Factory for data ingestion and transformation, Azure SQL Data Warehouse for petabyte-scale data warehousing, machine learning with ML Studio, and dashboards with Power BI. The suite aims to help users choose the right technologies to meet their needs and scale with demand.
Karan Gulati has over 5 years of experience as a SQL Server Analysis Services expert at Microsoft. In this presentation, he provides an overview of key data warehousing and OLAP concepts, including: defining a data warehouse and why OLAP is used; the components of a cube like measures, dimensions, and schemas; and slowly changing dimension types like Type 1, 2, and 3. He explains these concepts at a high level to help attendees understand the terminology in the SQL and data warehousing fields.
Creating a Tabular Model Using SQL Server 2012 Analysis ServicesCode Mastery
At Code Mastery Boston Steve Hughes, Principal Consultant at Magenic, highlights: Basics of SQL Server 2012 Analysis Services, Multidimensional Model, VS PowerPivot, Creating a Tabular Model
Azure analysis services next step to bi in the cloudGabi Münster
This document discusses Azure Analysis Services and how it can improve business intelligence (BI) in the cloud. It begins with an introduction of the speaker and an agenda for the presentation. It then provides definitions of Azure Analysis Services, BI, and their key components. The rest of the document focuses on the advantages of Azure Analysis Services compared to on-premises SSAS and other cloud BI services like Power BI, including easier setup and management, scalability, and cost benefits. It demonstrates features of Azure Analysis Services and how it can close gaps between self-service and enterprise BI needs.
This document discusses SSAS tabular models and compares them to multidimensional models. Tabular models offer shorter development times than multidimensional models. While tabular models have some limitations compared to multidimensional models, they provide high performance through in-memory column-based data storage and up to 10x data compression. The document provides a detailed comparison of the features and capabilities of tabular and multidimensional models. It also discusses considerations for choosing between the two types of models based on factors like data complexity, user requirements, and hardware.
SSIS coding conventions, best practices, tips and programming guidelines for ...Vishal Pawar
SQL Server Integration Service (SSIS ) coding conventions, best practices, tips and programming guidelines for sql server.This slide is really helpful for starting conversion between architects and developers. Just print 2nd slide and put on your desk as coding life board.
This document summarizes new features in SQL Server 2016 including improvements to SQL Server Integration Services, Master Data Services, Analysis Services, Data Quality Services, and Reporting Services. Key enhancements include increased data source support, performance optimizations, expanded DAX functionality, custom parameters in Reporting Services, and integration with Power BI. The presentation provides an overview of these features to help users understand the capabilities of SQL Server 2016.
The document provides an overview of SQL Server 2008 business intelligence capabilities including SQL Server Analysis Services (SSAS) for online analytical processing (OLAP) cubes and data mining models. Key capabilities covered include new aggregation designer, simplified cube/dimension wizards in SSAS, improved time series and cross-validation algorithms in data mining, and the ability to use Excel as both an OLAP cube and data mining client and model creator.
Sergiy Lunyakin "Cloud BI with Azure Analysis Services"DataConf
This document provides an overview of using Azure Analysis Services for cloud business intelligence (BI). It discusses the key components of Azure that work with Analysis Services, including Data Factory, SQL Database, SQL Data Warehouse, and Power BI. It also covers the architecture and performance levels of Analysis Services in Azure, how to connect various data sources, and tools for management, development, and troubleshooting. The document demonstrates how Analysis Services provides a fully managed tabular model engine in the cloud for enterprise-grade data modeling and analytics.
This document provides an overview of data mining in SQL Server 2008. It discusses the core functionality and new/advanced features including improved time series algorithms, holdout support for partitioning data, and cross-validation. It also outlines the data mining lifecycle and interfaces like DMX and XMLA that can be used to create and manage models. Excel add-ins and functions are demonstrated for exploring and querying models.
The document discusses SQL Server 2008 data mining capabilities. It provides an overview of data mining concepts and scenarios, demonstrates the data mining lifecycle process using SQL Server tools, and highlights new features in SQL Server 2008 such as improved time series algorithms and holdout support for model validation. Resources for learning more about SQL Server data mining are also listed.
Dimensional modeling primer - SQL Saturday Madison - April 11th, 2015Terry Bunio
This document provides a summary of a presentation on dimensional data modeling. It begins with introducing the presenter and their background. It then covers key concepts in dimensional modeling including facts, dimensions, and different modeling approaches like star schemas and snowflakes. It discusses more complex concepts like multi-valued dimensions, slowly changing dimensions, and hierarchies. It concludes by discussing why dimensional modeling is used and provides tips on how to start dimensional modeling a database.
This document outlines several business intelligence projects for AllWorks, a fictitious construction company. The first project involves building SSIS packages to transfer raw data from various sources into a SQL database, generating emails with results, and scheduling tasks. The second project involves building an SSAS cube from fact tables to analyze costs and profitability, including KPIs. The third project uses SSRS to create reports on overhead categories and employee jobs based on the SSAS cube. The final project develops dashboards in Performance Point with Excel spreadsheets, SSRS reports, and documents, publishing to SharePoint.
Building a SSAS Tabular Model DatabaseCode Mastery
This document provides an overview and agenda for a presentation on creating a tabular model using SQL Server 2012 Analysis Services. It discusses the different types of models in SSAS, the differences between multidimensional and tabular models, and demonstrates creating a basic tabular model using the AdventureWorks sample database. The presentation covers basics of SSAS, using Visual Studio for multidimensional and PowerPivot models, key features of tabular models like DirectQuery and xVelocity, and concludes with a Q&A section.
This document discusses techniques for optimizing Power BI performance. It recommends tracing queries using DAX Studio to identify slow queries and refresh times. Tracing tools like SQL Profiler and log files can provide insights into issues occurring in the data sources, Power BI layer, and across the network. Focusing on optimization by addressing wait times through a scientific process can help resolve long-term performance problems.
This document provides an overview of using Sybase WorkSpace to develop applications for Sybase IQ. It discusses WorkSpace features for enterprise modeling, database development, and migrating data and schemas from Sybase ASE to IQ. Specific capabilities covered include conceptual and physical data modeling, SQL development and debugging, schema development, and using WorkSpace to model replication environments and stage data migration to IQ. Links are provided to learn more about Sybase IQ, WorkSpace, and related products.
The document outlines an agenda for a session on SQL Server Reporting Services (SSRS) which includes demonstrations of using SSRS with OLTP, OLAP, and Hadoop HIVE data sources. It also discusses SSRS subscriptions and provides contact information for Jonathan Bloom, the presenter.
Microsoft SSAS: Should I Use Tabular or Multidimensional?Senturus
Learn the right version Microsoft SQL Server Analysis services to use to easily migrate the work to the other version. View the webinar video recording and download this deck: http://www.senturus.com/resources/microsoft-ssas/.
During this webinar, Senturus discussed how to choose between the tabular and multi-dimensional versions of SSAS for your analytic needs and the various features and benefits that each version provides.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Real-world BISM in SQL Server 2012 SSASLynn Langit
The document discusses the Business Intelligence Semantic Model (BISM) in SQL Server Analysis Services. It provides an overview of what BISM is, why it should be used, how to get started with it, and how to create and enhance BISM models. It also includes demonstrations of creating a BISM model in SQL Server Data Tools and deploying it to Analysis Services.
This document provides an overview of Microsoft SQL Server Analysis Services (SSAS) tabular models. It discusses the different modes in SSAS including multidimensional and tabular. The key differences between multidimensional and tabular models are described. Tabular models are better suited for tools like Power View, Power BI, and SQL Server Reporting Services. The document demonstrates how to build a sample tabular model in SQL Server Management Studio and Analysis Services including adding data, measures, columns, and other model elements. New features of tabular models in SQL Server 2017 like the user interface and DAX functions are also summarized.
This document introduces Cortana Analytics, a suite of Microsoft technologies for data management, analytics, and visualization. It discusses Azure Data Factory for data ingestion and transformation, Azure SQL Data Warehouse for petabyte-scale data warehousing, machine learning with ML Studio, and dashboards with Power BI. The suite aims to help users choose the right technologies to meet their needs and scale with demand.
Karan Gulati has over 5 years of experience as a SQL Server Analysis Services expert at Microsoft. In this presentation, he provides an overview of key data warehousing and OLAP concepts, including: defining a data warehouse and why OLAP is used; the components of a cube like measures, dimensions, and schemas; and slowly changing dimension types like Type 1, 2, and 3. He explains these concepts at a high level to help attendees understand the terminology in the SQL and data warehousing fields.
Creating a Tabular Model Using SQL Server 2012 Analysis ServicesCode Mastery
At Code Mastery Boston Steve Hughes, Principal Consultant at Magenic, highlights: Basics of SQL Server 2012 Analysis Services, Multidimensional Model, VS PowerPivot, Creating a Tabular Model
Azure analysis services next step to bi in the cloudGabi Münster
This document discusses Azure Analysis Services and how it can improve business intelligence (BI) in the cloud. It begins with an introduction of the speaker and an agenda for the presentation. It then provides definitions of Azure Analysis Services, BI, and their key components. The rest of the document focuses on the advantages of Azure Analysis Services compared to on-premises SSAS and other cloud BI services like Power BI, including easier setup and management, scalability, and cost benefits. It demonstrates features of Azure Analysis Services and how it can close gaps between self-service and enterprise BI needs.
This document discusses SSAS tabular models and compares them to multidimensional models. Tabular models offer shorter development times than multidimensional models. While tabular models have some limitations compared to multidimensional models, they provide high performance through in-memory column-based data storage and up to 10x data compression. The document provides a detailed comparison of the features and capabilities of tabular and multidimensional models. It also discusses considerations for choosing between the two types of models based on factors like data complexity, user requirements, and hardware.
SSIS coding conventions, best practices, tips and programming guidelines for ...Vishal Pawar
SQL Server Integration Service (SSIS ) coding conventions, best practices, tips and programming guidelines for sql server.This slide is really helpful for starting conversion between architects and developers. Just print 2nd slide and put on your desk as coding life board.
This document summarizes new features in SQL Server 2016 including improvements to SQL Server Integration Services, Master Data Services, Analysis Services, Data Quality Services, and Reporting Services. Key enhancements include increased data source support, performance optimizations, expanded DAX functionality, custom parameters in Reporting Services, and integration with Power BI. The presentation provides an overview of these features to help users understand the capabilities of SQL Server 2016.
The document provides an overview of SQL Server 2008 business intelligence capabilities including SQL Server Analysis Services (SSAS) for online analytical processing (OLAP) cubes and data mining models. Key capabilities covered include new aggregation designer, simplified cube/dimension wizards in SSAS, improved time series and cross-validation algorithms in data mining, and the ability to use Excel as both an OLAP cube and data mining client and model creator.
Sergiy Lunyakin "Cloud BI with Azure Analysis Services"DataConf
This document provides an overview of using Azure Analysis Services for cloud business intelligence (BI). It discusses the key components of Azure that work with Analysis Services, including Data Factory, SQL Database, SQL Data Warehouse, and Power BI. It also covers the architecture and performance levels of Analysis Services in Azure, how to connect various data sources, and tools for management, development, and troubleshooting. The document demonstrates how Analysis Services provides a fully managed tabular model engine in the cloud for enterprise-grade data modeling and analytics.
This document provides an overview of data mining in SQL Server 2008. It discusses the core functionality and new/advanced features including improved time series algorithms, holdout support for partitioning data, and cross-validation. It also outlines the data mining lifecycle and interfaces like DMX and XMLA that can be used to create and manage models. Excel add-ins and functions are demonstrated for exploring and querying models.
The document discusses SQL Server 2008 data mining capabilities. It provides an overview of data mining concepts and scenarios, demonstrates the data mining lifecycle process using SQL Server tools, and highlights new features in SQL Server 2008 such as improved time series algorithms and holdout support for model validation. Resources for learning more about SQL Server data mining are also listed.
Dimensional modeling primer - SQL Saturday Madison - April 11th, 2015Terry Bunio
This document provides a summary of a presentation on dimensional data modeling. It begins with introducing the presenter and their background. It then covers key concepts in dimensional modeling including facts, dimensions, and different modeling approaches like star schemas and snowflakes. It discusses more complex concepts like multi-valued dimensions, slowly changing dimensions, and hierarchies. It concludes by discussing why dimensional modeling is used and provides tips on how to start dimensional modeling a database.
This document outlines several business intelligence projects for AllWorks, a fictitious construction company. The first project involves building SSIS packages to transfer raw data from various sources into a SQL database, generating emails with results, and scheduling tasks. The second project involves building an SSAS cube from fact tables to analyze costs and profitability, including KPIs. The third project uses SSRS to create reports on overhead categories and employee jobs based on the SSAS cube. The final project develops dashboards in Performance Point with Excel spreadsheets, SSRS reports, and documents, publishing to SharePoint.
Building a SSAS Tabular Model DatabaseCode Mastery
This document provides an overview and agenda for a presentation on creating a tabular model using SQL Server 2012 Analysis Services. It discusses the different types of models in SSAS, the differences between multidimensional and tabular models, and demonstrates creating a basic tabular model using the AdventureWorks sample database. The presentation covers basics of SSAS, using Visual Studio for multidimensional and PowerPivot models, key features of tabular models like DirectQuery and xVelocity, and concludes with a Q&A section.
This document discusses techniques for optimizing Power BI performance. It recommends tracing queries using DAX Studio to identify slow queries and refresh times. Tracing tools like SQL Profiler and log files can provide insights into issues occurring in the data sources, Power BI layer, and across the network. Focusing on optimization by addressing wait times through a scientific process can help resolve long-term performance problems.
This document provides an overview of using Sybase WorkSpace to develop applications for Sybase IQ. It discusses WorkSpace features for enterprise modeling, database development, and migrating data and schemas from Sybase ASE to IQ. Specific capabilities covered include conceptual and physical data modeling, SQL development and debugging, schema development, and using WorkSpace to model replication environments and stage data migration to IQ. Links are provided to learn more about Sybase IQ, WorkSpace, and related products.
The document outlines an agenda for a session on SQL Server Reporting Services (SSRS) which includes demonstrations of using SSRS with OLTP, OLAP, and Hadoop HIVE data sources. It also discusses SSRS subscriptions and provides contact information for Jonathan Bloom, the presenter.
Microsoft SSAS: Should I Use Tabular or Multidimensional?Senturus
Learn the right version Microsoft SQL Server Analysis services to use to easily migrate the work to the other version. View the webinar video recording and download this deck: http://www.senturus.com/resources/microsoft-ssas/.
During this webinar, Senturus discussed how to choose between the tabular and multi-dimensional versions of SSAS for your analytic needs and the various features and benefits that each version provides.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Take your reports to the next dimension! In this session we will discuss how to combine the power of SSRS and SSAS to create cube driven reports. We will talk about using SSAS as a data source, writing MDX queries, using report parameters, passing parameters for drill down reports, performance tuning, and the pro’s and con’s of using a cube as your data source.
Jeff Prom is a Senior Consultant with Magenic Technologies. He holds a bachelor’s degree, three SQL Server certifications, and is an active PASS member. Jeff has been working in the IT industry for over 14 years and currently specializes in data and business intelligence.
This document provides an overview of Microsoft Business Intelligence tools including SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS), and SQL Server Reporting Services (SSRS). It discusses how these tools are used to extract, transform, and load data from various sources into a centralized data warehouse for analysis and reporting. It also provides brief descriptions of the key features and functions of each tool in the reporting development lifecycle.
This document contains a portfolio of business intelligence projects completed by Hong-Bing Li using Microsoft's BI product stack. It includes examples of SQL Server Integration Services (SSIS) packages to perform ETL, SQL programming, SQL Server Reporting Services (SSRS) reports including dashboards, SQL Server Analysis Services (SSAS) cubes, and MDX queries. The portfolio demonstrates skills in data integration, reporting, analytics, and dashboard development with a focus on Microsoft tools.
The document provides an overview of MDX (Multidimensional Expressions), a declarative query language for extracting information from Essbase databases. It compares MDX to the existing report writer interface, highlighting similarities and key differences in functions, member selection, sorting, and other capabilities. MDX allows for more complex, multidimensional queries and automated analysis with fewer steps than report writer. The document also gives examples of MDX query execution and using MDX to migrate existing report writer queries.
Despite widespread adoption of OLAP technologies, the MDX query language remains a bit of an enigma. It's not until a very simple but seldom explored concept is understood that the power and elegance of the language is revealed. Join Bryan Smith, co-author of Microsoft SQL Server 2008 MDX Step by Step, in exploring this central concept, providing a foundation for your success with the MDX language.
Multidimensional Expressions (MDX) is the query language used to retrieve multidimensional data from Analysis Services cubes. MDX utilizes expressions composed of identifiers, values, functions, and operators to retrieve objects like members, sets, or scalar values from cubes. The MDX language defines elements like identifiers, expressions, operators, functions, and comments that are used to construct MDX queries and scripts.
Feature brief detailing the MDX mobile application management features, including an overview of the technology and policies that can be added to applications.
2012 Acura MDX Brochure presented by DCH Acura of Temecula.
To see the 2012 Acura MDX in person or for more information contact DCH Acura of Temecula at (888) 690-6111 or visit our website at www.dchacuraoftemecula.com
MDx Dubai Campus known for excellence in teaching and research offers UG, PG courses in Arts, Science, technology. Middlesex MBA is the most sought after course in Dubai.
This portfolio contains examples of work done during a 10-week Business Intelligence training program. It includes projects on data modeling, T-SQL programming, SQL Server Integration Services, SQL Server Analysis Services, MDX query programming, SQL Server Reporting Services, Performance Point Server, and SharePoint Server. Relevant work experience demonstrating skills in these BI technologies is also included. The portfolio contains examples of designing an SSAS cube for a fictitious construction company including calculated members, partitioning, and a KPI. It also includes reports developed in SSRS, PPS dashboards, and an SSRS report deployed to SharePoint.
This document provides an introduction to writing MDX queries and member formulas. It covers basic MDX syntax including selecting members on columns and rows, specifying member names, understanding tuples and sets, and useful MDX functions like Children, Descendants, Generations, and Levels. It also discusses creating simple member formulas using relative and absolute references, and more advanced concepts like IIF, CASE, rolling calculations, and working with multiple time dimensions. Exercises are included to help apply the concepts.
This document provides an agenda and overview for a presentation on MDX query language for Essbase databases. It includes definitions of key MDX concepts like cubes, dimensions, and levels. It also describes the basic syntax of MDX queries with examples showing simple select statements with columns and rows axes using crossjoins and slices.
Presentation to the San Francisco SQL Server User Group on June 11, 2009.
Christian Wade of EMC discusses the numerous features in Analysis Services 2005 and 2008 as well as dimension/cube design.
Enhancing Dashboard Visuals with Multi-Dimensional Expressions (MDX)Daniel Upton
Here's an original presentation I gave at the SoCal Business Intelligence User Group in 2008. On reviewing it, and although the underlying platforms have evolved since then, the topic still seems relevant.
IBM Cognos Dimensional Dashboarding TechniquesSenturus
Learn best practices for creating interactive dashboards in the Cognos portal.
View the video recording and download this deck: http://www.senturus.com/resources/cognos-multi-dimensional-dashboarding-new-techniques/.
Senturus experts provide demonstrations using Report Studio, Cognos Connection, multi-dimensional expressions (MDX), Cognos portlets and inter-portlet communication techniques. All techniques covered are applicable to all versions of Cognos 8 and Cognos 10.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
The document provides an overview of the Miami-Dade Expressway Authority's (MDX) Fiscal Year 2015-2019 Work Program. Key points include: MDX maintains five expressways and is funded solely through toll revenues; the five-year, $879 million work program focuses on safety, system preservation, and mobility projects; and major projects include improvements to SR 836, planning for extensions of SR 924, and study of a potential SR 836 Southwest Extension.
This document contains examples from a portfolio of business intelligence projects including data modeling, SQL programming, SSIS, SSAS, SSRS, PPS, Excel Services, and SharePoint. It includes examples of relational and dimensional data models, SQL queries, SSIS packages for data integration and processing, an SSAS cube with calculations, KPIs and reports, Excel dashboards published to SharePoint using Excel Services, and reports and dashboards deployed to SharePoint.
The document describes a business intelligence suite developer. It lists the following core technologies the developer has explored and mastered: Microsoft SQL Server 2005, Microsoft SQL Server 2005 Integration Services, Microsoft SQL Server 2005 Analysis Services, Microsoft SQL Server 2005 Reporting Services, Microsoft Office SharePoint Server 2007, and Microsoft Office Performance Point Server. It then provides several examples of T-SQL queries, SSIS packages, MDX queries, and SSRS reports developed by this individual to demonstrate their skills in business intelligence development.
This document proposes generating additional revenue through an "Aerodynamic Landscape" idea. Specifically, it suggests creating digital twins for each aircraft serial number in a customer's fleet to allow real-time monitoring of aerodynamic performance. Metrics analysis and a "Digital Fit" approach would be used to analyze the business impact and advantages of the digital twin subscription model. The idea draws from the author's experience in aerodynamics, digital transformation, and operations management.
Nitin\'s Business Intelligence Portfolionpatel2362
The document provides samples of work from a Business Intelligence portfolio including T-SQL queries, MDX queries, SSIS packages, SSAS cube design, SSRS reports, and Excel Services reports with KPIs. It includes descriptions and screenshots of projects completed involving data integration, analysis, and reporting for a simulated construction company using SQL Server 2005 and Microsoft BI technologies.
PerformancePoint Server 2008 Project aimed to help organizations improve performance by creating dashboards to monitor, analyze, and plan using a single application. The project goals were to create dashboards showing company trends filtered by different options and see how key performance indicators could help organizations make better decisions. Sample MDX code is provided to filter labor costs by employee to analyze an individual employee's contribution across projects. Screenshots demonstrate sample KPIs in Excel and reports developed in Excel that were imported into a PerformancePoint dashboard deployed to SharePoint.
The document describes a project to develop an SSAS cube from four fact tables to support MDX queries and KPI reporting. It involved creating dimensions, hierarchies, and relationships in the data source view and cube. Sample MDX queries were developed utilizing measures, dimensions and hierarchies to retrieve and calculate data such as total costs, profits, and overhead by category and job.
Eileen Sauer completed a 400-hour Business Intelligence Masters Program covering Microsoft SQL Server 2005, Integration Services, Analysis Services, Reporting Services, SharePoint Server 2007, and PerformancePoint Server. For her capstone project, she designed and built a BI solution for a construction company tracking employee, customer, job, and timesheet data. Key aspects of the project included ETL processes, an SSAS cube with MDX queries and KPIs, SSRS reports, and dashboards in SharePoint and PerformancePoint.
Eileen Sauer completed a 400-hour Business Intelligence Masters Program covering Microsoft SQL Server 2005, Integration Services, Analysis Services, Reporting Services, SharePoint Server 2007, and PerformancePoint Server. For her capstone project, she designed and built a BI solution for a construction company to track employee, customer, job, and timesheet data. Key aspects of the project included ETL processes, an SSAS cube with MDX queries and KPIs, SSRS reports, and dashboards in SharePoint and PerformancePoint.
Lean Stack - A Story Of Continuous ImprovementLukas Fittl
Talk at Tools4AgileTeams '13 explaining how we iterated on our Lean Stack framework over the last 3 years.
From being risk-focused to focusing on the constraints in a business' customer factory.
The simple business plan template is based on Ash Maurya's lean canvas. If you need to write a business plan quickly or if your business is fairly simple and straightforward to explain, use our simple business plan template to write your business plan easily. Each section of a simple business plan is a quick summary and should not be longer than one page.
This simple business plan is not the detailed business plan that is being used to secure funding or loan. This simple business plan avoids long-worded summaries and detailed information about the business. This simple business plan is not even a document. It’s a collection of lists, tables, and bullet points of important aspects of your business strategy and management.
However, whenever there is a need for a formal business plan, this simple business plan can be an excellent first draft. Add descriptions and fill in the required information, make sure you have all the key business plan components, and you have the formal business plan ready that you need.
This document provides an overview of online analytical processing (OLAP). It defines OLAP as a process for analyzing multidimensional data to help decision makers. OLAP uses data warehouses to store historical data in a structured format. It allows for analytical queries and operations like aggregation, roll-up, drill-down and slicing and dicing of data. SQL extensions and OLAP functions further aid analysis. OLAP systems can be MOLAP, ROLAP or HOLAP based on their architecture and data storage methods. Commercial OLAP systems include IBM, Oracle and Microsoft products.
How to Realize an Additional 270% ROI on SnowflakeAtScale
Companies of all sizes have embraced the power, scale and ease of use of Snowflake’s cloud data platform, along with the promise of cost-savings. But if you aren’t careful, cloud compute usage can sneak up on you and leave you with runaway costs no matter what BI tool you are using.
The presentation from experts from Rakuten Rewards and AtScale shows practical techniques on how you can reduce unnecessary compute and boost BI performance to realize an additional 270% ROI on Snowflake. For the on-demand webinar, go to: https://www.atscale.com/resource/wbr-cloud-compute-cost-snowflake-tableau/
The business case is usually presented by senior executives within the organization to an identified business sponsor. It is the first document used in the project lifecycle and, once approved, allows the project to be formally defined.
While writing a business case, it may be required to undertake a formal feasibility study. This process involves a more detailed evaluation of the current business problem or opportunity, the different-different solutions available, the probability of a successful implementation for each solution, and the recommended best solution for implementation. The feasibility study provides a business case with more suitable solution options.
The business case is frequently referred to during the project development cycle. At each quality review point, the business case is used to determine whether or not the benefits, costs, risks, and issues prevalent match those listed in the business case.
Dear students
Call us at : 08263069601
Or
Mail us at “ help.mbaassignments@gmail.com ”
To get fully solved assignments
Send your semester & Specialization name to our mail id .
This document discusses connecting data between SharePoint, Tableau, and IBM BPM. It provides concepts and examples for extracting data from SharePoint into Tableau using a data extract utility. It also discusses capturing production data like story points and weighted hours to calculate costs. Finally, it addresses treating certain digital assets like portals and applications as capital expenditures to be depreciated over multiple years for accounting purposes.
Analytics Cloud - Comprehensive Look to Data Visualization Alithya
The document provides an overview of Oracle Analytics Cloud (OAC) presented by Alithya, an analytics solutions provider. It discusses the business need for analytics and integrated business analytics. It then summarizes OAC's key capabilities including data connection, preparation, exploration, and sharing. The presentation includes a demo of OAC's data visualization tool showing how to create visualizations from different data sources and perform analysis. It also discusses implementation options including an Oracle Analytics Cloud workshop.
Analytics Cloud Comprehensive Look to Data VisualizationAlithya
The Mandate for Business Analytics, Oracle Analytics Cloud (OAC) Overview, Brief OAC Screen Shot Demo – Data Visualizer
Presented at Oracle EPM Day Montreal 1/22/19 by Mike Killeen, SVP, Alithya
KPI Calculus for BSC Performance & Progress EstimationFarooq Omar
In the business space, a marker is a mathematical worth that is connected to some sort of cycle or business objective.
Its essential objective is to show a number that can give us a thought regarding the current presentation of the processor's business objective.
Addressing the inquiry concerning driving execution, it is right to state that driving presentation is handled into the slacking execution for a situation when the theory that remains behind the objective ends up being valid.
A more secure option for the KPI expression would be "pointer" or "metric."
There is a need for performance tasks that require students to apply their learning to real-world situations. The GRASPS framework can be used to design effective performance assessments. GRASPS stands for Goal, Role, Audience, Situation, Product, and Standards/Criteria. It provides guidelines for constructing scenarios that establish clear goals, roles for students, intended audiences, realistic situations, expected products, and standards for success. An example is given of a math performance task where students take on the role of an engineer designing a shipping container to maximize shipping volume and costs.
This portfolio contains examples of Carmen Faber's skills in developing Microsoft Business Intelligence packages using SQL Server Integration Services (SSIS). It includes SSIS packages to load and transform data from various sources into dimensional models for employee, client, project, and other data, with processes for validation, lookup, data conversion and loading into SQL Server databases. The packages are managed through a master package that runs the individual packages in sequence.
1. Carmen Faber MBA, OCP Wharton, NJ carmenfaber@gmail.com Business Intelligence Suite Developer 1 Is Business Intelligence in Your Business?
2. Portfolio Overview This portfolio contains selected examples of my development skills using Microsoft Business Intelligence SSAS and Sample MDX using BIDS SSAS using Microsoft Visual Studio page 3-20 MDX – Multi-Dimensional Queries Cube Structure Various sample Queries - page 21-43 Data Source View Dimension Usage Job Master Dimension Structure / Hierarchy Sample SSAS Calculation Calculation – Open Receivable Percent of Inventory Calculation – Total Cost Calculation - Overhead Percent of Total Cost Calculation - Total Profit Calculation - Profit Percent Calculation - Job Increase Calculation - Overhead Percent Increase Sample SSAS KPIs KPI Open Receivable KPI Job Increase KPI Profit Percent KPI Overhead Percent Increase KPI Profit Percent Partitions Perspective Test using Browser 2 Is Business Intelligence in Your Business?
3. SSAS Project All Works Cube (Measures/Fact and Dimension) 3 Is Business Intelligence in Your Business?
4. SSAS Project Data Source View 4 Is Business Intelligence in Your Business?
6. SSAS Project – Job Master Dimension Structure / Hierarchy 6 Is Business Intelligence in Your Business?
7. SSAS Project – Calculation – Open Receivable Percent of Inventory CASE WHEN [Measures].[Invoice Amount] = 0 THEN -1. ELSE ([Measures].[Invoice Amount]-[Measures].[Amount Received])/[Measures].[Invoice Amount] END 7 Is Business Intelligence in Your Business?
8. SSAS Project – Calculation – Total Cost [Measures].[Total Overhead] + [Measures].[Total Material Cost]+ [Measures].[Total Labor Cost] 8 Is Business Intelligence in Your Business?
9. SSAS Project – Overhead Percent of Total Cost CASE WHEN [Measures].[Total Overhead] / [Measures].[TotalCost] = 0 THEN 0 ELSE [Measures].[Total Overhead] / [Measures].[TotalCost] END 9 Is Business Intelligence in Your Business?
10. SSAS Project – Total Profit [Measures].[Total Labor Profit] + [Measures].[Total Material Profit] +[Measures].[Additional Labor Profit] 10 Is Business Intelligence in Your Business?
11. SSAS Project – Profit Percent CASE WHEN [Measures].[TotalCost] = 0 THEN '100%' ELSE [Measures].[TotalProfit] / ([Measures].[TotalCost] +[Measures].[TotalProfit]) END 11 Is Business Intelligence in Your Business?
12. SSAS Project – Job Increase [Measures].[Job Summary Facts Count] - ([Measures].[Job Summary Facts Count] , ParallelPeriod ([Fy Qtr].[Fy Qtr], 1)) 12 Is Business Intelligence in Your Business?
13. SSAS Project – Overhead Percent Increase CASE WHEN ([Measures].[Weekly Over Head] , ParallelPeriod ([Fy Qtr].[Fy Qtr], 1)) = 0 THEN 1 ELSE ([Measures].[Weekly Over Head] - ([Measures].[Weekly Over Hea d] , ParallelPeriod ([Fy Qtr].[Fy Qtr], 1))) /([Measures].[Weekly Over Head] , ParallelPeriod ([Fy Qtr].[Fy Qtr], 1)) END 13 Is Business Intelligence in Your Business?
14. SSAS Project – KPI Open Receivable CASE WHEN KPIVALUE("KPIOpenReceivable") <= KPIGOAL( "KPIOpenReceivable") THEN 1 WHEN KPIVALUE("KPIOpenReceivable")>= KPIGOAL( "KPIOpenReceivable") AND KPIVALUE("KPIOpenReceivable")<= KPIGOAL( "KPIOpenReceivable") * 2 THEN 0 WHEN KPIVALUE("KPIOpenReceivable")> KPIGOAL( "KPIOpenReceivable")* 2 THEN -1 END 14 Is Business Intelligence in Your Business?
15. SSAS Project – KPI Job Increase CASE WHEN KPIVALUE("KPIJobIncrease") >= KPIGOAL( "KPIJobIncrease") THEN 1 WHEN KPIVALUE("KPIJobIncrease") < KPIGOAL( "KPIJobIncrease") THEN -1 END 15 Is Business Intelligence in Your Business?
16. SSAS Project – KPI Profit Percent CASE WHEN KPIVALUE("KPIProfitPercent") > KPIGOAL( "KPIProfitPercent") THEN 1 WHEN KPIVALUE("KPIProfitPercent") >= (KPIGOAL( "KPIProfitPercent")/3) AND KPIVALUE("KPIProfitPercent") <= KPIGOAL( "KPIProfitPercent") THEN 0 WHEN KPIVALUE("KPIProfitPercent") < (KPIGOAL( "KPIProfitPercent")/ 3) THEN -1 END 16 Is Business Intelligence in Your Business?
17. SSAS Project – KPI Overhead Percent Increase CASE WHEN KPIVALUE("KPIOverheadPercentIncrease") <= KPIGOAL( "KPIOverheadPercentIncrease") THEN 1 WHEN KPIVALUE("KPIOverheadPercentIncrease") >= KPIGOAL( "KPIOverheadPercentIncrease") AND KPIVALUE("KPIOverheadPercentIncrease") <= KPIGOAL( "KPIOverheadPercentIncrease") * 1.5 THEN 0 WHEN KPIVALUE("KPIOverheadPercentIncrease") > KPIGOAL( "KPIOverheadPercentIncrease") * 1.5 THEN -1 END 17 Is Business Intelligence in Your Business?
18. SSAS Project – Partitions 18 Is Business Intelligence in Your Business?
19. SSAS Project – Perspective 19 Is Business Intelligence in Your Business?
20. SSAS Project – Test using Browser 20 Is Business Intelligence in Your Business?
21. MDX – Multi-Dimensional Queries List Hours Worked and Total Labor for each employee for 2005, -- along with the labor rate (Total labor / Hours worked). WITH MEMBER[LaborRate] AS ([Total Labor] / [Hoursworked]) SELECT {[Hoursworked],[Total Labor], [LaborRate]} ON COLUMNS, NON EMPTY( [Employees].[Full Name].members) ON ROWS FROM [All WorksCube] WHERE [Fy Year].[2005] 21 Is Business Intelligence in Your Business?
22. MDX – Multi-Dimensional Queries Retrieve total labor costs by County SELECT [Measures].[Total Labor Cost]ON COLUMNS, non empty([Job Master].[County Name].members) ON ROWS FROM [All WorksCube] 22 Is Business Intelligence in Your Business?
23. MDX – Multi-Dimensional Queries Retrieve total labor costs by Division SELECT [Measures].[Total Labor Cost]ON COLUMNS, non empty([Job Master].[Division Name].members) ON ROWS FROM [All WorksCube] 23 Is Business Intelligence in Your Business?
24. MDX – Multi-Dimensional Queries Retrieve total labor costs by Client Account grouping SELECT [Measures].[Total Labor Cost]ON COLUMNS, non empty([Job Master].[Client Groupings].members) ON ROWS FROM [All WorksCube] 24 Is Business Intelligence in Your Business?
25. MDX – Multi-Dimensional Queries Retrieve 3 meatures…total labor cost, total material cost, and total overhead by client SELECT {[Total Labor Cost], [Total Material Cost], [Total Overhead]}ON COLUMNS, non empty([Job Master].[Client Name].MEMBERS) ON ROWS FROM [All WorksCube] 25 Is Business Intelligence in Your Business?
26. MDX – Multi-Dimensional Queries Retrieve 3 meatures…total labor cost, total material cost, and total overhead by client Do the same (retrieve 3 measures) and add a 4th measure, -- a calculated measure, that adds all three costs WITH MEMBER [AllCosts] AS [Total Labor Cost]+ [Total Material Cost]+ [Total Overhead] SELECT {[Total Labor Cost], [Total Material Cost], [Total Overhead], [AllCosts]}ON COLUMNS, non empty([Job Master].[Client Name].MEMBERS) ON ROWS FROM [All WorksCube] 26 Is Business Intelligence in Your Business?
27. MDX – Multi-Dimensional Queries Retrieve and calculate the total costs, the total profit, and total profit %, for each individual job. The three are calculated as follows: -- Total costs = total labor cost + total material cost + total overhead cost -- Total profit = labor profit + material profit + additional labor overhead profit -- Total profit % = (total profit / (total cost + total profit)) * 100 WITH MEMBER [TotalCosts] AS [Total Labor Cost]+ [Total Material Cost]+ [Total Overhead] MEMBER [TotalProfit] AS [Total Labor Profit]+ [Total Material Profit]+ [Additional Labor Profit] MEMBER [ProfitPct] AS ([TotalProfit] / ([TotalCosts]+[TotalProfit]) ) , format_string = 'percent‘ SELECT {[TotalCosts], [TotalProfit], [ProfitPct] }ON COLUMNS, NON EMPTY ([Job Master].[Description].members) HAVING [ProfitPct] > 0 ON ROWS FROM [All WorksCube] 27 Is Business Intelligence in Your Business?
28. MDX – Multi-Dimensional Queries Retrieve and calculate the total costs, the total profit, and total profit %, for each individual job. The three are calculated as follows: -- Total costs = total labor cost + total material cost + total overhead cost -- Total profit = labor profit + material profit + additional labor overhead profit -- Total profit % = (total profit / (total cost + total profit)) * 100 Do the same thing as above, but group it by client WITH MEMBER [TotalCosts] AS [Total Labor Cost]+ [Total Material Cost]+ [Total Overhead] MEMBER [TotalProfit] AS [Total Labor Profit]+ [Total Material Profit]+ [Additional Labor Profit] MEMBER [ProfitPct] AS ([TotalProfit] / ([TotalCosts]+[TotalProfit]) ) , format_string = 'percent' SELECT {[TotalCosts], [TotalProfit], [ProfitPct] }ON COLUMNS, NON EMPTY ([Job Master].[Client Name].members) ON ROWS FROM [All WorksCube] 28 Is Business Intelligence in Your Business?
29. MDX – Multi-Dimensional Queries Display a count of Jobs by Client in alphabetical order. Display NULLs as 0. WITH MEMBER [JobSummaryFactsCount] as IIF ([MEASURES].[Job Summary Facts Count] > 0, [MEASURES].[Job Summary Facts Count], 0) SELECT [JobSummaryFactsCount] ON COLUMNS, [Job Master].[Client Name].MEMBERS ON ROWS FROM [All WorksCube] 29 Is Business Intelligence in Your Business?
30. MDX – Multi-Dimensional Queries Retrieve all Clients with a Total Labor cost to date greater than 5,000, and the word 'INC' appears in the client name SELECT [Total Labor Cost]ON COLUMNS, filter([Job Master].[Client Name].CHILDREN, Instr([Job Master].[Client Name].CurrentMember.Name, "INC") AND [Total Labor Cost]> 5000 ) ON ROWS FROM [All WorksCube] 30 Is Business Intelligence in Your Business?
31. MDX – Multi-Dimensional Queries List the jobs that make up the top 30% of total invoice amount Select [Measures].[Invoice Amount] on columns, TopPercent([Job Master].[Job Master].children, 30,[Measures].[Invoice Amount]) on Rows from[All WorksCube] 31 Is Business Intelligence in Your Business?
32. MDX – Multi-Dimensional Queries Show Overhead by Overhead Category for Q3 and Q4 2005 (hint, use the FY Qtr as a dimension) SELECT {[Fy Qtr].[2005 Q3], [Fy Qtr].&[2005 Q4]} ON COLUMNS, non empty ([Overhead].[Overhead].MEMBERS) ON ROWS FROM [All WorksCube] WHERE [Weekly Over Head] 32 Is Business Intelligence in Your Business?
33. MDX – Multi-Dimensional Queries Show Overhead by Overhead Category for Q3 and Q4 2005, and also show the % of change between the two) WITH member [ovheadCurrentPeriod] as ([Measures].[Weekly Over Head], [Fy Qtr].currentmember) member [ovheadPriorPeriod] as ([Measures].[Weekly Over Head], [Fy Qtr].prevmember) member [PctofCHG] AS iif([ovheadPriorPeriod], ([ovheadCurrentPeriod] - [ovheadPriorPeriod])/ [ovheadPriorPeriod], null), format_string = '0.00%;;;/A' SELECT {[ovheadCurrentPeriod], [ovheadPriorPeriod], [PctofCHG] } ON COLUMNS, non empty([Overhead].[Description].MEMBERS) ON ROWS FROM [All WorksCube] WHERE [Fy Qtr].[2005 Q4] 33 Is Business Intelligence in Your Business?
34. MDX – Multi-Dimensional Queries Show Overhead by Overhead Category for all of 2005, order by Overhead $$ amount descending WITH SET [OrderOverhead] AS ORDER([Overhead].[Overhead].MEMBERS, [Weekly Over Head], DESC) SELECT [Weekly Over Head] ON COLUMNS, non empty ( [OrderOverhead]) ON ROWS FROM [All WorksCube] WHERE [Fy Year].[2005] 34 Is Business Intelligence in Your Business?
35. MDX – Multi-Dimensional Queries Show Material Purchase amounts by Material Type for 2005. The result set should have 1 column for the purchase amounts for Fuel, Materials, and petty Cash SELECT [Purchase Amount] ON COLUMNS, [Material Types].[Description].members ON ROWS FROM [All WorksCube] 35 Is Business Intelligence in Your Business?
36. MDX – Multi-Dimensional Queries Show Material purchase amounts for 2005, broken out by Material Purchase type and client. (for instance, Fuel for client A, B, C…Petty Cash for client A, B, C, etc.) Display NULLs as $0.00 WITH MEMBER [PurchaseAmt] as IIF ([MEASURES].[Purchase Amount] > 0, [Purchase Amount], 0), format_string = 'currency' SELECT [PurchaseAmt] ON COLUMNS, ([Material Types].[Description].children, [Client Name].children) ON ROWS FROM [All WorksCube] WHERE [Fy Year].[2005] 36 Is Business Intelligence in Your Business?
37. MDX – Multi-Dimensional Queries Show a list of total client material purchases for 2005, in descending purchase amount order. The result set should show at the top which client required the most materials. WITH SET [OrderClientPurchAmt] AS order( [Client Name].children, [Purchase Amount], desc) SELECT [Purchase Amount] ON COLUMNS, non empty ( [OrderClientPurchAmt] ) ON ROWS FROM [All WorksCube] WHERE [Fy Year].[2005] 37 Is Business Intelligence in Your Business?
38. MDX – Multi-Dimensional Queries -- Show jobs in order of purchase amount and then show the -- breakdown in each job of material type (for instance, Job A, total purchase amount, amount for fuel, amount for materials, amount for petty cash, etc.) The general order should be by -- total purchase amount, so that the top of the result set -- shows the jobs that required the highest purchase amounts WITH SET [OrderedJOB] AS ORDER( [Job Master].[Job Master].CHILDREN, [Purchase Amount], desc) MEMBER [PurchaseAmt] AS IIF ([Purchase Amount]> 0, [Purchase Amount], 0), format_string = 'currency' SELECT [PurchaseAmt] ON COLUMNS, ([OrderedJOB], [Material Types].[Description].members) ON ROWS FROM [All WorksCube] 38 Is Business Intelligence in Your Business?
39. MDX – Multi-Dimensional Queries List Hours Worked and Total Labor for each employee for 2005, along with the labor rate (Total labor / Hours worked). WITH MEMBER[LaborRate] AS ([Total Labor] / [Hoursworked]) SELECT {[Hoursworked],[Total Labor], [LaborRate]} ON COLUMNS, NON EMPTY( [Employees].[Full Name].members) ON ROWS FROM [All WorksCube] WHERE [Fy Year].[2005] 39 Is Business Intelligence in Your Business?
40. MDX – Multi-Dimensional Queries List Hours Worked and Total Labor for each employee for 2005, along with the labor rate (Total labor / Hours worked). -- sort the employees by labor rate descending, to see the employees with -- the highest labor rate at the top. WITH MEMBER[LaborRate] AS ([Total Labor] / [Hoursworked]) SELECT {[Hoursworked],[Total Labor], [LaborRate]} ON COLUMNS, NON EMPTY( ORDER ([Employees].[Full Name].members, [LaborRate], bDESC) ) ON ROWS FROM [All WorksCube] WHERE [Fy Year].[2005] 40 Is Business Intelligence in Your Business?
41. MDX – Multi-Dimensional Queries For 2005, show Total Hours worked, total labor dollars, and total labor rate for contractors (employee flag is false) and employees (employee flag is true) WITH MEMBER[LaborRate] AS ([Total Labor] / [Hoursworked]) SELECT {[Hoursworked],[Total Labor], [LaborRate]} ON COLUMNS, non empty ([Employees].[Employee Flag].members) ON ROWS FROM [All WorksCube] WHERE [Fy Year].[2005] 41 Is Business Intelligence in Your Business?
42. MDX – Multi-Dimensional Queries For 2005, show the job and the top three employees who worked the most hours. -- Show the jobs in job order, and within the job show the employees in hours worked order WITH SET [JobTop3emp] AS GENERATE( [Job Master].[Description].children , ([Job Master].[Description].currentmember, topcount( [Employees].[Employees].children, 3, [Hoursworked]) ) ) SELECT [Hoursworked] ON COLUMNS, non empty ( [JobTop3emp] ) ON ROWS FROM [All WorksCube] WHERE [Fy Year].[2005] 42 Is Business Intelligence in Your Business?
43. MDX – Multi-Dimensional Queries Show All employees for 2005 Q4, and four periods ago, -- for total hours worked in the Quarter -- Display NULLs as 0 with member [HrsWrkParamWhereCLausewhichisQ42005] as IIF ( ([Fy Qtr].currentmember,[Measures].[Hoursworked] ) > 0, ([Fy Qtr].currentmember,[Measures].[Hoursworked] ), 0) member [HrsWrk4PeriodsAgo] as IIF ( ([Measures].[Hoursworked] , ParallelPeriod ([Fy Qtr].[Fy Qtr], 4)) > 0, ([Measures].[Hoursworked] , ParallelPeriod ([Fy Qtr].[Fy Qtr], 4)), 0) SELECT { [HrsWrk4PeriodsAgo] , [HrsWrkParamWhereCLausewhichisQ42005]} ON COLUMNS, [Employees].[Full Name].children ON ROWS FROM [All WorksCube] WHERE [Fy Qtr].[2005 Q4] 43 Is Business Intelligence in Your Business?
44. Thank you for Your Time I hope you enjoyed your few minutes of viewing what took intense months of training to accomplished 44 Is Business Intelligence in Your Business?