SSRS Report with Parameters and Data Filtration

Oct 27, 20180 likes167 views

This document outlines how to use parameters and data filtration in SQL Server Reporting Services (SSRS) reports. It discusses using the AdventureWorks sample database with SSRS, designing queries to retrieve product category, subcategory, and product data, configuring cascading multi-valued parameters to filter the data, and displaying the selected parameter values in the report. Code examples are provided to retrieve the necessary data and configure the parameters.

SSRS
Parameters and Data Filtration
Rev 1407R04
Naji El Kotob
naji [@] dotnetheroes.com
www.DotNETHeroes.com

Outlines
 Introduction to SSRS
 AdventureWorks Database
 Datasets
 Multi-Valued and Cascading Parameters Report
 Interactive DEMO
 Q&A
 References

Adventure Works Database
 Adventure Works Cycles, the fictitious company on which the AdventureWorks
sample databases are based, is a large, multinational manufacturing
company.
 http://msftdbprodsamples.codeplex.com/

SSRS Report with Parameters and Data Filtration

ProductCategoriesDataSet
SELECT
Production.ProductCategory.ProductCategoryID
,Production.ProductCategory.Name
FROM
Production.ProductCategory

ProductSubCategoriesDataSet
SELECT
Production.ProductSubcategory.ProductSubcategoryID
,Production.ProductSubcategory.ProductCategoryID
,Production.ProductSubcategory.Name
FROM
Production.ProductSubcategory
WHERE
Production.ProductSubcategory.ProductCategoryID IN (@ProductCategoryID)

ProductsDataSet
SELECT
Production.Product.ProductID
,Production.ProductCategory.Name AS [ProductCategory Name]
,Production.ProductSubcategory.Name AS [ProductSubcategory Name]
,Production.Product.Name AS [Product Name]
,Production.Product.Color ,Production.Product.ListPrice
FROM
Production.ProductSubcategory
INNER JOIN Production.Product
ON Production.ProductSubcategory.ProductSubcategoryID = Production.Product.ProductSubcategoryID
INNER JOIN Production.ProductCategory
ON Production.ProductSubcategory.ProductCategoryID = Production.ProductCategory.ProductCategoryID
WHERE
Production.ProductSubcategory.ProductSubcategoryID IN (@ProductSubcategoryID)

Displaying Single & Multi-Valued Report
Parameter Selections
 ="Category(s) Selected: " & JOIN(Parameters!ProductCategoryID.Label, ", ")
 ="Subcategory(s) Selected: " & JOIN(Parameters!ProductSubcategoryID.Label, ", ")

More touches!
="Category(s) Selected (" &
Parameters!ProductCategoryID.Count.ToString & "):
" & JOIN(Parameters!ProductCategoryID.Label, ", ")

Q&A
 Please send your feedback to naji [@] dotnetheroes.com

References
 http://www.sqlchick.com/entries/2012/2/25/displaying-single-multi-valued-
report-parameter-selections-i.html
 Samples and Walkthroughs - http://msdn.microsoft.com/en-
us/library/ms251686(v=vs.90).aspx

This document provides an overview of data warehousing and data mining. It discusses key topics such as the definition of a data warehouse, its characteristics and architectures. It also describes how data is stored and modeled in a data warehouse. The document then covers data mining, outlining its process and elements. It discusses advantages of both data warehousing and data mining such as enhanced business intelligence and improved decision making. Disadvantages like privacy and security issues are also presented.

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!

ER/Studio and DB PowerStudio Launch Webinar: Big Data, Big Models, Big News! Embarcadero Technologies

Training on Microsoft SQL Server(older version).pptxnaibedyakar00

Business Intelligence PortfolioBob Litsinger

The document provides examples of the author's business intelligence skills, including data modeling, SQL programming, SQL Server Integration Services, SQL Server Analysis Services, MDX programming, SQL Server Reporting Services, Excel Power Pivot, Performance Point Services, and SharePoint Services. Examples include data warehouse modeling, stored procedures, SSIS packages, SSAS cubes and MDX queries, SSRS reports, Power Pivot reports, PerformancePoint dashboards, and SharePoint dashboards.

Retail referencearchitecture productcatalogMongoDB

During this session we will cover the best practices for implementing a product catalog with MongoDB. We will cover how to model an item properly when it can have thousands of variations and thousands of properties of interest. You'll learn how to index properly and allow for faceted search with milliseconds response latency and how to implement per-store, per-sku pricing while still keeping a sane number of documents. We will also cover operational considerations, like how to bring the data closer to users to cut down the network latency.

Create and Maintain COMPLEX HIERARCHIES easilySreenivasulu Kandakuru PMP®

Microsoft Data Science Technologies 201608Mark Tabladillo

Delivered to SQL Saturday Columbus, GA Microsoft provides several technologies which can be used for casual to serious data science. This presentation provides an authoritative overview of two major categories: products and services. The products include: SQL Server Analysis Services, Excel Add-in for SSAS, Semantic Search, SQL Server R Services, Microsoft R Technologies, and F#. The services include Cortana Intelligence and Bing Predicts. These technologies have been used by the presenter in various companies and industries, and he will be speaking toward how Microsoft uses these technologies today for its largest Azure customers.

Database@Home : The Future is Data DrivenTammy Bednar

These slides were presented during the Database@Home : Data-Driven Apps event. This session will discuss the importance of data to an organisation and the need to build applications where the value within that data can easily be exploited. To achieve that aim we need to start building applications that benefit from the flexibility of new development paradigms but don't create artificial barriers of complexity that stop us from easily responding to change within our organisations.

Boosting MySQL with Vector Search Scale22X 2025.pdfAlkin Tezuysal

As the demand for vector databases and Generative AI continues to rise, integrating vector storage and search capabilities into traditional databases has become increasingly important. This session introduces the *MyVector Plugin*, a project that brings native vector storage and similarity search to MySQL. Unlike PostgreSQL, which offers interfaces for adding new data types and index methods, MySQL lacks such extensibility. However, by utilizing MySQL's server component plugin and UDF, the *MyVector Plugin* successfully adds a fully functional vector search feature within the existing MySQL + InnoDB infrastructure, eliminating the need for a separate vector database. The session explains the technical aspects of integrating vector support into MySQL, the challenges posed by its architecture, and real-world use cases that showcase the advantages of combining vector search with MySQL's robust features. Attendees will leave with practical insights on how to add vector search capabilities to their MySQL

Wix Machine Learning - Ran RomanoWix Engineering

Ran Romano leads Wix's ML engineering team. The presentation discusses Wix's ML platform, which allows data scientists to build, deploy, maintain and monitor ML models. The platform includes an offline and online feature store to prepare and serve features for models. It aims to get new models into production within 3 weeks. Various models in use at Wix are discussed, including for churn prediction, semantic search, and image analysis. Future plans include improved model CI/CD and auto feature discovery.

SQL Server 2008 Data Miningllangit

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.

Freeing Yourself from an RDBMS ArchitectureDavid Hoerster

SQL Server 2008 Data Miningllangit

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.

SQL Server 2008 Data Miningllangit

ASHviz - Dats visualization research experiments using ASH dataJohn Beresniewicz

RMOUG Training Days 2020 abstract: The Active Session History (ASH) mechanism is a rich source of fine-grained data about database activity, and is the lynchpin for many database performance management features in the Diagnostic and Tuning packs. Many interesting stories about happenings in the database are buried in ASH waiting to be revealed, and data visualization is key to sifting these out from the high dimensionality and volume of ASH data. The session will cover a number of data visualization experiments conducted using a single ASH dump with an emphasis on the iterative process of discovering useful data visualizations.

Building Modern Websites with ASP.NET by Rachel Appel.NET Conf UY

This document provides an overview of building modern websites with ASP.NET MVC, including discussions of models, controllers, views, routing, Entity Framework, and view models. It describes models as the application's data expressed as classes, controllers as handling requests and routing, and views as the UI layer that renders models. It also covers Entity Framework for database mapping, RESTful routing, and using view models to promote separation of concerns.

IBM Insight 2015 - 1824 - Using Bluemix and dashDB for Twitter AnalysisTorsten Steinbach

Using Bluemix and dashDB for Twitter Analysis This document discusses using IBM's Bluemix and dashDB services for Twitter analysis. It provides an overview of the IBM Insights for Twitter service in Bluemix, which allows querying and searching over enriched Twitter data stored in dashDB. Examples are given of queries that can be performed, such as searching for tweets about an upcoming movie within a time frame or searching for tweets with positive sentiment about a product. The document also discusses loading Twitter data into dashDB using a Bluemix app and performing predictive analytics on the data using built-in R and Python capabilities in dashDB.

Designer's Favorite New Features in SQLServerKaren Lopez

Dublin Ireland Spark Meetup October 15, 2015eddiebaggott

This document discusses Apache Spark DataFrames and their use for fraud detection. It provides an overview of DataFrames, how they can be created from various data sources and used for data aggregation, filtering, and querying. Examples are given for creating DataFrames from text files, performing SQL queries, and using DataFrames for profiling, charting, and data quality checks. A variety of fraud detection applications for DataFrames are also outlined.

Quark Virtualization Engine for Analytics DataWorks Summit/Hadoop Summit

Rajat Venkatesh from Qubole presented on Quark, a virtualization engine for analytics. Quark uses a multi-store architecture to optimize queries using materialized views, predicate injection, and denormalized/sorted tables. It supports multiple SQL and storage engines. The roadmap includes improvements to the cost-based optimizer, support for OLAP cubes, and developing Quark as a service. Coordinates for the Quark GitHub and mailing list were provided.

Squirrel – Enabling Accessible Analytics for AllSudipta Mukherjee

Squirrel is a .NET library that provides tools for data processing, analytics, and visualization using small data. It features I/O blocks, data modeling, database connectors, data generation, data cleansing, statistics/math functions, and visualization adaptors. Squirrel also supports mobile integration through messaging with Android devices. Future releases will enhance connectors, provide a single API for visualization, and add voice/gesture recognition capabilities.

Why is data independence (still) so important? Optiq and Apache Drill.Julian Hyde

Introduction To Sql Server Data MiningHugo Olivera Alonso

This document introduces data mining with SQL Server. It discusses how data mining can provide business insights by analyzing large amounts of data. It describes how SQL Server integrates data acquisition, transformation, discovery, and presentation capabilities for data mining. It also provides an example of how a customer used SQL Server to analyze transaction and stock data to increase sales and profits.

Why Standards-Based Drivers Offer Better API IntegrationNordic APIs

As enterprises grow, so too does the number and variety of data sources they use to drive business. The average company is using at least sixteen SaaS applications and has data in at least that many on-premises data stores and internal apps. With such disparate data, each tied to a unique API, integrating, managing, and maintaining integrations for all of a company’s data creates a whole new set of challenges. Thankfully, solutions exist that enable enterprises to rely on data to drive business without causing undue strain. In this session, we’ll explore and compare the different options for solving the data integration problem and explain why you should be using standards-based drivers to abstract your API integrations.

Odoo - Educational Account for Students and Teachers Ver. 2.0Naji El Kotob

This document provides an overview of the Odoo ERP system. It describes what Odoo is, its major releases over time, how to access a demo version, and how students and teachers can sign up for an educational account to use Odoo's full features for learning purposes. It also outlines various apps in Odoo, how to navigate between them, and next steps users can take to learn more about and start using Odoo.

Google search - Tips and TricksNaji El Kotob

This document outlines Google search tips and tricks. It discusses the Google search results page layout, how to perform searches, using punctuation and operators to refine searches, quick answers, filtering results, and advanced search options. Tips provided include using fewer search terms initially, the auto-complete feature, phrase searching with quotes, wildcard searches, and excluding terms. Advanced topics like site searching and related searches are also covered.

More Related Content

Similar to SSRS Report with Parameters and Data Filtration (20)

Retail referencearchitecture productcatalogMongoDB

Create and Maintain COMPLEX HIERARCHIES easilySreenivasulu Kandakuru PMP®

Microsoft Data Science Technologies 201608Mark Tabladillo

Database@Home : The Future is Data DrivenTammy Bednar

Boosting MySQL with Vector Search Scale22X 2025.pdfAlkin Tezuysal

Wix Machine Learning - Ran RomanoWix Engineering

SQL Server 2008 Data Miningllangit

Freeing Yourself from an RDBMS ArchitectureDavid Hoerster

SQL Server 2008 Data Miningllangit

ASHviz - Dats visualization research experiments using ASH dataJohn Beresniewicz

Building Modern Websites with ASP.NET by Rachel Appel.NET Conf UY

IBM Insight 2015 - 1824 - Using Bluemix and dashDB for Twitter AnalysisTorsten Steinbach

Designer's Favorite New Features in SQLServerKaren Lopez

Dublin Ireland Spark Meetup October 15, 2015eddiebaggott

Quark Virtualization Engine for Analytics DataWorks Summit/Hadoop Summit

Squirrel – Enabling Accessible Analytics for AllSudipta Mukherjee

Why is data independence (still) so important? Optiq and Apache Drill.Julian Hyde

Introduction To Sql Server Data MiningHugo Olivera Alonso

Why Standards-Based Drivers Offer Better API IntegrationNordic APIs

Retail referencearchitecture productcatalogMongoDB

Create and Maintain COMPLEX HIERARCHIES easilySreenivasulu Kandakuru PMP®

Microsoft Data Science Technologies 201608Mark Tabladillo

Database@Home : The Future is Data DrivenTammy Bednar

Boosting MySQL with Vector Search Scale22X 2025.pdfAlkin Tezuysal

Wix Machine Learning - Ran RomanoWix Engineering

SQL Server 2008 Data Miningllangit

Freeing Yourself from an RDBMS ArchitectureDavid Hoerster

SQL Server 2008 Data Miningllangit

ASHviz - Dats visualization research experiments using ASH dataJohn Beresniewicz

Building Modern Websites with ASP.NET by Rachel Appel.NET Conf UY

IBM Insight 2015 - 1824 - Using Bluemix and dashDB for Twitter AnalysisTorsten Steinbach

Designer's Favorite New Features in SQLServerKaren Lopez

Dublin Ireland Spark Meetup October 15, 2015eddiebaggott

Quark Virtualization Engine for Analytics DataWorks Summit/Hadoop Summit

Squirrel – Enabling Accessible Analytics for AllSudipta Mukherjee

Why is data independence (still) so important? Optiq and Apache Drill.Julian Hyde

Introduction To Sql Server Data MiningHugo Olivera Alonso

Why Standards-Based Drivers Offer Better API IntegrationNordic APIs

More from Naji El Kotob (9)

Odoo - Educational Account for Students and Teachers Ver. 2.0Naji El Kotob

Google search - Tips and TricksNaji El Kotob

Microsoft SQL Server - Files and FilegroupsNaji El Kotob

This document discusses files and filegroups in Microsoft SQL Server. It begins by explaining pages and extents, which are the basic units of data storage and management in SQL Server. It then defines files, filegroups, and their default extensions (.mdf, .ndf, .ldf). The document outlines the differences between primary and secondary filegroups and provides recommendations for using files and filegroups to improve performance, enable backup/restore strategies, and follow design rules. It also discusses read-only filegroups and compares the benefits of using filegroups versus RAID storage configurations.

tempdb and Performance KeysNaji El Kotob

This document outlines best practices for configuring and managing the tempDB database in SQL Server. It discusses using tempDB for sorting operations, querying size and location information with T-SQL, autogrowth settings, shrinking tempDB with DBCC, best practice guidelines, optimizing performance by adjusting size and placement, changing the location, adding new files, and demonstrates these tasks in a live demo.

Microsoft SQL Server 2012 Components and Tools (Quick Overview) - Rev 1.3Naji El Kotob

This document provides an overview of SQL Server tools and core services. It describes several Microsoft SQL Server tools, including SQL Server Management Studio (SSMS), SQL Server Configuration Manager, and SQL Profiler. It also outlines the main SQL Server core services: the Database Engine, SQL Server Integration Services (SSIS), SQL Server Reporting Services (SSRS), and SQL Server Analysis Services (SSAS). The document indicates that it will include an interactive demonstration exploring these SQL Server components.

T-SQL Data Types (Quick Overview)Naji El Kotob

This document discusses data types in databases. It describes numeric, character, temporal, and miscellaneous data types. It also covers precision, scale, length, custom data types, special column types like identity and timestamp columns. The document explains CAST and CONVERT functions that explicitly convert data between types and provides syntax examples. It demonstrates converting date/time values to different formats and casting between different data types.

Robots and-sitemap - Version 1.0.1Naji El Kotob

The document discusses search engine optimization and how robots.txt and sitemaps are used to help search engines properly index websites. It defines robots.txt as a file that search engines use to see what pages should be indexed or not indexed, and sitemaps as an XML file that provides search engines a list of pages on a website. It also provides examples of robots.txt and sitemap formats and discusses how to dynamically generate robots.txt files and sitemap generators.

Practical MS SQL IntroductionNaji El Kotob

This document outlines topics related to database design, performance, and reporting using Microsoft SQL Server. The topics covered include database fundamentals, relational database objects, SQL Server design and architecture, database normalization, SQL, optimization techniques, and reporting tools. Database concepts such as tables, keys, indexes, and relationships are defined. The benefits of normalization for organizing data efficiently without redundancy are also discussed.

MVC and Razor - Doc. v1.2Naji El Kotob

The document discusses Razor and MVC concepts like layouts, sections, partial views, and HTML helpers. It explains that MVC separates an application into the model, view, and controller. The view handles display, the controller handles user interaction, and the model handles application logic and data access. Razor is a view engine that allows embedding C#/VB code in HTML views. Partial views, layouts, and sections help reuse view code across pages.

Odoo - Educational Account for Students and Teachers Ver. 2.0Naji El Kotob

Google search - Tips and TricksNaji El Kotob

Microsoft SQL Server - Files and FilegroupsNaji El Kotob

tempdb and Performance KeysNaji El Kotob

Microsoft SQL Server 2012 Components and Tools (Quick Overview) - Rev 1.3Naji El Kotob

T-SQL Data Types (Quick Overview)Naji El Kotob

Robots and-sitemap - Version 1.0.1Naji El Kotob

Practical MS SQL IntroductionNaji El Kotob

MVC and Razor - Doc. v1.2Naji El Kotob

Recently uploaded (20)

Handling Multiple Choice Responses: Fortune Effiong.pptxAuthorAIDNationalRes

pulse ppt.pptx Types of pulse , characteristics of pulse , Alteration of pulsesushreesangita003

New Microsoft PowerPoint Presentation.pptxmilanasargsyan5

Geography Sem II Unit 1C Correlation of Geography with other school subjectsProfDrShaikhImran

Sinhala_Male_Names.pdf Sinhala_Male_Namekeshanf79

Presentation of the MIPLM subject matter expert Erdem KayaMIPLM

Biophysics Chapter 3 Methods of Studying Macromolecules.pdfPKLI-Institute of Nursing and Allied Health Sciences Lahore , Pakistan.

This chapter provides an in-depth overview of the viscosity of macromolecules, an essential concept in biophysics and medical sciences, especially in understanding fluid behavior like blood flow in the human body. Key concepts covered include: ✅ Definition and Types of Viscosity: Dynamic vs. Kinematic viscosity, cohesion, and adhesion. ⚙️ Methods of Measuring Viscosity: Rotary Viscometer Vibrational Viscometer Falling Object Method Capillary Viscometer 🌡️ Factors Affecting Viscosity: Temperature, composition, flow rate. 🩺 Clinical Relevance: Impact of blood viscosity in cardiovascular health. 🌊 Fluid Dynamics: Laminar vs. turbulent flow, Reynolds number. 🔬 Extension Techniques: Chromatography (adsorption, partition, TLC, etc.) Electrophoresis (protein/DNA separation) Sedimentation and Centrifugation methods.

Anti-Depressants pharmacology 1slide.pptxMayuri Chavan

Social Problem-Unemployment .pptx notes for Physiotherapy StudentsDrNidhiAgarwal

Unemployment is a major social problem, by which not only rural population have suffered but also urban population are suffered while they are literate having good qualification.The evil consequences like poverty, frustration, revolution result in crimes and social disorganization. Therefore, it is necessary that all efforts be made to have maximum. employment facilities. The Government of India has already announced that the question of payment of unemployment allowance cannot be considered in India

Introduction to Vibe Coding and Vibe EngineeringDamian T. Gordon

One Hot encoding a revolution in Machine learningmomer9505

P-glycoprotein pamphlet: iteration 4 of 4 finalbs22n2s

Operations Management (Dr. Abdulfatah Salem).pdfArab Academy for Science, Technology and Maritime Transport

Presentation on Tourism Product Development By Md Shaifullar RabbiMd Shaifullar Rabbi

How to track Cost and Revenue using Analytic Accounts in odoo Accounting, App...Celine George

Analytic accounts are used to track and manage financial transactions related to specific projects, departments, or business units. They provide detailed insights into costs and revenues at a granular level, independent of the main accounting system. This helps to better understand profitability, performance, and resource allocation, making it easier to make informed financial decisions and strategic planning.

Metamorphosis: Life's Transformative JourneyArshad Shaikh

apa-style-referencing-visual-guide-2025.pdfIshika Ghosh

Title: A Quick and Illustrated Guide to APA Style Referencing (7th Edition) This visual and beginner-friendly guide simplifies the APA referencing style (7th edition) for academic writing. Designed especially for commerce students and research beginners, it includes: ✅ Real examples from original research papers ✅ Color-coded diagrams for clarity ✅ Key rules for in-text citation and reference list formatting ✅ Free citation tools like Mendeley & Zotero explained Whether you're writing a college assignment, dissertation, or academic article, this guide will help you cite your sources correctly, confidently, and consistent. Created by: Prof. Ishika Ghosh, Faculty. 📩 For queries or feedback: [email protected]

Phoenix – A Collaborative Renewal of Children’s and Young People’s Services C...Library Association of Ireland

Niamh Lucey, Mary Dunne. Health Sciences Libraries Group (LAI). Lighting the ...Library Association of Ireland

How to manage Multiple Warehouses for multiple floors in odoo point of saleCeline George

Handling Multiple Choice Responses: Fortune Effiong.pptxAuthorAIDNationalRes

pulse ppt.pptx Types of pulse , characteristics of pulse , Alteration of pulsesushreesangita003

New Microsoft PowerPoint Presentation.pptxmilanasargsyan5

Geography Sem II Unit 1C Correlation of Geography with other school subjectsProfDrShaikhImran

Sinhala_Male_Names.pdf Sinhala_Male_Namekeshanf79

Presentation of the MIPLM subject matter expert Erdem KayaMIPLM

Biophysics Chapter 3 Methods of Studying Macromolecules.pdfPKLI-Institute of Nursing and Allied Health Sciences Lahore , Pakistan.

Anti-Depressants pharmacology 1slide.pptxMayuri Chavan

Social Problem-Unemployment .pptx notes for Physiotherapy StudentsDrNidhiAgarwal

Introduction to Vibe Coding and Vibe EngineeringDamian T. Gordon

One Hot encoding a revolution in Machine learningmomer9505

P-glycoprotein pamphlet: iteration 4 of 4 finalbs22n2s

Operations Management (Dr. Abdulfatah Salem).pdfArab Academy for Science, Technology and Maritime Transport

Presentation on Tourism Product Development By Md Shaifullar RabbiMd Shaifullar Rabbi

How to track Cost and Revenue using Analytic Accounts in odoo Accounting, App...Celine George

Metamorphosis: Life's Transformative JourneyArshad Shaikh

apa-style-referencing-visual-guide-2025.pdfIshika Ghosh

Phoenix – A Collaborative Renewal of Children’s and Young People’s Services C...Library Association of Ireland

Niamh Lucey, Mary Dunne. Health Sciences Libraries Group (LAI). Lighting the ...Library Association of Ireland

How to manage Multiple Warehouses for multiple floors in odoo point of saleCeline George

SSRS Report with Parameters and Data Filtration

1. SSRS Parameters and Data Filtration Rev 1407R04 Naji El Kotob naji [@] dotnetheroes.com www.DotNETHeroes.com

2. Outlines  Introduction to SSRS  AdventureWorks Database  Datasets  Multi-Valued and Cascading Parameters Report  Interactive DEMO  Q&A  References

3. Adventure Works Database  Adventure Works Cycles, the fictitious company on which the AdventureWorks sample databases are based, is a large, multinational manufacturing company.  http://msftdbprodsamples.codeplex.com/

4. Design and Build your Queries

6. ProductCategoriesDataSet SELECT Production.ProductCategory.ProductCategoryID ,Production.ProductCategory.Name FROM Production.ProductCategory

7. ProductSubCategoriesDataSet SELECT Production.ProductSubcategory.ProductSubcategoryID ,Production.ProductSubcategory.ProductCategoryID ,Production.ProductSubcategory.Name FROM Production.ProductSubcategory WHERE Production.ProductSubcategory.ProductCategoryID IN (@ProductCategoryID)

9. ProductsDataSet SELECT Production.Product.ProductID ,Production.ProductCategory.Name AS [ProductCategory Name] ,Production.ProductSubcategory.Name AS [ProductSubcategory Name] ,Production.Product.Name AS [Product Name] ,Production.Product.Color ,Production.Product.ListPrice FROM Production.ProductSubcategory INNER JOIN Production.Product ON Production.ProductSubcategory.ProductSubcategoryID = Production.Product.ProductSubcategoryID INNER JOIN Production.ProductCategory ON Production.ProductSubcategory.ProductCategoryID = Production.ProductCategory.ProductCategoryID WHERE Production.ProductSubcategory.ProductSubcategoryID IN (@ProductSubcategoryID)

10. Configure Parameters

11. @ProductCategoryID

12. @ProductSubcategoryID

13. Displaying Single & Multi-Valued Report Parameter Selections  ="Category(s) Selected: " & JOIN(Parameters!ProductCategoryID.Label, ", ")  ="Subcategory(s) Selected: " & JOIN(Parameters!ProductSubcategoryID.Label, ", ")

14. More touches! ="Category(s) Selected (" & Parameters!ProductCategoryID.Count.ToString & "): " & JOIN(Parameters!ProductCategoryID.Label, ", ")

15. Q&A  Please send your feedback to naji [@] dotnetheroes.com

16. References  http://www.sqlchick.com/entries/2012/2/25/displaying-single-multi-valued- report-parameter-selections-i.html  Samples and Walkthroughs - http://msdn.microsoft.com/en- us/library/ms251686(v=vs.90).aspx

SSRS Report with Parameters and Data Filtration

Recommended

More Related Content

Similar to SSRS Report with Parameters and Data Filtration (20)

More from Naji El Kotob (9)

Recently uploaded (20)

SSRS Report with Parameters and Data Filtration