SSIS Connection managers and data sources
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This document discusses SSIS data sources and connections. It provides an overview of different types of connections that can be used in SSIS packages, including OLEDB, ADO.NET, flat file, FTP, and Excel connections. Examples are given for Oracle and SQL Server OLEDB connection strings. The resources section links to Microsoft documentation on SSIS connections and data sources for further reference.
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Data visualizationSlava Kokaev This document describes three different approaches to building custom business intelligence applications and dashboards:
1) A basic BI approach using ASP.NET, SQL Server 2008 R2, Excel 2007 and report server for static reporting and simple pivot analysis.
2) An approach using PowerPivot for SharePoint 2010, which enables advanced slicing and dicing of data in Excel 2010 and self-service reporting and interactive dashboards in Internet Explorer 8.
3) A more advanced custom BI portal approach using ASP.NET, SQL Server 2008 R2, and Data Dynamics BI Suite for interactive reporting, dashboards and personalized analytics accessed through Excel, PowerPivot and Internet Explorer 8.
Developing ssas cube
Developing ssas cubeSlava Kokaev 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.
Business intelligence architecture
Business intelligence architectureSlava Kokaev This document provides an overview of business intelligence and outlines a conceptual framework for designing a business intelligence system driven by business processes. It discusses understanding the business system, defining business processes and requirements, technical design including databases and ETL, and developing BI applications to optimize operations, analyze and control business processes, and monitor business performance. An example sales process is described to illustrate how the framework can be applied.
Designing and developing Business Process dimensional Model or Data Warehouse
Designing and developing Business Process dimensional Model or Data WarehouseSlava Kokaev This document discusses best practices for designing a dimensional data warehouse model including using a star schema with fact and dimension tables, surrogate keys, snowflaking, slowly changing dimensions, and maintaining historical context when loading new or changed data into dimension tables. It describes the three types of slowly changing dimensions including overwriting existing records, inserting new versioned records, and tracking limited history with attributes.
SSAS R2 and SharePoint 2010 – Business Intelligence
SSAS R2 and SharePoint 2010 – Business IntelligenceSlava Kokaev This document discusses Microsoft SQL Server Analysis Services 2008 and enterprise data warehousing. It focuses on analysis services, SQL Server, data mining, and integration services as key components of Microsoft's business intelligence platform for performing analysis on enterprise data warehouses. The platform is designed to provide business insights for improved decision making.
MS SQL Server Analysis Services 2008 and Enterprise Data Warehousing
MS SQL Server Analysis Services 2008 and Enterprise Data WarehousingSlava Kokaev This document discusses business intelligence integration services including SQL Server, data mining, and Analysis Services. It provides an overview of key concepts for building an OLAP cube in Analysis Services such as data sources, data source views, dimensions, hierarchies, and processing cubes. The document also mentions additional cube objects like calculations, KPIs, actions, and perspectives.
06 SSIS Data Flow
06 SSIS Data FlowSlava Kokaev The document discusses Microsoft SQL Server Integration Services (SSIS). It describes how SSIS uses a data flow model to extract, transform, and load data. The data flow task encapsulates the data flow engine and connects components together in a pipeline. The key components of the data flow are sources that extract data, transformations that modify data, and destinations that load data. Paths connect the components and define the data flow.
05 SSIS Control Flow
05 SSIS Control FlowSlava Kokaev The document discusses Microsoft SQL Server Integration Services (SSIS) and focuses on defining control flow and data flow objects. It describes the three primary types of control flow objects - tasks, containers, and constraints - and provides examples of common tasks and containers used in SSIS packages to manage workflow and data transformation. It also discusses using variables to store and pass information between different objects in the package control flow.
03 Integration Services Project
03 Integration Services ProjectSlava Kokaev The document discusses Microsoft SQL Server Integration Services (SSIS) projects. It states that in SQL Server Business Intelligence Development Studio, an SSIS project is a container that stores and groups the files related to an SSIS package, including the package file, data sources, data source views, and other miscellaneous files. It provides details on how to structure an SSIS project and create packages within a project in Business Intelligence Development Studio.
01 Architecture Of Integration Services
01 Architecture Of Integration ServicesSlava Kokaev The document discusses the architecture of Microsoft SQL Server Integration Services (SSIS). SSIS is a platform for building data integration and transformation solutions. It allows users to process data into data warehouses, migrate data between systems, integrate data from multiple sources, and cleanse and analyze data. The core components of the SSIS architecture include packages, tasks, containers, control and data flow, connections, variables and event handlers.
Bi Architecture And Conceptual Framework
Bi Architecture And Conceptual FrameworkSlava Kokaev This document discusses business intelligence architecture and concepts. It covers topics like analysis services, SQL Server, data mining, integration services, and enterprise BI strategy and vision. It provides overviews of Microsoft's BI platform, conceptual frameworks, dimensional modeling, ETL processes, and data visualization systems. The goal is to improve organizational processes by providing critical business information to employees.
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SSIS Connection managers and data sources
- 1. Agenda SSIS Data Sources SSIS Connections Manager
- 2. Creating a Data Source
- 3. OLEDB Oracle Connection ADO.NET Connection Source Target Package Understanding a Data Source Data Source=MyOracleDB; User Id=myUsername; Password=myPassword; Server=myServer; Database=myDataBase; User ID=myUsername; Password=myPassword; Provider=OraOLEDB.Oracle; Provider=SQLNCLI10;
- 4. Understanding a SSIS Connections (Big Picture) Flat File Connection FTP Connection OLE DB Connection MOLAP Connection EXCEL Connection ADO.NET Connection SSIS Packages
- 5. Resources Integration Services Connections-http://msdn.microsoft.com/en- us/library/ms140203.aspx Data Source (SSIS) - http://msdn.microsoft.com/en- us/library/ms141792.aspx
Editor's Notes
- #3: Data sources are optional within SSIS, but they are beneficial during development if you have a large number of packages that need to use the same database or file connection. Using a data source also helps if you need to change a connection used in many packages. You simply change the data source once and then open each package in your project, which will automatically synchronize the connection string stored in the package with the data source.Connection Managers Integration Services uses the connection manager as a logical representation of a connection. At design time, you set the properties of a connection manager to describe the physical connection that Integration Services creates when the package runs. For example, a connection manager includes the ConnectionString property that you set at design time; at run time, a physical connection is created using the value in the connection string property. A package can use multiple instances of a connection manager type, and you can set the properties on each instance. At run time, each instance of a connection manager type creates a connection that has different attributes.
- #5: SQL Server Integration Services provides different types of connection managers that enable packages to connect to a variety of data sources and servers:There are built-in connection managers that Setup installs when you install Integration Services.There are connection managers that are available for download from the Microsoft Web site.You can create your own custom connection manager if the existing connection managers do not meet your needs.