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SQL Server 2014 BI: Integration and Analysis Services

SQL Server 2014 BI: Integration and Analysis Services


Software Skills Training
<b>Specific Address TBD</b>
New York, NY
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Monday, June 17, 2019 - 5:00am


This hands-on course focuses on the Integration Services (SSIS) and Analysis Services (SSAS) business intelligence tools that are bundled with SQL Server 2014. Students will install and configure SQL Server 2014 servers that are enabled for SSIS and SSAS, which are then used for comprehensive hands on exercises demonstrating key features of SSIS/SSAS. Students work with complex SSIS data migration projects that import/export data between multiple formats including: Access, SQL Server, Oracle and other databases, XML files, Excel spreadsheets and flat files. Also demonstrated are SSIS tasks that can download from FTP Servers, copy/move files and folders, execute Win32 processes and .NET scripts, perform bulk imports, perform database maintenance, contact (via text or e-mail) administrators, and transfer database components between SQL Servers. Error handling options are also demonstrated with hands-on exercises, as well as how to use variables and input parameters in SSIS routines. The course provides thorough coverage of how to deploy, automate, secure and troubleshoot SSIS routines. Students will learn how to use SSAS to design, build and populate data warehouses to stage data for use by data cubes, and will perform hands-on exercises to design and build a data warehouse. Advanced data warehouse concepts, such as surrogate keys and rapidly changing dimensions are also reviewed. Subsequent exercises use SSAS to create data cubes and analyze them. Cube customization options are demonstrated, including how to add Key Performance Indicators (KPIs), custom calculations, and actions that link to SSRS reports. Attendees also learn how to optimize cube performance by defining attribute relationships and custom aggregation levels. The course also includes an overview of data mining and the tools available to do this in SSAS, supported by a hands-on exercise that walks through the process of defining a data mining structure to predict future sales. Administration topics related to data cubes are covered, including exercises that deploy and secure cubes, process and manage cubes. Course Prerequisites: Familiarity with database concepts, Windows desktop navigation and software installation techniques. Attendance at HOTT's SQL Programming course or Microsoft Transact-SQL Programming course is highly recommended although not required. Course Overview Installing SQL Server Business Intelligence Tools Installation Requirements Steps to Install SSRS, SSIS and SSAS Navigating the SQL Server Data Tools Development Environment New Features to SQL Server 2014 Business Intelligence Integration Services Architecture Architecture of the SSIS Data Engine Using Data Transformation Tasks Managing Connections to Sources and Destinations ADO.NET Data Source and Destination Understanding Data Buffers Control Flow Tasks and Containers Common SSIS Tasks Executing SQL Statements Connecting to FTP Servers Sending E-mail Notifying Administrators of Errors Completing Bulk Inserts Copying, Moving and Deleting Files and Folders Data Transformations Converting Data Types Merging Data from Multiple Sources Splitting Data to Multiple Destinations Counting Rows Sampling and Sorting Records Copying Columns Advanced SSIS Tasks Executing .NET Scripts and Win32 Processes Using the Windows Management Instrumentation (WMI) Tasks Performing Database Maintenance and Backups During SSIS Routines Using Variables and Input Parameters Profiling Database Tables Comparing XML Files Against Schemas Advanced Data Transformations Filling in Missing Data with Lookups Locating Near Duplicate Rows with Fuzzy Grouping Adding Audit Information to Results Counting the Occurrence of Keywords Sending Rows That Process Correctly and Incorrectly to Different Destinations Respond to Truncation Errors Migrating SQL Server 2000 DTS Packages Using the Upgrade Advisor Running Legacy DTS Packages on SQL Server 2005 Migration DTS Packages to SSIS Customizing Upgraded DTS Packages SSIS Administration and Automation Deploying SSIS Routines Manually Running SSIS Routines Automating SSIS Execution Configuring Notifications for Execution Success, Failure or Both SSIS Security Troubleshooting Techniques OLAP Design Understanding Fact and Dimension Tables Modeling Slowly Changing and Rapidly Changing Dimensions Modeling Fact Tables Using Star and Snowflake Schemas for Dimension Tables Implementing Surrogate Keys Defining Business Keys Creating and Populating Data Warehouses Creating Data Warehouses (OLAP Databases) Adding Fact Tables Adding Dimension Tables and Joining Them to Fact Tables Loading Data into Fact and Dimension Tables Validation Techniques for Data Loads Creating and Managing Cubes Creating Data Sources to Connect to Data Warehouses Using SSAS to Create Cubes Applying Friendly Names to Measures and Attributes Customizing Dimensions and Measures Setting up Navigational Hierarchies Optimizing Cubes with Attribute Relationships Customizing Cubes Adding Key Performance Indicators (KPIs) Customizing Dimensions and Attributes Adding Translations to Support Multiple Languages Adding Custom Calculations Subdividing Cubes Using Perspectives Cube Deployment and Administration Cube Storage Calculations Configuring Desired Aggregation Configuring Caching Deploying and Processing Cubes Connecting to Cubes from Excel and Other Clients Partitioning and Processing Cubes Backup and Restore Options Securing Cubes Multidimensional (MDX) Essentials Using MDX Queries to Pull Data from Cubes Understanding Tuples and Sets MDX Expressions vs. Queries Grouping Attribute Values into Named Sets Adding Custom Calculations for Cubes Using MDX MDX Functions Using MDX Aggregate Functions Using Navigations Functions to Move Though Hierarchies Grouping, Filtering and Sorting Functions Time-Based MDX Functions Understanding the Data Mining Process Types of Business Analysis Supported by Data Mining Data Mining Process Explained Understanding the Key Components of Data Mining Built-In Data Mining Algorithms Matching Mining Algorithms to Business Needs Working with Data Mining Structures Adding Data Mining Structures Mining for Hidden Information Discovering Patterns in Data Creating Predictive Models Using the Data Mining Wizard Modifying Mining Structures with the Data Mining Designer

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