27 Data Warehouse courses in Sheffield delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for Application Consultant Business Analyst Business Process Architect Business Process Owner / Team Lead / Power User Developer Enterprise Architect Solution Architect Trainer Overview This course will prepare you to: Understand the basic concepts of SAP data warehousing Position the value-added of SAP Data Warehouse Cloud Integrate on-premise SAP Sources Model in SAP Data Warehouse Cloud Consume Data in SAP Analytics Cloud This course will prepare you to:Understand the basic concepts of SAP data warehousingPosition the value-added of SAP Data Warehouse CloudIntegrate on-premise SAP SourcesModel in SAP Data Warehouse CloudConsume Data in SAP Analytics Cloud Course Outline Getting started with data warehousing and the training environment Short introduction in SAP BW Bridge and other sources SAP Data Warehouse Cloud: -Introducing SAP Data Warehouse Cloud -Describing Spaces, integration options, operations and best practices -Introducing modeling in the Data Builder -Introducing modeling the Business Layer Describing consumption options in SAP Analytics Cloud Additional aspects in SAP Data Warehouse Cloud Outlook and roadmap Additional course details: Nexus Humans DSP01 SAP Introduction to SAP Data Warehouse Cloud training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the DSP01 SAP Introduction to SAP Data Warehouse Cloud course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Database architects Database administrators Database developers Data analysts and scientists Overview This course is designed to teach you how to: Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution Architect the data warehouse Identify performance issues, optimize queries, and tune the database for better performance Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data Module 1: Introduction to Data Warehousing Relational databases Data warehousing concepts The intersection of data warehousing and big data Overview of data management in AWS Hands-on lab 1: Introduction to Amazon Redshift Module 2: Introduction to Amazon Redshift Conceptual overview Real-world use cases Hands-on lab 2: Launching an Amazon Redshift cluster Module 3: Launching clusters Building the cluster Connecting to the cluster Controlling access Database security Load data Hands-on lab 3: Optimizing database schemas Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods Module 5: Identifying data sources Data sources overview Amazon S3 Amazon DynamoDB Amazon EMR Amazon Kinesis Data Firehose AWS Lambda Database Loader for Amazon Redshift Hands-on lab 4: Loading real-time data into an Amazon Redshift database Module 6: Loading data Preparing Data Loading data using COPY Data Warehousing on AWS AWS Classroom Training Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command Module 7: Writing queries and tuning for performance Amazon Redshift SQL User-Defined Functions (UDFs) Factors that affect query performance The EXPLAIN command and query plans Workload Management (WLM) Hands-on lab 6: Configuring workload management Module 8: Amazon Redshift Spectrum Amazon Redshift Spectrum Configuring data for Amazon Redshift Spectrum Amazon Redshift Spectrum Queries Hands-on lab 7: Using Amazon Redshift Spectrum Module 9: Maintaining clusters Audit logging Performance monitoring Events and notifications Lab 8: Auditing and monitoring clusters Resizing clusters Backing up and restoring clusters Resource tagging and limits and constraints Hands-on lab 9: Backing up, restoring and resizing clusters Module 10: Analyzing and visualizing data Power of visualizations Building dashboards Amazon QuickSight editions and feature

Business Intelligence: In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Introduction to data engineering on Azure What is data engineering Important data engineering concepts Data engineering in Microsoft Azure 2 - Introduction to Azure Data Lake Storage Gen2 Understand Azure Data Lake Storage Gen2 Enable Azure Data Lake Storage Gen2 in Azure Storage Compare Azure Data Lake Store to Azure Blob storage Understand the stages for processing big data Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - Introduction to Azure Synapse Analytics What is Azure Synapse Analytics How Azure Synapse Analytics works When to use Azure Synapse Analytics 4 - Use Azure Synapse serverless SQL pool to query files in a data lake Understand Azure Synapse serverless SQL pool capabilities and use cases Query files using a serverless SQL pool Create external database objects 5 - Use Azure Synapse serverless SQL pools to transform data in a data lake Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement Encapsulate data transformations in a stored procedure Include a data transformation stored procedure in a pipeline 6 - Create a lake database in Azure Synapse Analytics Understand lake database concepts Explore database templates Create a lake database Use a lake database 7 - Analyze data with Apache Spark in Azure Synapse Analytics Get to know Apache Spark Use Spark in Azure Synapse Analytics Analyze data with Spark Visualize data with Spark 8 - Transform data with Spark in Azure Synapse Analytics Modify and save dataframes Partition data files Transform data with SQL 9 - Use Delta Lake in Azure Synapse Analytics Understand Delta Lake Create Delta Lake tables Create catalog tables Use Delta Lake with streaming data Use Delta Lake in a SQL pool 10 - Analyze data in a relational data warehouse Design a data warehouse schema Create data warehouse tables Load data warehouse tables Query a data warehouse 11 - Load data into a relational data warehouse Load staging tables Load dimension tables Load time dimension tables Load slowly changing dimensions Load fact tables Perform post load optimization 12 - Build a data pipeline in Azure Synapse Analytics Understand pipelines in Azure Synapse Analytics Create a pipeline in Azure Synapse Studio Define data flows Run a pipeline 13 - Use Spark Notebooks in an Azure Synapse Pipeline Understand Synapse Notebooks and Pipelines Use a Synapse notebook activity in a pipeline Use parameters in a notebook 14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics Understand hybrid transactional and analytical processing patterns Describe Azure Synapse Link 15 - Implement Azure Synapse Link with Azure Cosmos DB Enable Cosmos DB account to use Azure Synapse Link Create an analytical store enabled container Create a linked service for Cosmos DB Query Cosmos DB data with Spark Query Cosmos DB with Synapse SQL 16 - Implement Azure Synapse Link for SQL What is Azure Synapse Link for SQL? Configure Azure Synapse Link for Azure SQL Database Configure Azure Synapse Link for SQL Server 2022 17 - Get started with Azure Stream Analytics Understand data streams Understand event processing Understand window functions 18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics Stream ingestion scenarios Configure inputs and outputs Define a query to select, filter, and aggregate data Run a job to ingest data 19 - Visualize real-time data with Azure Stream Analytics and Power BI Use a Power BI output in Azure Stream Analytics Create a query for real-time visualization Create real-time data visualizations in Power BI 20 - Introduction to Microsoft Purview What is Microsoft Purview? How Microsoft Purview works When to use Microsoft Purview 21 - Integrate Microsoft Purview and Azure Synapse Analytics Catalog Azure Synapse Analytics data assets in Microsoft Purview Connect Microsoft Purview to an Azure Synapse Analytics workspace Search a Purview catalog in Synapse Studio Track data lineage in pipelines 22 - Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts 23 - Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data 24 - Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook Additional course details: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the DP-203T00 Data Engineering on Microsoft Azure course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Business Intelligence: Virtual In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is database professionals who need to fulfil a Business Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing. Overview Create sophisticated SSIS packages for extracting, transforming, and loading data Use containers to efficiently control repetitive tasks and transactions Configure packages to dynamically adapt to environment changes Use Data Quality Services to cleanse data Successfully troubleshoot packages Create and Manage the SSIS Catalog Deploy, configure, and schedule packages Secure the SSIS Catalog SQL Server Integration Services is the Community Courseware version of 20767CC Implementing a SQL Data Warehouse. This five-day instructor-led course is intended for IT professionals who need to learn how to use SSIS to build, deploy, maintain, and secure Integration Services projects and packages, and to use SSIS to extract, transform, and load data to and from SQL Server. This course is similar to the retired Course 20767-C: Implementing a SQL Data Warehouse but focuses more on building packages, rather than the entire data warehouse design and implementation. Prerequisites Working knowledge of T-SQL and SQL Server Agent jobs is helpful, but not required. Basic knowledge of the Microsoft Windows operating system and its core functionality. Working knowledge of relational databases. Some experience with database design. 1 - SSIS Overview Import/Export Wizard Exporting Data with the Wizard Common Import Concerns Quality Checking Imported/Exported Data 2 - Working with Solutions and Projects Working with SQL Server Data Tools Understanding Solutions and Projects Working with the Visual Studio Interface 3 - Basic Control Flow Working with Tasks Understanding Precedence Constraints Annotating Packages Grouping Tasks Package and Task Properties Connection Managers Favorite Tasks 4 - Common Tasks Analysis Services Processing Data Profiling Task Execute Package Task Execute Process Task Expression Task File System Task FTP Task Hadoop Task Script Task Introduction Send Mail Task Web Service Task XML Task 5 - Data Flow Sources and Destinations The Data Flow Task The Data Flow SSIS Toolbox Working with Data Sources SSIS Data Sources Working with Data Destinations SSIS Data Destinations 6 - Data Flow Transformations Transformations Configuring Transformations 7 - Making Packages Dynamic Features for Making Packages Dynamic Package Parameters Project Parameters Variables SQL Parameters Expressions in Tasks Expressions in Connection Managers After Deployment How It All Fits Together 8 - Containers Sequence Containers For Loop Containers Foreach Loop Containers 9 - Troubleshooting and Package Reliability Understanding MaximumErrorCount Breakpoints Redirecting Error Rows Logging Event Handlers Using Checkpoints Transactions 10 - Deploying to the SSIS Catalog The SSIS Catalog Deploying Projects Working with Environments Executing Packages in SSMS Executing Packages from the Command Line Deployment Model Differences 11 - Installing and Administering SSIS Installing SSIS Upgrading SSIS Managing the SSIS Catalog Viewing Built-in SSIS Reports Managing SSIS Logging and Operation Histories Automating Package Execution 12 - Securing the SSIS Catalog Principals Securables Grantable Permissions Granting Permissions Configuring Proxy Accounts Additional course details: Nexus Humans 55321 SQL Server Integration Services training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the 55321 SQL Server Integration Services course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines. Completed either AWS Technical Essentials or Architecting on AWS Completed Building Data Lakes on AWS Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a data warehouse analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Using Amazon Redshift in the Data Analytics Pipeline Why Amazon Redshift for data warehousing? Overview of Amazon Redshift Module 2: Introduction to Amazon Redshift Amazon Redshift architecture Interactive Demo 1: Touring the Amazon Redshift console Amazon Redshift features Practice Lab 1: Load and query data in an Amazon Redshift cluster Module 3: Ingestion and Storage Ingestion Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API Data distribution and storage Interactive Demo 3: Analyzing semi-structured data using the SUPER data type Querying data in Amazon Redshift Practice Lab 2: Data analytics using Amazon Redshift Spectrum Module 4: Processing and Optimizing Data Data transformation Advanced querying Practice Lab 3: Data transformation and querying in Amazon Redshift Resource management Interactive Demo 4: Applying mixed workload management on Amazon Redshift Automation and optimization Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster Module 5: Security and Monitoring of Amazon Redshift Clusters Securing the Amazon Redshift cluster Monitoring and troubleshooting Amazon Redshift clusters Module 6: Designing Data Warehouse Analytics Solutions Data warehouse use case review Activity: Designing a data warehouse analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course are Application Consultants, Business Analysts, Business Process Owners/Team Leads/Power Users, Program/Project Managers, Technology Consultants, and Users. In this course, students will gain SAP Netweaver Business Warehouse knowledge necessary for successful implementation and administration within a heterogeneous SAP NetWeaver BW system landscape. Data Warehousing Describing Data Warehouse Systems Describing Data Warehouse Architecture Using the Data Warehousing Workbench Master Data Modeling in SAP BW Describing InfoObjects Creating Characteristic InfoObjects The Loading of Master Data from SAP Data Sources Describing Data Flow Modeling a Master Data Flow Loading a Master Data Flow Modeling with the Graphical Data Flow Tool Loading of Transaction Data from SAP DataSources Describing the Core InfoProviders Creating a Key Figure InfoObject Creating a DataStore Object (DSO) Loading Transaction Data into a Data Store Object Describing the Extended Star Schema of an InfoCube Creating InfoCubes Loading Transaction Data into an InfoCube Master Data Loading from Flat File Data Sources Loading Data From a Flat File Describing the Data Flow in Detail Describing the Data Loading Process in Detail InfoProviders in SAP BW Explaining the InfoProviders Used in SAP BW ? Introduction Creating MultiProviders Usage of SAP BI Content Using BI Content Query Performance Optimization Optimizing Query Performance Monitoring Performance Creating and Filling Aggregates The SAP BW Administration Describing Administrative Tasks and Tools Administrating the InfoCubes Administrating the DataStore Objects Creating Process Chains

Duration 5 Days 30 CPD hours This course is intended for Data Warehouse AdministratorDatabase AdministratorsDatabase DesignersSupport EngineerTechnical Administrator Overview Monitor the DatabaseManage Database PerformanceImplement Database AuditingConfigure the Database Instance Such That Resources Are Appropriately Allocated Among Sessions and TasksSchedule Jobs to Run Inside or Outside of the DatabaseConfigure Oracle Net ServicesConfigure your Database For Backup and Recovery OperationsDescribe Oracle Database ArchitectureManage the Oracle Database InstanceManage Oracle Database Storage structuresCreate and Administer User Accounts The Oracle Database 12c: Administration Workshop will teach you about the Oracle Database architecture. You will discover how to effectively manage an Oracle Database instance, configure the Oracle Network Environment and perform database maintenance. The Oracle Database 12c: Administration Workshop will teach you about the Oracle Database architecture. You will discover how to effectively manage an Oracle Database instance, configure the Oracle Network Environment and perform database maintenance.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for experienced administrators with a background in either software development or system administration. Team leaders, lead developers, and other accidental Team Foundation Server administrators are also encouraged to take this course. This course will also help a student prepare for the relevant Microsoft certification exam. Overview At course completion, attendees will have had exposure to: - TFS editions and components - Supported topologies and environments - Must-have TFS administration tools - Hardware and software requirements - Required service accounts and permissions - Installing Team Foundation Server - Configuring Team Foundation Server - Managing relevant SQL Server components - Managing relevant SharePoint components - Installing and using Team Explorer - Team project collections and team projects - Using and customizing process templates - TFS licensing and Client Access Licenses - Connecting and using Microsoft Excel & Project - Installing and using Team Explorer Everywhere - Integrating TFS and SharePoint - Using the TFS web portal - Git and TFVC version control systems - Basic and advanced version control workflows - Configuring and using code search - Controlling access to version controlled items - Command-line and third party tools - Configuring automated builds - Deploying and using Visual Studio agents - Configuring agent pools and queues - Creating and queuing automated builds - Configuring Package Management - Configuring Release Management - Creating a release definition - Creating and deploying a release - Strategies for upgrading and migrating to TFS - Integrating TFS with other systems and data - High availability and scalability options - Capacity planning and disaster recovery - Backing up, restoring, and moving TFS data - Managing the data warehouse - Using PowerShell to manage TFS - Customizing Team Foundation Server - Extending Team Foundation Server Provides students with the knowledge and skills to deploy, configure, and manage Microsoft Team Foundation Server 2019 and related software components. Introduction to Team Foundation Server Introduction to Team Foundation Server Editions, components, and configurations Visual Studio Team Services comparison TFS' support of Application Lifecycle Management TFS administrator responsibilities and tasks ?Must-have? tools of a TFS administrator Planning and Deploying TFS Planning the deployment System requirements, software, and accounts Installing and configuring TFS Installing Team Explorer Troubleshooting Configuring TFS Administrator roles and tools Managing team project collections Managing team projects Managing process templates Securing TFS, SharePoint, and SQL Server Renaming and deleting a team project Client Applications TFS Client Access Licenses (CAL) Team Explorer and the web portal Microsoft Excel and Microsoft Project SharePoint project portal Team Explorer Everywhere Command-line and 3rd party tools Version Control Overview of Git and TFVC version control systems Integration with Visual Studio Using TFVC and Git version control Basic and advanced workflows Controlling access to version control Command-line tools and utilities TFS Proxy, MSSCCI Provider, and TFS Sidekicks Building and Releasing Overview of the Visual Studio build system Build agents, agent pools, agent queues Creating and queuing a build Monitoring, and managing a build Securing the build process Running tests as part of the build Overview of Package Management Overview of Release Management Defining, creating, and deploying a release Upgrading, Migrating, and Integrating Upgrading Team Foundation Server In-place vs. migration upgrade Performing post-upgrade tasks Migrating work items Migrating items under version controlled Integrating with Team Foundation Server Custom and 3rd party solutions Advanced Administration Monitoring the health of Team Foundation Server Web-based diagnostic tools Options for scalability and high availability Disaster recovery, backup, and restore Moving Team Foundation Server Managing the data warehouse Using PowerShell to manage TFS Customizing and Extending Customizing vs. extending Customizing a process template Customizing a work item type Creating default work items Creating and using a global list Using Witadmin.exe Using work item templates Creating a custom report Using the REST API to extend Team Foundation Server Additional course details: Nexus Humans Administering Team Foundation Server 2017 training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Administering Team Foundation Server 2017 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.