419 Database courses in Heanor delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This is an introductory-level XML training course, designed for those needing an introduction to concepts and technologies associated with XML and its related recommendations. Previous experience or knowledge of HTML is helpful but not essential. Overview This course is an intensive, hands-on introduction to XML, XPath, and XSLT. The course is a balanced mixture of theory and practical labs designed to take students from the basic fundamentals of XML through to the related advanced technologies. The students walk through the different standards in a structured manner to enable them to master the concepts and ideas, which are reinforced in the lab exercises. The course starts with the fundamentals of XML, including coverage of DTDs and XML Schema. It then moves on to the XPath and XSLT standards, and how to use them to transform XML documents into other documents such as HTML documents or other XML documents. This course provides indoctrination in the practical use of W3C standards (including XSL and XML Schema) and of implementing tools and technologies. This course is programming language independent, making it useful for Java, .NET, C++, and any other programming orientation. Graduates will hit the ground running, applying XML to projects at both an architectural as well as a line by line coding level. We can easily adapt this course to industry and client specific needs.In addition to valuable knowledge and working examples, students receive a copy of the 'Xtensil' product. This unique software was developed to assist in implementing, testing, and fielding XML applications. Xtensil is used as both a teaching aid and a straightforward, basic, fully functional XML toolkit that students can use on Windows and Linux platforms. Working in a hands-on learning environment student will learn to: Write well-formed XML documents Model business requirements using XML Handle XML reserved characters Validate an XML document with a DTD and with a Schema Centralize data and markup definition with entities Create DTDs and Schemas using XML tools Generate XML documents from databases Write XSL templates to transform XML documents into HTML Integrate XML, XSL and the DOM to implement a complete solution The Extensible Markup Language (XML) is a standard that is enabling a revolution in web applications and business to business interactions. XML is the basis for Wireless Markup Language (WML), Voice Markup Language (VoiceML), Simple Object Access Protocol (SOAP), Web Services, and numerous industry initiatives such as ACORD (insurance), PXML (proposal/RFP) and OTA (travel). Introduction to XML is a three-day, hands-on course geared for software developers who need to understand what XML is and how to use in with today's systems and architectures. This course covers the topics from tags to architectures. The course is a balanced mixture of theory and practical labs designed to take students from a quick review of the basic fundamentals of XML through to the related advanced technologies. The students walk through the different standards in a structured manner to enable them to master the concepts and ideas, which are reinforced in the lab exercises. The course starts with a quick review of the fundamentals of XML before covering XML Schema in detail. It then moves on to the XPath and XSLT covering advanced topics in both. Finally, XML and Web Services security mechanisms and issues are addressed. XML Content Introduction to XML XML Mechanics XML Structure Namespaces Structure Using Schemas XML Formatting CSS and Rendering XML XSL Transformations XSLT and XPath XPath 2.0 and XSLT 2.0 Overview XSL FO (Formatting Objects) Applying XML XML Interoperability XML Performance Improvements Web Services Overview XML Applications Additional course details: Nexus Humans Introduction to XML (TT4300) 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 Introduction to XML (TT4300) 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 5 Days 30 CPD hours This course is intended for New or junior administrators and operators; system managers accountable for staffing and training Horizon operators and administrators. Experienced system operators, administrators, and integrators responsible for managing and maintaining VMware Horizon solutions Overview By the end of the course, you should be able to meet the following objectives: Implement a structured approach to troubleshooting Resolve common issues that occur in a VMware Horizon environment Troubleshoot issues with linked and instant clones Configure the Windows client Identify the correct log level for gathering logs Optimize protocols for best end-user experience Discuss Horizon Connection Server advanced configurations List troubleshooting techniques for Horizon Connection Server common issues Interpret Horizon 8 Connection Server logs Identify Unified Access Gateway configuration and certificate issues List troubleshooting steps for Unified Access Gateway common issues Describe BLAST configuration verification using logs and settings Describe BLAST optimization recommendations for different use cases Describe Horizon 8 Connections and how to troubleshoot related issues Describe Horizon 8 certificates List troubleshooting steps for common issues with Horizon 8 certificates Leverage Horizon infrastructure troubleshooting steps to resolve issues  This five-day course builds your skills in resolving common issues that occur in a VMware Horizon© environment. You engage in a series of lab exercises to bring existing environment issues to resolution. The exercises mirror real-world troubleshooting use cases. These exercises equip learners with the knowledge and practical skills to manage typical challenges faced by virtual desktop administrators and operators and provides you with the advanced knowledge, skills, and abilities to troubleshoot VMware Horizon© 8 infrastructure related issues. This workshop teaches the required skill and competence for troubleshooting VMware Horizon© Connection Server?, VMware Unified Access Gateway?, protocols, connections, and certificates Course Introduction Introductions and course logistics Course objectives Overview of Virtual Desktop Troubleshooting Structured approach to troubleshooting configuration and operational problems Applying troubleshooting methods Documenting the steps to resolving the problem Command-Line Tools and Backup Options Using command-line tools Backing-up and restoring VMware Horizon databases Troubleshooting Horizon Linked Clone Desktops Only applicable for Horizon 7.x environments Describe the components that make up a VMware Horizon desktop Explain how the View Agent Direct-Connection plug-In is useful for diagnosing problems Highlight the best practice for optimizing a VMware Horizon desktop Troubleshoot common problems with VMware Horizon desktops Troubleshooting Instant Clones Discuss how instant clones are created Discuss what gets logged when an instant clone is created Discuss the keywords to look for in the logs when troubleshooting instant clones Discuss how to troubleshoot problems with instant clones Windows Client Correctly configure the Windows Client Identify the correct log level for gathering logs Enable the required SSL configuration level for the environment Ports and Protocols Discuss the key ports on a Horizon Environment Discuss protocols used in the Horizon Environment Understand the benefit of optimizing Blast Become familiar with the optimization features for Blast Implement GPO changes for Blast Become familiar with the causes for Black Screens Discuss how to troubleshoot Black Screen problems Identify problems encountered when applying GPOs Discuss how to troubleshoot GPO-related problems Horizon Connection Server Troubleshooting Discuss Horizon Connection Server general troubleshooting techniques Identity Horizon Connection Server common issues through logs Describe AD LDS replication Discuss Horizon Connection Server replication common issues Review and Interpret Horizon Connection Server logs Compare successful and unsuccessful logs from everyday infrastructure administration tasks Unified Access Gateway Troubleshooting List and identify common Unified Access Gateway deployment issues Monitor the Unified Access Gateway deployment to identify health and issues Identify and troubleshoot Unified Access Gateway certificate issues Monitor, test, and troubleshoot network problems Discuss general Unified Access Gateway troubleshooting processes BLAST Configuration Verification Discuss BLAST Codecs and Encoder Switch settings. Describe how to verify BLAST configuration using logs and settings BLAST Optimization List general BLAST optimization recommendations Summarize BLAST tuning recommendations that apply to WAN connections Summarize BLAST tuning recommendations that apply to work-from-home and home-office-to-cloud use cases Describe recommended tuning options to increase display protocol quality for all use cases and applications. VMware Horizon Connections Troubleshooting Explain Horizon connections Describe the role of Primary and Secondary protocols in Horizon connections Describe HTML client access connections Describe Horizon connections load balancing Describe timeout settings, supported health monitoring string, and suitable load balancer persistence values Identify troubleshooting steps for failing Horizon load balancer connections List troubleshooting steps for Horizon connections VMware Horizon Certificates Troubleshooting List Horizon certificate functions Describe Horizon certificates scenarios. Discuss potential challenges related to certificates in Horizon Describe the troubleshooting approach to Horizon certificate issues VMware Horizon Challenge Lab Leverage Horizon infrastructure troubleshooting steps to resolve issues

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

Learn how to work with and connect multiple data sets to effectively analyse and report on data. Course overview Duration: 1 day (6.5 hours) Within Excel you have some powerful features to enable you to connect and analyse multiple data sources. Power Query enables you to import and manipulate your data, Power Pivot enables you to connect multiple data sources and create pivot tables and pivot charts from them. This course is an introduction to Power Query and Power Pivot in Excel to get you started on creating a powerful reporting capability. Knowledge of working with Excel workbooks and relational databases would be an advantage. Objectives By the end of the course you will be able to: Import data from multiple data sources Edit and transform data before importing Add extra columns of data Append data Merge data from other tables Create data models Build data relationships Build Pivot Tables Build Pivot Charts Use Slicers and Timeline Filters Content Importing data Data sources Importing data Transforming data Editing your data Setting data types Removing columns/rows Choosing columns to keep Setting header rows Splitting columns Appending queries Appending data from other tables Adding text Columns from example Custom columns Conditional columns Merge queries Setting up and using merge queries Merging in columns of data Creating a data model The data model Multiple data tables Connecting tables Building relationships Relationship types Building visuals from multiple tables Analysing information using pivot tables Creating and modifying a Pivot Table Recalculating the Pivot Table Filtering the Pivot Table Searching the Pivot Table Drilling down to underlying data Customising field names Changing field formatting Pivot charts, slices and timelines Creating Pivot Charts Adding and using Slicers

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Duration 2 Days 12 CPD hours Overview Understand why Blockchain is needed and where Explore the major components of BlockchainLearn about Hyperledger Fabric and the structure of the Hyperledger ArchitectureLean the features of the Fabric model including chaincode, SDKs, Ledger, Security and Membership ServicesPerform comprehensive labs on writing chaincodeExplore the architecture of Hyperledger FabricUnderstand and perform in depth labs on Bootstrapping the NetworkPerform comprehensive labs to integrate/develop an application with Hyperledger Fabric running a smart contractBuild applications on Hyperledger FabricCourse Outline: This training course has been created to walk you through Chaincode Development, Testing, and Deployment for a Hyperledger Fabric Network catering specifically toward Golang written Chaincode (Fabric?s original Chaincode Language). Additionally as an Application Developer you will learn how to write, and prepare Client Applications using the most mature Standard Development Kit in Hyperledger Fabric, NodeJS. Blockchain Basics (Overview)Hyperledger Fabric Development EnvironmentKnowing the Difference: ComposerChaincode Use CasesChaincode BasicsGolang Shim DevelopmentDatabases for the DeveloperChaincode Dev. Deployment and InteractionsClients & SDK Development: Fabric-NetworkClients & SDK Development: Fabric-Client InteractionsLogging and Monitoring

Duration 2 Days 12 CPD hours This course is intended for Application Developers Business Analysts Developer End Users Functional Implementer Java Developer System Analysts Technical Administrator Overview Create administrator-level personalizations Personalize configurable pages Utilize advanced personalization features Implement flexfields on OA Framework-based pages Create custom look and feel definitions Create user-level personalizations This course will be applicable for customers who have implemented Oracle E-Business Suite Release 12 or Oracle E-Business Suite 12.1. This course will be applicable for customers who have implemented Oracle E-Business Suite Release 12 or Oracle E-Business Suite 12.1.

Duration 5 Days 30 CPD hours This course is intended for The course provides an intensive hands-on experience for key system administration tasks with the goal of making the system administrator job-ready. Overview Administer the Oracle Solaris 11 Host on an Existing Network Administer Oracle Solaris Zones Control Access to Systems and Files Install Oracle Solaris 11 Operating System Administer User Accounts Administer System Processes and Schedule System Tasks Manage Data by Using ZFS Manage Boot and Shutdown of a System Administer Services by Using SMF Administer Software Packages by Using IPS and Manage Boot Environments Describe the use of IPS in packaging the Oracle Solaris OS Manage boot environments Updating the OS by using IPS The Oracle Solaris 11 System Administration training covers the full range of introductory system administration tasks on Oracle Solaris 11.3 OS. The topics covered range from installing the operating system on a single system, to monitoring and basic troubleshooting. The Oracle Solaris 11 System Administration course is designed to provide new system administrators, as well as enterprise system administrators who are new to the Oracle Solaris 11 Operating System, with the skills they need to perform their job tasks successfully and efficiently. Installing Oracle Solaris 11 Operating System Introduction to Oracle Solaris 11 OS Planning for Oracle Solaris 11 OS installation Installing Oracle Solaris 11 OS by Using the Live Media Installer Installing Oracle Solaris 11 OS Using the Text Installer Verifying the OS Installation Managing Boot and Shutdown of Systems Analyze the boot design and boot process Boot a SPARC-based system Boot an x86-based system Shut down a system Administering Services by Using SMF Describing SMF and its components Administering SMF Services Administering Software Packages by Using IPS and Managing Boot Environments Describing IPS, its components, and interfaces Configuring an IPS Client to Access the Local IPS Repository Managing Package Publishers Managing Software Packages Managing Signed Packages and Package Properties Describe the use of IPS in packaging the Oracle Solaris OS Manage boot environments Updating the OS by using IPS Managing Data by Using ZFS Introducing ZFS Administering ZFS Storage Pools Administering ZFS File Systems Administering ZFS Properties Administering ZFS Snapshots and Clones Administering the Network Reviewing Networking Fundamentals Administering Datalink Configuration Administering a Network Interface Administering Profile-Based Network Configuration Configuring a Virtual Network Verifying the Network Operations Managing Resources on the Virtual Network Administering Oracle Solaris Zones Introducing Oracle Solaris Zones Configuring an Oracle Solaris Zone Determining an Oracle Solaris Zone Configuration Controlling Access to Systems and Files Controlling Access to Systems Controlling Access to Files Securing Access to Remote Host Administering User Accounts Getting Started with the User Administration Setting Up User Accounts Maintaining User Accounts Configuring User Disk Quotas Managing System Processes and System Tasks Managing System Processes Scheduling System Administration Tasks

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