27 Data Warehouse courses in Cardiff delivered Live Online

Duration 5 Days 30 CPD hours This course is intended for Data Warehouse Administrator Database Administrators Support Engineer Technical Administrator Technical Consultant Overview Use Oracle Flashback Technologies to recover from human error Use Recovery Manager (RMAN) to create backups and perform recovery operations Use the Data Recovery Advisor to diagnose and repair failures Plan effective backup and recovery procedures Describe the Oracle Database architecture components related to backup and recovery operations Perform an encrypted database backup and restore Perform tablespace point-in-time recovery Configure the database for recoverability Describe Cloud Tooling for Backup and Recovery Describe Oracle Database backup methods and recovery operations that can be used to resolve database failure In this Oracle Database 12c R2: Backup and Recovery Workshop, students learn how to perform backup and recovery based on the related Oracle Database architecture components. Various backup, failure, restore, and recovery scenarios are provided so that students learn to evaluate their own recovery requirements and develop an appropriate strategy for backup and recovery procedures. This course includes an interactive workshop, with scenarios that provide participants with opportunities to diagnose and recover from several failure situations. Introduction Curriculum Context Assess your recovery requirements Categories of failures Oracle backup and recovery solutions Oracle Maximum Availability Architecture Oracle Secure Backup Benefits of using Oracle Data Guard Basic Workshop Architecture Getting Started Core Concepts of the Oracle Database, critical for Backup and Recovery Oracle DBA Tools for Backup and Recovery Connecting to Oracle Recovery Manager (RMAN) Configuring for Recoverablility RMAN commands Configuring and managing persistent settings Using the Fast Recovery Area (FRA) Control File Redo Log File Archiving Logs Using the RMAN Recovery Catalog Creating and Configuring the Recovery Catalog Managing Target Database Records in the Recovery Catalog Using RMAN Stored Scripts Maintaining and Protecting the Recovery Catalog Virtual Private Catalogs Backup Strategies and Terminology Backup Solutions Overview and Terminology Balancing Backup and Restore Requirements Backing Up Read-Only Tablespaces Data Warehouse Backup and Recovery: Best Practices Additional Backup Terminology Performing Backups RMAN Backup Types Incrementally Updated Backups Fast Incremental Backup Block Change Tracking Oracle-Suggested Backup Reporting on Backups Managing Backups Improving Your Backups Compressing Backups Using a Media Manager Backup and Restore for Very Large Files Creating RMAN Multi-section Backups, Proxy Copies, Duplexed Backup Sets and Backups of Backup Sets Creating and Managing Archival Backups Backing Up Recovery Files Backing Up the Control File to a Trace File Cataloging Additional Backup Files Using RMAN-Encrypted Backups Creating RMAN-Encrypted Backups Using Transparent-Mode Encryption Using Password-Mode Encryption Using Dual-Mode Encryption Diagnosing Failures Reducing Problem Diagnosis Time Automatic Diagnostic Repository Data Recovery Advisor Handling Block Corruption Restore and Recovery Concepts Restoring and Recovering Instance Failure and Instance/Crash Recovery Media Failure Complete Recovery (Overview) Point-in-Time Recovery (Overview) Recovery with the RESETLOGS Option Performing Recovery, Part I RMAN Recovery in NOARCHIVELOG Mode Performing Complete Recovery (of critical and noncritical data files) Restoring ASM Disk Groups Recovery with Image Files Performing Point-in-Time (PITR) or Incomplete Recovery Performing Recovery, Part II Recovery of Server Parameter File, Control File (One and All) Redo Log File Loss and Recovery Password Authentication File Re-creation Index, Read-Only Tablespace, and Temp file Recovery Restoring the Database to a New Host Disaster Recovery Restoring RMAN Encrypted Backups RMAN and Oracle Secure Backup Oracle Secure Backup Overview and Interface Options RMAN and OSB: Overview and Basic Process Flow Starting with Oracle Secure Backup Configuring Oracle Secure Backup for RMAN RMAN Backup and Restore Operations Oracle Secure Backup Jobs Displaying OSB log files and transcripts for RMAN activities Using Flashback Technologies Flashback Technology: Overview and Setup Using Flashback Technology to Query Data Flashback Table Flashback Transaction (Query and Back out) Flashback Drop and the Recycle Bin Flashback Data Archive Using Flashback Database Flashback Database Architecture Configuring Flashback Database Performing Flashback Database Best Practices for Flashback Database Transporting Data Transporting Data Across Platforms Transporting Data with Backup Sets Database Transport: Using Data Files Performing Point-in-Time Recovery When to use TSPITR TSPITR Architecture Performing RMAN TS Point-in-time Recovery Recovering Tables from Backups Duplicating a Database Using a Duplicate Database Duplicating Database with 'push' and 'pull' techniques Choosing Database Duplication Techniques Creating a Backup-up Based Duplicate Database Understanding the RMAN Duplication Operation RMAN Troubleshooting and Tuning Interpreting RMAN Message Output Tuning Principles Diagnosing Performance Bottlenecks RMAN Multiplexing Restore and Recovery Performance Best Practices Cloud Tooling for Backup and Recovery Backup Destinations Customize Backup Configuration On-Demand Backup and Recovery Oracle Backup Cloud Service Installing the Backup Module Backup and Recovery Workshop Workshop Structure and Approach Business Requirements for Database Availability and Procedures Diagnosing the Failures

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.

Duration 2 Days 12 CPD hours This course is intended for Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek techniques for working with complex types of data resources. Overview Use Connector stages to read from and write to database tables Handle SQL errors in Connector stages Use Connector stages with multiple input links Use the File Connector stage to access Hadoop HDFS data Optimize jobs that write to database tables Use the Unstructured Data stage to extract data from Excel spreadsheets Use the Data Masking stage to mask sensitive data processed within a DataStage job Use the Hierarchical stage to parse, compose, and transform XML data Use the Schema Library Manager to import and manage XML schemas Use the Data Rules stage to validate fields of data within a DataStage job Create custom data rules for validating data Design a job that processes a star schema data warehouse with Type 1 and Type 2 slowly changing dimensions This course is designed to introduce you to advanced parallel job data processing techniques in DataStage v11.5. In this course you will develop data techniques for processing different types of complex data resources including relational data, unstructured data (Excel spreadsheets), and XML data. In addition, you will learn advanced techniques for processing data, including techniques for masking data and techniques for validating data using data rules. Finally, you will learn techniques for updating data in a star schema data warehouse using the DataStage SCD (Slowly Changing Dimensions) stage. Even if you are not working with all of these specific types of data, you will benefit from this course by learning advanced DataStage job design techniques, techniques that go beyond those utilized in the DataStage Essentials course. Accessing databases Connector stage overview - Use Connector stages to read from and write to relational tables - Working with the Connector stage properties Connector stage functionality - Before / After SQL - Sparse lookups - Optimize insert/update performance Error handling in Connector stages - Reject links - Reject conditions Multiple input links - Designing jobs using Connector stages with multiple input links - Ordering records across multiple input links File Connector stage - Read and write data to Hadoop file systems Demonstration 1: Handling database errors Demonstration 2: Parallel jobs with multiple Connector input links Demonstration 3: Using the File Connector stage to read and write HDFS files Processing unstructured data Using the Unstructured Data stage in DataStage jobs - Extract data from an Excel spreadsheet - Specify a data range for data extraction in an Unstructured Data stage - Specify document properties for data extraction. Demonstration 1: Processing unstructured data Data masking Using the Data Masking stage in DataStage jobs - Data masking techniques - Data masking policies - Applying policies for masquerading context-aware data types - Applying policies for masquerading generic data types - Repeatable replacement - Using reference tables - Creating custom reference tables Demonstration 1: Data masking Using data rules Introduction to data rules - Using the Data Rules Editor - Selecting data rules - Binding data rule variables - Output link constraints - Adding statistics and attributes to the output information Use the Data Rules stage to valid foreign key references in source data Create custom data rules Demonstration 1: Using data rules Processing XML data Introduction to the Hierarchical stage - Hierarchical stage Assembly editor - Use the Schema Library Manager to import and manage XML schemas Composing XML data - Using the HJoin step to create parent-child relationships between input lists - Using the Composer step Writing Hierarchical data to a relational table Using the Regroup step Consuming XML data - Using the XML Parser step - Propagating columns Topic 6: Transforming XML data - Using the Aggregate step - Using the Sort step - Using the Switch step - Using the H-Pivot step Demonstration 1: Importing XML schemas Demonstration 2: Compose hierarchical data Demonstration 3: Consume hierarchical data Demonstration 4: Transform hierarchical data Updating a star schema database Surrogate keys - Design a job that creates and updates a surrogate key source key file from a dimension table Slowly Changing Dimensions (SCD) stage - Star schema databases - SCD stage Fast Path pages - Specifying purpose codes - Dimension update specification - Design a job that processes a star schema database with Type 1 and Type 2 slowly changing dimensions Demonstration 1: Build a parallel job that updates a star schema database with two dimensions Additional course details: Nexus Humans KM423 IBM InfoSphere DataStage v11.5 - Advanced Data Processing 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 KM423 IBM InfoSphere DataStage v11.5 - Advanced Data Processing 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 Database Administrators Data Warehouse Administrator Support Engineer Technical Consultant Technical Administrator Overview Describe Oracle Database backup methods and recovery operations that can be used to resolve database failure. Describe the Oracle Database architecture components related to backup and recovery operations. Plan effective backup and recovery procedures. Configure the database for recoverability. Use Recovery Manager (RMAN) to create backups and perform recovery operations. Use the Data Recovery Advisor to diagnose and repair failures. Use Oracle Flashback Technologies to recover from human error. Perform an encrypted database backup and restore. Perform tablespace point-in-time recovery. Describe additional high availability features such as Oracle Data Guard. This Oracle Database 12c: Backup and Recovery Workshop will teach you how to evaluate your own recovery requirements. You'll develop appropriate strategies for backup, restore and recovery procedures from provided scenarios. This Oracle Database 12c: Backup and Recovery Workshop will teach you how to evaluate your own recovery requirements. You'll develop appropriate strategies for backup, restore and recovery procedures from provided scenarios. Additional course details: Nexus Humans Oracle Database 12c - Backup and Recovery Workshop 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 Oracle Database 12c - Backup and Recovery Workshop 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 Oracle Database Administrator Data Warehouse Administrator Support Engineer Technical Consultant Technical Administrator Overview The student benefits by gaining a deeper understanding of possibly the most important job of a DBA - backup and recovery. The concepts and architecture that support backup and recovery, along with implementation steps in various ways and situations, are presented in detail. Students gain knowledge of the Recovery Manager (RMAN) command-line interface for various backup, failure, restore, and recovery scenarios, including data duplication. The student begins by gaining a deeper understanding of possibly the most important job of a DBA - backup and recovery. The concepts and architecture that support backup and recovery, along with implementation in various ways and situations are covered in detail. Students gain knowledge of the Recovery Manager (RMAN) command-line interface for various backup, failure, restore, and recovery scenarios, including data duplication. Introduction and Configuration Introduction Getting Started Configuring for Recoverablility Using the RMAN Recovery Catalog Backup Backup Strategies and Terminology Performing Backups Improving Your Backups Using RMAN-Encrypted Backups Recovery Diagnosing Failures Restore and Recovery Concepts Performing Complete Recovery Performing Point-in-Time Recovery Performing Additional Recovery Operations Additional Technologies Using Flashback Technologies Using Flashback Database Transporting Data Duplicating a Database RMAN Troubleshooting and Tuning Hands-On Backup and Recovery Workshop Additional course details: Nexus Humans Oracle Database: Backup and Recovery Workshop 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 Oracle Database: Backup and Recovery Workshop 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 The primary audience for this course are Application Consultants, Business Analysts, Business Process Owners/Team Leads/Power Users, Program/Project Managers, and Users. Overview Learn how to create queries in BEx Query DesignerLearn how to use advanced query functionsLearn how to perform OLAP analysis In this course, students obtain the knowledge to create query definitions using the BEx Query Designer and to make them available for OLAP analysis. Data Warehousing Describing Data Warehousing Describing Data Warehouse Architecture Using Reporting Tools Navigation Options in Reports Using the Navigation Options in Reports Saving Analysis Views Simple Queries Creating Simple Queries Finding a Query Filtering Query Definition Data Configuring Query Properties Key Figures and Structures in Queries Creating Restricted Key Figures Creating Calculated Key Figures Creating a New Formula with Boolean Operators Configuring Properties of Key Figures Using Exception and Nested Exception Aggregation Queries with Multiple Structures Creating Structures Resolving Formula Collision Designing Detailed Queries with the Cell Editor Characteristics and Hierarchies in Queries Configuring the Properties of Characteristics Running Display and Navigation Attribute Queries Adding Hierarchies to Reports Adding External Hierarchies to a Report Using Hierarchies and Structures Creating External Hierarchies Variables in Queries Using Variables Creating Characteristic Value and Text Variables in Queries Creating Hierarchy and Hierarchy Node Variables in Queries Creating Formula Variables in Queries Activating Business Content Variables Exceptions and Conditions in Queries Creating Exceptions in Query Design Creating Conditions in Query Design Report-Report Interface Using the Report-Report Interface Query Performance Optimization Optimizing Query Performance Configuring Query Read Mode Use Performance Monitoring Tools Queries Management and Authorizations Overview Managing Query Objects Describing Authorizations Reporting Options Outlining Reporting Options for SAP NetWeaver BW Additional course details: Nexus Humans BW305 SAP Business Warehouse Query Design and Analysis 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 BW305 SAP Business Warehouse Query Design and Analysis 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 Overview Our engaging instructors and mentors are highly-experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working within in a hands-on learning environment, guided by our expert team, attendees will explore: New Features Overview Multitenant New Features Security Features Cloud Services Networking Globalization Big Data Support Database Installation and Configuration Database Tuning Backup and Recovery Oracle 19c New Features is a hands-on course that explores the newest features such as Big Data Enhancements, Security, Multitenant features, Oracle Cloud Services, Networking, and much more. Oracle is one of the leading databases in industry today. Learn what their latest flagship product has to offer from industry experts. Oracle 19c New Features Overview Introduction to Oracle 19c New Features Oracle 19c Multitenant New Features Refreshable PDB Switchover PDB Integration with Data Guard PDB Snapshot Carousel CDB Fleet Management Oracle 19c Security Features Profile Lockdown Create a User Defined Master Encryption Key Encrypted Passwords in Database Links and Data Pump Create Keystores for Pluggable Databases Datapump and Unified Auditing Schema Only Accounts Oracle 19c Cloud Services Oracle IaaS Oracle Saas Oracle PaaS Oracle 19c Networking Database Connection Manager Database Proxy Support Tenant Isolation Oracle 19c Globalization New globalization for Bind Variables New Database Local Support Additional Unicode Support Big Data Support New Analytic Support Data Mining Data Warehouse Additional Parallel Processing Support Inline External Tables Database Installation and Configuration Zero Downtime Upgrades Dry Run Command implementation New location for Password File Improved Bulk Operations Database Tuning SQL Tuning Advisor and Exadata New SQL Tuning Set API Concurrent SQL and Sql Performance Analyzer Database In Memory Features In Memory Support for External Tables In Memory Features for Analytics Oracle 19c Backup and Recovery Active Pluggable Cloning Pluggable and non Pluggable Database Migration Additional course details: Nexus Humans Oracle 19c New Features (TTOR20019) 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 Oracle 19c New Features (TTOR20019) 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 Individuals planning to deploy applications and create application environments on Google Cloud. Developers, systems operations professionals, and solution architects getting started with Google Cloud. Executives and business decision makers evaluating the potential of Google Cloud to address their business needs. Overview Identify the purpose and value of Google Cloud products and services. Interact with Google Cloud services. Describe ways in which customers have used Google Cloud. Choose among and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine, and Compute Engine. Choose among and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore. Make basic use of BigQuery, Google's managed data warehouse for analytics. This course uses lectures, demos, and hands-on labs to give you an overview of Google Cloud products and services so that you can learn the value of Google Cloud and how to incorporate cloud-based solutions into your business strategies. Introducing Google Cloud Platform Explain the advantages of Google Cloud Platform. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Platform Identify the purpose of projects on Google Cloud Platform. Understand the purpose of and use cases for Identity and Access Management. List the methods of interacting with Google Cloud Platform. Lab: Getting Started with Google Cloud Platform. Google Compute Engine and Networking Identify the purpose of and use cases for Google Compute Engine. Understand the basics of networking in Google Cloud Platform. Lab: Deploying Applications Using Google Compute Engine. Google Cloud Platform Storage Options Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable. Learn how to choose between the various storage options on Google Cloud Platform. Lab: Integrating Applications with Google Cloud Storage. Google Container Engine Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Introduction to Hybrid and Multi-Cloud computing (Anthos). Lab: Deploying Applications Using Google Container Engine. Google App Engine and Google Cloud Datastore Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand the purpose of and use cases for Google Cloud Endpoints. Lab: Deploying Applications Using App Engine and Cloud Datastore. Deployment and Monitoring Understand the purpose of template-based creation and management of resources. Understand the purpose of integrated monitoring, alerting, and debugging. Lab: Getting Started with Stackdriver and Deployment Manager. Big Data and Machine Learning Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Lab: Getting Started with BigQuery. Summary and Review Summary and Review. What's Next?.

Duration 2 Days 12 CPD hours This course is intended for This course is intended for Data Warehouse Administrator, Database Administrator, Database Designer, Support Engineer, and Technical Administrator. Overview Upon successful completion of this course, students will be able to Install Oracle Grid Infrastructure for a Standalone Server, Configure ASMLIB and create ASM disk groups, Apply the latest patch set updates to the Grid Infrastructure software, Install Oracle Database software, Use Oracle Restart to manage components, Prepare the Linux operating system for Oracle software installation, Upgrade Oracle Database, Create a container database, Install Oracle Grid Infrastructure for an Independent Server, Create an Oracle Database using DBCA, and Install the latest patch set updates to the Oracle database software. This Oracle Database: Deploy, Patch and Upgrade Workshop gives you detailed information to help you install Oracle Database software. In this course, you will be introduced to Oracle Database Cloud Service. Oracle Database Overview Oracle Database Introduction Oracle Database Architecture Overview Oracle Database Instance Configurations Oracle Database Memory Structures Process Structures Database Storage Architecture Logical and Physical Database Structures Container and Pluggable Database Overview Installing Oracle Grid Infrastructure for a Standalone Server Overview of Oracle Grid Infrastructure for a Standalone Server System Requirements for Oracle Grid Infrastructure Configuring Storage for Oracle Automatic Storage Management (ASM) Installing Oracle Grid Infrastructure for a Standalone Server Upgrading Oracle Grid Infrastructure for a Standalone Server Installing Oracle Database Software Planning Your Installation System Requirements for Oracle Database Preparing the Operating System Using 4 KB Sector Disks Setting Environment Variables Checking the System Requirements Using the Oracle Universal Installer (OUI) Performing a Silent Mode Installation Creating an Oracle Database by Using DBCA Planning the Database Storage Structure Choosing non-CDB or CDB Types of Databases (based on workload) Choosing the Appropriate Character Set Understanding How Character Sets are Used Setting the NLS_LANG Initialization Parameter Using the Database Configuration Assistant (DBCA) Using Oracle Restart Oracle Restart Overview Oracle Restart Process startup Controlling Oracle Restart Choosing the Correct SRVCTL Utility Oracle Restart Configuration Using the SRVCTL Utility Obtaining Help for the SRVCTL Utility Starting Components by Using the SRVCTL Utility Introduction to Upgrading to Oracle Database Upgrade Methods Data Migration Methods Supported Releases for Direct Upgrade Overview of Upgrade Process Performing a Rolling Upgrade Upgrading a CBD Preparing to Upgrade to Oracle Database Developing a Test Plan Performance Testing Requirements for Databases Using Oracle Label Security or Oracle Database Vault Requirement for Databases Using Oracle Warehouse Builder Using the Pre-Upgrade Information Tool Backing Up the Database Installing the Oracle Database Software Preparing the New Oracle Home Upgrading to Oracle Database Upgrading by Using the Database Upgrade Assistant (DBUA) Manually Upgrading to Oracle Database Migrating a non-CDB to a CDB Performing Post-Upgrade Tasks Migrating to Unified Auditing Performing Post-Upgrade Tasks Following a Manual Upgrade Migrating Data by Using Oracle Data Pump Data Pump Overview Migrating by Using Data Pump Importing by Using a Network Link

Duration 2 Days 12 CPD hours This course is intended for Cloud Solutions Architects, Site Reliability Engineers, Systems Operations professionals, DevOps Engineers, IT managers. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform. Overview Apply a tool set of questions, techniques and design considerations Define application requirements and express them objectively as KPIs, SLO's and SLI's Decompose application requirements to find the right microservice boundaries Leverage Google Cloud developer tools to set up modern, automated deployment pipelines Choose the appropriate Google Cloud Storage services based on application requirements Architect cloud and hybrid networks Implement reliable, scalable, resilient applications balancing key performance metrics with cost Choose the right Google Cloud deployment services for your applications Secure cloud applications, data and infrastructure Monitor service level objectives and costs using Stackdriver tools This course features a combination of lectures, design activities, and hands-on labs to show you how to use proven design patterns on Google Cloud to build highly reliable and efficient solutions and operate deployments that are highly available and cost-effective. This course was created for those who have already completed the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course. Defining the Service Describe users in terms of roles and personas. Write qualitative requirements with user stories. Write quantitative requirements using key performance indicators (KPIs). Evaluate KPIs using SLOs and SLIs. Determine the quality of application requirements using SMART criteria. Microservice Design and Architecture Decompose monolithic applications into microservices. Recognize appropriate microservice boundaries. Architect stateful and stateless services to optimize scalability and reliability. Implement services using 12-factor best practices. Build loosely coupled services by implementing a well-designed REST architecture. Design consistent, standard RESTful service APIs. DevOps Automation Automate service deployment using CI/CD pipelines. Leverage Cloud Source Repositories for source and version control. Automate builds with Cloud Build and build triggers. Manage container images with Google Container Registry. Create infrastructure with code using Deployment Manager and Terraform. Choosing Storage Solutions Choose the appropriate Google Cloud data storage service based on use case, durability, availability, scalability and cost. Store binary data with Cloud Storage. Store relational data using Cloud SQL and Spanner. Store NoSQL data using Firestore and Cloud Bigtable. Cache data for fast access using Memorystore. Build a data warehouse using BigQuery. Google Cloud and Hybrid Network Architecture Design VPC networks to optimize for cost, security, and performance. Configure global and regional load balancers to provide access to services. Leverage Cloud CDN to provide lower latency and decrease network egress. Evaluate network architecture using the Cloud Network Intelligence Center. Connect networks using peering and VPNs. Create hybrid networks between Google Cloud and on-premises data centers using Cloud Interconnect. Deploying Applications to Google Cloud Choose the appropriate Google Cloud deployment service for your applications. Configure scalable, resilient infrastructure using Instance Templates and Groups. Orchestrate microservice deployments using Kubernetes and GKE. Leverage App Engine for a completely automated platform as a service (PaaS). Create serverless applications using Cloud Functions. Designing Reliable Systems Design services to meet requirements for availability, durability, and scalability. Implement fault-tolerant systems by avoiding single points of failure, correlated failures, and cascading failures. Avoid overload failures with the circuit breaker and truncated exponential backoff design patterns. Design resilient data storage with lazy deletion. Analyze disaster scenarios and plan for disaster recovery using cost/risk analysis. Security Design secure systems using best practices like separation of concerns, principle of least privilege, and regular audits. Leverage Cloud Security Command Center to help identify vulnerabilities. Simplify cloud governance using organizational policies and folders. Secure people using IAM roles, Identity-Aware Proxy, and Identity Platform. Manage the access and authorization of resources by machines and processes using service accounts. Secure networks with private IPs, firewalls, and Private Google Access. Mitigate DDoS attacks by leveraging Cloud DNS and Cloud Armor. Maintenance and Monitoring Manage new service versions using rolling updates, blue/green deployments, and canary releases. Forecast, monitor, and optimize service cost using the Google Cloud pricing calculator and billing reports and by analyzing billing data. Observe whether your services are meeting their SLOs using Cloud Monitoring and Dashboards. Use Uptime Checks to determine service availability. Respond to service outages using Cloud Monitoring Alerts. Additional course details: Nexus Humans Architecting with Google Cloud: Design and Process 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 Architecting with Google Cloud: Design and Process 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.