1561 CLO courses in Cardiff delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for This class is designed for experienced Salesforce Administrators who are responsible for setting up, configuring, and managing Service Cloud. Prior to taking this class, you should have a solid understanding of Salesforce functionality and concepts, at least 6 months of experience using Salesforce, and the Salesforce Administrator credential or equivalent knowledge. Overview Set up the case management process automating the support process with queues, assignment/escalation rules, and Process Builder. Configure Salesforce knowledge to help you manage the creation, publication, and maintenance of knowledge articles. Enable entitlements to set up service contracts. Set up the Salesforce Service Console app to help your support reps work more efficiently. Understand the capabilities of the Softphone Utility in the Lightning Console. Configure online chat with customers using Web Chats. Understand and set up communities. Leverage Service Cloud to scale your support efforts and improve customer service. In this 2-day class, Service Cloud experts will walk you through how to configure and maintain Service Cloud for your organization. Learn how to set up service contracts with milestones and entitlements, set up the Service Console application, add the Softphone Utility to your Lightning Console, and set up Web Chats to provide frictionless customer support. Learn how to configure a Customer Community so you can connect customers to knowledge articles and community members to find answers instantly. Case Escalations and Entitlements Create processes to streamline a support team?s workflow and case management. Customize fields, page layouts, and record types for different kinds of support cases. Define picklist values for each new record type. Create case assignment rules, queues, and escalation rules to push cases to the appropriate support team at the appropriate time. Create and manage entitlements to customize the level of support for each customer. Salesforce Knowledge Enable Lightning Knowledge and assign appropriate user licenses. Customize page layouts and record types to support knowledge article management. Customize access to, permissions for, and visibility of knowledge tools and processes. Create and manage articles to ensure quality of information. Manage and close cases more efficiently using knowledge articles. Lightning Service Console Create your own Service Console app. Customize the Lightning Console pages. Add Utilities to your console. Enable and utilize Chat (formerly Live Agent). Optimize the use of Omni-Channel. Salesforce Self-Service Communities Enable communities in your Salesforce org. Create a permission set for effective administration of communities. Customize the look and layout of the community. Add the Reputation component to the community. Additional course details: Nexus Humans Salesforce Administer and Maintain Service Cloud (ADX261) 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 Salesforce Administer and Maintain Service Cloud (ADX261) 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 Software developers, system administrators, and IT professionals who are focused on Microsoft Windows Overview Configuring Microsoft Windows and Microsoft SQL Server in Google Compute Engine. Deploying ASP.NET MVC applications to Google Compute Engine. Deploying .NET Core applications to Google Compute Engine, Google Compute Engine, and Google Container Engine Learn how to create Windows virtual machines on Google Cloud so that you can deploy and run Microsoft Windows applications. In this course, you'll learn how to run SQL Server in Compute Engine, how to deploy instances across Google Cloud zones, and how to get more out of ASP.NET on Compute Engine, Google Container Engine, and App Engine. Introduction to Google Cloud Platform Scope and structure of GCP. Options for Windows deployment on GCP. GCP interfaces. Windows Workloads on Google Compute Engine Google Compute Engine virtual machine options. Integrating Active Directory with Google Compute Engine virtual machines. Options for running SQL Server in Google Compute Engine. Configuring SQL Server for high availability. Developing ASP.NET MVC applications Model-view-controller structure. Using Microsoft Visual Studio?s Web Project template to develop in ASP.NET. Deploying applications to Microsoft Internet Information Server (IIS) in GCE. Configuring Resilient Workloads Deploying instances across GCP zones. Using instance groups to create pools of virtual machines. Load balancing Windows applications. Delivering Next-Generation ASP.NET Core on GCP Understanding .NET Core and EF Core. Options for deploying ASP.NET Core applications on Google Cloud Platform. Deploying ASP.NET Core applications on Google Compute Engine. Deploying ASP.NET Core applications on Google Container Engine. Deploying ASP.NET Core applications on Google App Engine. Additional course details: Nexus Humans Develop and Deploy Windows Applications on Google Cloud Platform 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 Develop and Deploy Windows Applications on Google Cloud Platform 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 This class is designed for email digital marketers who manage the email channel for their organization. Whether you are new to Marketing Cloud or looking for tips on how to improve your existing customer journeys, this class is a great place to start. No prior knowledge of Marketing Cloud is needed. Overview When you complete this course, you will be able to: Explain compliance concepts to ensure optimal deliverability. Use tools within Marketing Cloud to uphold deliverability standards. Utilize Email Design best practices to ensure the best customer experience. Develop effective, relevant messages using Content Builder. Design and test different delivery methods and options when sending an email message. Design and execute customer journeys using automation tools within Marketing Cloud. Differentiate the use cases for different automation activities in Automation Studio and Journey Builder. Define fundamental data management and structure terminology. Use data segmentation tools to create targeted emails. Apply a simple data model concept to a real-world scenario. Define subscriber statuses, unsubscribe methods, and preferences. Analyze marketing campaigns using common KPIs. Solve a common marketing problem using troubleshooting guidance. Prioritize testing methods and tools to ensure quality control. Explain fundamental account and sending administration. Know where to go for more information, guidance, and support. Describe capabilities across the platform. Start your journey to becoming a Marketing Cloud Specialist. In this 5-day, expert-led class, you will learn how to build customer journeys within Marketing Cloud. Our team of Marketing Cloud pros will walk you through best practices related to executing, monitoring, and analyzing your journeys, arming you with the tools and know-how to design personalized journeys and engage with your customers in a whole new way. Course Outline Introduction to Salesforce Marketing Cloud Administration Subscriber and Data Management Email Message Design and Creation Message Testing, Delivery, and Email Marketing Best Practices Marketing Automation Analytics and Troubleshooting Summary

Duration 4 Days 24 CPD hours This course is intended for This course is appropriate for developers and administrators who intend to use HBase. Overview Skills learned on the course include:The use cases and usage occasions for HBase, Hadoop, and RDBMSUsing the HBase shell to directly manipulate HBase tablesDesigning optimal HBase schemas for efficient data storage and recoveryHow to connect to HBase using the Java API, configure the HBase cluster, and administer an HBase clusterBest practices for identifying and resolving performance bottlenecks Cloudera University?s four-day training course for Apache HBase enables participants to store and access massive quantities of multi-structured data and perform hundreds of thousands of operations per second. Introduction to Hadoop & HBase What Is Big Data? Introducing Hadoop Hadoop Components What Is HBase? Why Use HBase? Strengths of HBase HBase in Production Weaknesses of HBase HBase Tables HBase Concepts HBase Table Fundamentals Thinking About Table Design The HBase Shell Creating Tables with the HBase Shell Working with Tables Working with Table Data HBase Architecture Fundamentals HBase Regions HBase Cluster Architecture HBase and HDFS Data Locality HBase Schema Design General Design Considerations Application-Centric Design Designing HBase Row Keys Other HBase Table Features Basic Data Access with the HBase API Options to Access HBase Data Creating and Deleting HBase Tables Retrieving Data with Get Retrieving Data with Scan Inserting and Updating Data Deleting Data More Advanced HBase API Features Filtering Scans Best Practices HBase Coprocessors HBase on the Cluster How HBase Uses HDFS Compactions and Splits HBase Reads & Writes How HBase Writes Data How HBase Reads Data Block Caches for Reading HBase Performance Tuning Column Family Considerations Schema Design Considerations Configuring for Caching Dealing with Time Series and Sequential Data Pre-Splitting Regions HBase Administration and Cluster Management HBase Daemons ZooKeeper Considerations HBase High Availability Using the HBase Balancer Fixing Tables with hbck HBase Security HBase Replication & Backup HBase Replication HBase Backup MapReduce and HBase Clusters Using Hive & Impala with HBase Using Hive and Impala with HBase Appendix A: Accessing Data with Python and Thrift Thrift Usage Working with Tables Getting and Putting Data Scanning Data Deleting Data Counters Filters Appendix B: OpenTSDB

Duration 5 Days 30 CPD hours This course is intended for System administrators, IT security administrators, IT security engineers, and other professionals responsible for designing, implementing, maintaining, and managing the security of Red Hat Enterprise Linux systems and ensuring their compliance with the organization's security policies. Be a Red Hat Certified Engineer (RHCE©), or demonstrate equivalent Red Hat Enterprise Linux knowledge and experience. Overview Students that complete this course should be able to demonstrate these skills: - Analyze and remediate system compliance using OpenSCAP and SCAP Workbench, employing and customizing baseline policy content provided with Red Hat Enterprise Linux. - Monitor security-relevant activity on your systems with the kernel's audit infrastructure. - Explain and implement advanced SELinux techniques to restrict access by users, processes, and virtual machines. - Confirm the integrity of files and their permissions with AIDE. - Prevent unauthorized USB devices from being used with USBGuard. - Protect data at rest but provide secure automatic decryption at boot using NBDE. - Proactively identify risks and misconfigurations of systems and remediate them with Red Hat Insights. - Analyze and remediate compliance at scale with OpenSCAP, Red Hat Insights, Red Hat Satellite, and Red Hat Ansible Tower. This course is ideal for security administrators and system administrators who need to manage the secure operation of servers running Red Hat© Enterprise Linux©, whether deployed on physical hardware, as virtual machines, or as cloud instances. Maintaining security of computing systems is a process of managing risk through the implementation of processes and standards backed by technologies and tools. In this course, you will discover and understand the resources that can be used to help you implement and comply with your security requirements. This course is based on Red Hat Enterprise Linux 7.5, Red Hat Satellite 6.3, Red Hat Ansible© Engine 2.5, Red Hat Ansible Tower 3.2, and Red Hat Insights. 1 - MANAGE SECURITY AND RISK Define strategies to manage security on Red Hat Enterprise Linux servers. 2 - AUTOMATE CONFIGURATION AND REMEDIATION WITH ANSIBLE Remediate configuration and security issues with Ansible Playbooks. 3 - PROTECT DATA WITH LUKS AND NBDE Encrypt data on storage devices with LUKS and use NBDE to manage automatic decryption when servers are booted. 4 - RESTRICT USB DEVICE ACCESS Protect system from rogue USB device access with USBGuard. 5 - CONTROL AUTHENTICATION WITH PAM Manage authentication, authorization, session settings, and password controls by configuring pluggable authentication modules (PAMs). 6 - RECORD SYSTEM EVENTS WITH AUDIT Record and inspect system events relevant to security, using the Linux kernel's audit subsystem and supporting tools. 7 - MONITOR FILE SYSTEM CHANGES Detect and analyze changes to a server's file systems and their contents using AIDE. 8 - MITIGATE RISK WITH SELINUX Improve security and confinement between processes by using SELinux and advanced SELinux techniques and analyses. 9 - MANAGE COMPLIANCE WITH OPENSCAP Evaluate and remediate a server's compliance with security policies by using OpenSCAP. 10 - AUTOMATE COMPLIANCE WITH RED HAT SATELLITE Automate and scale your ability to perform OpenSCAP checks and remediate compliance issues using Red Hat Satellite. 11 - ANALYZE AND REMEDIATE ISSUES WITH RED HAT INSIGHTS Identify, detect, and correct common issues and security vulnerabilities with Red Hat Enterprise Linux systems by using Red Hat Insights. 12 - PERFORM A COMPREHENSIVE REVIEW Review the content covered in this course by completing hands-on review exercises. Additional course details: Nexus Humans Red Hat Security - Linux in Physical, Virtual, and Cloud (RH415) 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 Red Hat Security - Linux in Physical, Virtual, and Cloud (RH415) 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.

Successfully closing a sale and negotiating the best outcome for the business is a key skill for all salespeople, and often an area that is overlooked. Investing in this skill will have a positive impact on interactions with customers, both new and existing, and lead to improved sales performance. Whilst understanding how to reach a conclusion with a customer faster means increased efficiency and more time to invest in sourcing new business. We have developed this programme to be practical, fun and interactive. Participants will learn proven techniques for influencing, persuading and negotiating with clients, gain increased confidence and clarity when reviewing contract terms and prices, and understand how to structure and manage sales negotiation and contract review meetings. This course will help participants: Learn a structured and proven approach to the negotiation of contract terms Apply the key principles of negotiation, playing the person and the problem Create a contract negotiation strategy - from opening to close Recognize and put to use proven negotiation tactics and techniques Learn how to embrace conflict positively - to 'say no, then negotiate' Plan and prepare for any commercial negotiation conversations Understand the stages of negotiation and how to move through them 1 Closing and negotiating from a position of personal power The eight steps of a sales or commercial negotiation Ten ways to resist price pressure How to draw on sources of power when you have less authority The six principles of influence and persuasion and how to use them 2 Effective negotiation - planning and theory How to plan and structure your negotiation for a successful and quick conclusion Influence: knowing how to 'push or pull' to win an argument Achieving a BATNA - a range of practical skills and techniques Case study: planning for a client negotiation around contract or price issues 3 Effective closing and negotiation - practice and reality Higher-level questioning techniques to investigate and solve problems Listening to lead - active listening and structuring your conversation The most common 'unforced' negotiation mistakes and errors Case study: setting objectives, sources of value, trading concessions 4 Sales negotiation tactics and playing the game How high - how hard - how soon; why now How to identify hidden or perceived currencies and values How to use these to establish a higher base price Negotiation best-practice checklist and summary

Duration 3 Days 18 CPD hours This course is intended for This class is intended for the following job roles: [Cloud] information security analysts, architects, and engineers Information security/cybersecurity specialists Cloud infrastructure architects Additionally, the course is intended for Google and partner field personnel who work with customers in those job roles. The course should also be useful to developers of cloud applications Overview This course teaches participants the following skills: Understanding the Google approach to security Managing administrative identities using Cloud Identity. Implementing least privilege administrative access using Google Cloud Resource Manager, Cloud IAM. Implementing IP traffic controls using VPC firewalls and Cloud Armor Implementing Identity Aware Proxy Analyzing changes to the configuration or metadata of resources with GCP audit logs Scanning for and redact sensitive data with the Data Loss Prevention API Scanning a GCP deployment with Forseti Remediating important types of vulnerabilities, especially in public access to data and VMs This course gives participants broad study of security controls and techniques on Google Cloud Platform. Through lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution. Participants also learn mitigation techniques for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. Foundations of GCP Security Google Cloud's approach to security The shared security responsibility model Threats mitigated by Google and by GCP Access Transparency Cloud Identity Cloud Identity Syncing with Microsoft Active Directory Choosing between Google authentication and SAML-based SSO GCP best practices Identity and Access Management GCP Resource Manager: projects, folders, and organizations GCP IAM roles, including custom roles GCP IAM policies, including organization policies GCP IAM best practices Configuring Google Virtual Private Cloud for Isolation and Security Configuring VPC firewalls (both ingress and egress rules) Load balancing and SSL policies Private Google API access SSL proxy use Best practices for structuring VPC networks Best security practices for VPNs Security considerations for interconnect and peering options Available security products from partners Monitoring, Logging, Auditing, and Scanning Stackdriver monitoring and logging VPC flow logs Cloud audit logging Deploying and Using Forseti Securing Compute Engine: techniques and best practices Compute Engine service accounts, default and customer-defined IAM roles for VMs API scopes for VMs Managing SSH keys for Linux VMs Managing RDP logins for Windows VMs Organization policy controls: trusted images, public IP address, disabling serial port Encrypting VM images with customer-managed encryption keys and with customer-supplied encryption keys Finding and remediating public access to VMs VM best practices Encrypting VM disks with customer-supplied encryption keys Securing cloud data: techniques and best practices Cloud Storage and IAM permissions Cloud Storage and ACLs Auditing cloud data, including finding and remediating publicly accessible data Signed Cloud Storage URLs Signed policy documents Encrypting Cloud Storage objects with customer-managed encryption keys and with customer-supplied encryption keys Best practices, including deleting archived versions of objects after key rotation BigQuery authorized views BigQuery IAM roles Best practices, including preferring IAM permissions over ACLs Protecting against Distributed Denial of Service Attacks: techniques and best practices How DDoS attacks work Mitigations: GCLB, Cloud CDN, autoscaling, VPC ingress and egress firewalls, Cloud Armor Types of complementary partner products Application Security: techniques and best practices Types of application security vulnerabilities DoS protections in App Engine and Cloud Functions Cloud Security Scanner Threat: Identity and Oauth phishing Identity Aware Proxy Content-related vulnerabilities: techniques and best practices Threat: Ransomware Mitigations: Backups, IAM, Data Loss Prevention API Threats: Data misuse, privacy violations, sensitive/restricted/unacceptable content Mitigations: Classifying content using Cloud ML APIs; scanning and redacting data using Data Loss Prevention API Additional course details: Nexus Humans Security in Google 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 Security in Google 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 2 Days 12 CPD hours This course is intended for This class is intended for network engineers and network admins that are either using Google Cloud Platform or are planning to do so. The class is also for individuals that want to be exposed to software-defined networking solutions in the cloud. Overview Configure Google VPC networks, subnets, and routers Control administrative access to VPC objects Control network access to endpoints in VPCsInterconnect networks among GCP projects Interconnect networks among GCP VPC networks and on-premises or other-cloud networks Choose among GCP load balancer and proxy options and configure them Use Cloud CDN to reduce latency and save money Optimize network spend using Network TiersConfigure Cloud NAT or Private Google Access to provide instances without public IP addresses access to other services Deploy networks declaratively using Cloud Deployment Manager or Terraform Design networks to meet common customer requirements Configure monitoring and logging to troubleshoot networks problems Learn about the broad variety of networking options on Google Cloud. This course uses lectures, demos, and hands-on labs to help you explore and deploy Google Cloud networking technologies, including Virtual Private Cloud (VPC) networks, subnets, and firewalls; interconnection among networks; load balancing; Cloud DNS; Cloud CDN; and Cloud NAT. You'll also learn about common network design patterns and automated deployment using Cloud Deployment Manager or Terraform. Google Cloud VPC Networking Fundamentals Recall that networks belong to projects. Explain the differences among default, auto, and custom networks. Create networks and subnets. Explain how IPv4 addresses are assigned to Compute Engine instances. Publish domain names using Google Cloud DNS. Create Compute Engine instances with IP aliases. Create Compute Engine instances with multiple virtual network. Controlling Access to VPC Networks Outline how IAM policies affect VPC networks. Control access to network resources using service accounts. Control access to Compute Engine instances with tag-based firewall rules. Sharing Networks across Projects Outline the overall workflow for configuring Shared VPC. Differentiate between the IAM roles that allow network resources to be managed. Configure peering between unrelated VPC Networks. Recall when to use Shared VPC and when to use VPC Network Peering. Load Balancing Recall the various load balancing services. Configure Layer 7 HTTP(S) load balancing. Whitelist and blacklist IP traffic with Cloud Armor. Cache content with Cloud CDN. Explain Layer 4 TCP or SSL proxy load balancing. Explain regional network load balancing. Configure internal load balancing. Recall the choices for enabling IPv6 Internet connectivity for Google Cloud load balancers. Determine which Google Cloud load balancer to use when. Hybrid Connectivity Recall the Google Cloud interconnect and peering services available to connect your infrastructure to Google Cloud. Explain Dedicated Interconnect and Partner Interconnect. Describe the workflow for configuring a Dedicated Interconnect. Build a connection over a VPN with Cloud Router. Determine which Google Cloud interconnect service to use when. Explain Direct Peering and Partner Peering. Determine which Google Cloud peering service to use when. Networking Pricing and Billing Recognize how networking features are charged for. Use Network Service Tiers to optimize spend. Determine which Network Service Tier to use when. Recall that labels can be used to understand networking spend. Network Design and Deployment Explain common network design patterns. Configure Private Google Access to allow access to certain Google Cloud services from VM instances with only internal IP addresses. Configure Cloud NAT to provide your instances without public IP addresses access to the internet. Automate the deployment of networks using Deployment Manager or Terraform. Launch networking solutions using Cloud Marketplace. Network Monitoring and Troubleshooting Configure uptime checks, alerting policies and charts for your network services. Use VPC Flow Logs to log and analyze network traffic behavior.

Duration 3 Days 18 CPD hours This course is intended for Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.

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.