2196 Courses in Cardiff delivered Live Online

This course is designed for all those who are planning to visit Greece and would like to learn and practice common and useful Greek phrases used when travelling. This mini-course introduces different aspects of Greek for tourism, working on main language points and useful Greek vocabulary through a variety of topics related to the tourist industry. After the completion of the course you will be able to communicate in basic everyday circumstances. The course is designed to be completed in 10 days – 10 lessons of 60 minutes each. The lessons are supported by slides (including readers and exercises), audios, and video files. All you need is a computer and an Internet connection, and you are ready to go!

Duration 4 Days 24 CPD hours This course is intended for Data Modelers Overview Please refer to course overview This offering provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using IBM Cognos Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the web, enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Framework Manager Model data and identifying related data Define requirements and modeling strategies Overview of IBM Cognos Framework Manager Create a baseline project Extend a model Prepare reusable metadata Model for predictable results in IBM Cognos Framework Manager Identify query issues Identify reporting traps Model virtual star schemas Use query subjects, modify relationships, and consolidate metadata using virtual objects Create calculations, filter data, and customize metadata for runtime Implement a time dimension and specify determinants Model for presentation in IBM Cognos Framework Manager Create a presentation view Examine data source query subject types and stored procedure query subject types Specify data security and package security Specify object security and dynamic data security Create analysis objects Manage OLAP data sources Advanced capabilities in IBM Cognos Framework Manager Explore SQL generation and the use of governors Examine the use of IBM Cognos SQL and generated SQL for DMR data Other query considerations Use session parameters, prompt macros, and security macro functions Use materialized views, minimize SQL, and enable Dynamic Query Mode (DQM) DQM, CQM, caching metadata, query processing, aggregate calculation, and other ways to improve performance Extended capabilities in IBM Cognos Framework Manager Perform basic maintenance and management on a model Remap metadata to another source and import and link additional data sources Run scripts to automate or update a model and report on a model Segment a project, link a project, and branch a model Nest packages and specify package languages and functions Explore additional modeling techniques and customize metadata for a multilingual audience Additional course details: Nexus Humans B6252 IBM Cognos Framework Manager: Design Metadata Models v11.1.x 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 B6252 IBM Cognos Framework Manager: Design Metadata Models v11.1.x 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 4 Days 24 CPD hours This course is intended for Data Modelers Overview Please refer to course overview This offering provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the web, enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Framework Manager Model data and identifying related data Define requirements and modeling strategies Overview of IBM Cognos Framework Manager Create a baseline project Extend a model Prepare reusable metadata Model for predictable results in IBM Cognos Framework Manager Identify query issues Identify reporting traps Model virtual star schemas Use query subjects, modify relationships, and consolidate metadata using virtual objects Create calculations, filter data, and customize metadata for runtime Implement a time dimension and specify determinants Model for presentation in IBM Cognos Framework Manager Create a presentation view Examine data source query subject types and stored procedure query subject types Specify data security and package security Specify object security and dynamic data security Create analysis objects Manage OLAP data sources Advanced capabilities in IBM Cognos Framework Manager Explore SQL generation and the use of governors Examine the use of IBM Cognos SQL and generated SQL for DMR data Other query considerations Use session parameters, prompt macros, and security macro functions Use materialized views, minimize SQL, and enable Dynamic Query Mode (DQM) DQM, CQM, caching metadata, query processing, aggregate calculation, and other ways to improve performance Extended capabilities in IBM Cognos Framework Manager (Optional) Perform basic maintenance and management on a model Remap metadata to another source and import and link additional data sources Run scripts to automate or update a model and report on a model Segment a project, link a project, and branch a model Nest packages and specify package languages and functions Explore additional modeling techniques and customize metadata for a multilingual audience Additional course details: Nexus Humans B6152 IBM Cognos Framework Manager - Design Metadata Models v11.0.x 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 B6152 IBM Cognos Framework Manager - Design Metadata Models v11.0.x course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is appropriate for anyone needing to interface with an Oracle database or those needing a general understanding of Oracle database functionality. That would include end users, business analysts, application developers and database administrators. Overview Working in a hands-on learning environment led by our expert pracitioner you'll learn how to: Add Data, Retrieve, Sort and Organize a SQL Database Combine Data, Set Operators and Subqueries Manipulate Data and Data Definition Languages in SQL Work with Data Dictionary Views and Create Sequences, Indexes and Views Use Database Objects and Subqueries Perform Data and access control Perform other Advanced Level Database operations. Oracle 19C SQL Programming Fundamentals Is a three-day, hands-on course designed to equip you with the fundamental skills needed to set up, run and manage SQL databases using Oracle Database Technology. You will also be discovering all the tools and concepts required to organize data efficiently. 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 develop a practical approach to Oracle Database Technology. Throughout the course, you will learn the key elements of a database, and the way Oracle systems facilitate their induction in the system. You?ll also learn the tools and strategies you can implement to store, retrieve, compare and organize data according to your requirements. You?ll also explore the process of creating simple to complex reports from existing data. By the end of this course, you will also have hands-on knowledge of SQL systems that are required to proceed to other advanced to professional programs. Adding Data, Retrieving, Sorting and Organizing a SQL Database The building blocks of a database. How to add data to the database. The process of retrieving data using SQL functions. Multiple methods of sorting and organizing data. Using SQL functions to get the required simple to complex output. Various strategies for using functions and conditions to organize data. Combining Data, Set Operators And Subqueries Consolidating data using multiple functions and group operators. Fetching intelligent data reports using simple functions. Fetching data from multiple sources in the tables. Using Subqueries to compile data as required. Using Set operators to create smart data reports. Data Manipulation and Data Definition Languages in SQL Describing and managing data transaction using Data Definition Language. Categorize and review data tables using Data Definition Language. Data Dictionary Views and Creating Sequences, Indexes and Views How to manage and query Data Dictionary Views. The process of creating and using Sequences. How to create various types of Synonyms and Indexes. Creating simple and complex views and retrieving data. Understanding and using Database Objects and Subqueries Core concept and application of Schema Objects. Fetching required data with Subqueries. Using Subqueries to organize Data in SQL. Data and access control Assigning and revoking data access. Managing data access control according to user levels. Performing Advanced Level Database operations. Using advanced functions and performing data queries. Creating and managing time zone-based databases.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for customer service professionals with any level of experience who want to expand their knowledge, improve their skill set, and increase the understanding of customer benefits. Overview In this course, you will develop the skills to coach for results. You will:  Describe the benefits of customer service, identify internal customers, identify the benefits to you of giving good customer service, and identify how you can help your company to excel. Identify the major trends in customer service today and the combination of criteria required for customer satisfaction. Identify the benefits of bringing respect, emotional support, and a personal touch to customer interactions, and apply the personal touch to customer interactions. Identify the six categories of face-to-face communication, the critical success factors in face-to-face communication, and the benefits of actively listening to your customers. Identify remote customer service communication channels and apply remote customer service best practices. Identify guidelines for handling unreasonable customers, explore ways to handle angry customers, and identify guidelines for handling unhelpful colleagues. Take action to increase the loyalty of the customers you serve. You will also identify guidelines for dealing with moments of truth, identify the benefits of customer complaints, identify the steps in the service recovery process, and analyze the moments of truth in a real-life situation. As a customer service representative, you are expected to handle customer interactions in the best way possible. The expectations of both your company and your customers hinge on your ability to provide the right service in the right way. In this course, you will explore the background and techniques of customer interactions.Providing quality customer care ensures that every single contact with your company is a positive experience. Customers can range from external consumers to internal employees in other departments. Knowing how to provide the same level of service to all customers will enrich your time spent at work by establishing positive business relationships. Recognizing crucial points throughout customer interactions increases your ability to solve problems and offer affirmative solutions. Applying this knowledge to trends in service and consumer desires allows you to contribute to the company?s bottom line and make a customer?s life a little easier. Understanding Customer Service Describe Customer Service Benefits Recognize the Importance of Internal Customer Service Identify How Customer Service Benefits You Excel with Customer Service Identifying How Customers Define the Success of Your Company Recognize Trends in Customer Service Identify Criteria for Customer Satisfaction Increasing Customer Satisfaction Identify Characteristics of the Personal Touch Create Lasting Positive Impressions on Your Customers Providing Face-to-Face Customer Service Identify Categories of Face-to-Face Contact Understand the Critical Success Factors in Face-to-Face Customer Service Identify the Characteristics of Active Listening Providing Remote Customer Service Identify Remote Customer Service Communication Channels Apply Remote Customer Service Best Practices Engaging Difficult Customers Serve Difficult Customers Manage Angry Customers Deal with Difficult or Unhelpful Colleagues Increasing Customer Loyalty Optimize Moments of Truth Recognize the Value of Customer Complaints Identify the Stages of the Service Recovery Process

Duration 1 Days 6 CPD hours This course is intended for This class is intended for the following: Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports. Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. Overview This course teaches students the following skills:Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.Employ BigQuery and Cloud Datalab to carry out interactive data analysis.Train and use a neural network using TensorFlow.Employ ML APIs.Choose between different data processing products on the Google Cloud Platform. This course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. Introducing Google Cloud Platform Google Platform Fundamentals Overview. Google Cloud Platform Big Data Products. Compute and Storage Fundamentals CPUs on demand (Compute Engine). A global filesystem (Cloud Storage). CloudShell. Lab: Set up a Ingest-Transform-Publish data processing pipeline. Data Analytics on the Cloud Stepping-stones to the cloud. Cloud SQL: your SQL database on the cloud. Lab: Importing data into CloudSQL and running queries. Spark on Dataproc. Lab: Machine Learning Recommendations with Spark on Dataproc. Scaling Data Analysis Fast random access. Datalab. BigQuery. Lab: Build machine learning dataset. Machine Learning Machine Learning with TensorFlow. Lab: Carry out ML with TensorFlow Pre-built models for common needs. Lab: Employ ML APIs. Data Processing Architectures Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow. Reference architecture for real-time and batch data processing. Summary Why GCP? Where to go from here Additional Resources Additional course details: Nexus Humans Google Cloud Platform Big Data and Machine Learning Fundamentals 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 Google Cloud Platform Big Data and Machine Learning Fundamentals 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 course is designed for Collaboration engineers and administration professionals in job roles such as: Network administrator Network architect Network designer Network engineer Network manager Overview After taking this course, you should be able to: Analyze and troubleshoot SIP, H.323, and media protocols Implement time-of-day routing, call park, call pickup, and meet-me conferences in Cisco Unified Communications Manager Implement call coverage in Cisco Unified Communications Manager Configure and troubleshoot Cisco Unified Communications Manager Device Mobility Configure and troubleshoot Cisco Unified Communications Manager Extension Mobility Configure and troubleshoot Cisco Unified Communications Manager Unified Mobility Implement Cisco Unified Communications Manager Express for SIP phones Implement globalized call routing within and between Cisco Unified Communications Manager clusters Implement Media Gateway Control Protocol (MGCP) fallback and Survivable Remote Site Telephony (SRST) in Cisco Unified Communications Manager and in Cisco IOS XE gateways Implement Call Admission Control and Automated Alternate Routing (AAR) in Cisco Unified Communications Manager Implement URI calling in Cisco Unified Communications Manager for calls within a cluster and between clusters Troubleshoot multisite Cisco Unified Communications Manager deployments Implement Intercluster Lookup Service (ILS) between Cisco Unified Communications Manager clusters and enable General Data Protection Regulation (GDPR) Configure and troubleshoot Cisco Unified Border Element In this course, you will learn how to use Cisco© Unified Communications Manager features to consolidate your communications infrastructure into a scalable, portable, and secure collaboration solution. This course prepares you for the 300-815 Implementing Cisco Advanced Call Control and Mobility Services (CLACCM) concentration exam and CCNP-Collaboration certification. Course Outline Analyzing and Troubleshooting Signaling and Media Protocols Implementing Cisco Unified Communications Manager Supplemental Services Implementing Call Coverage in Cisco Unified Communications Manager Configuring and Troubleshooting Cisco Unified Communications Manager Device Mobility Configuring and Troubleshooting Cisco Unified Communications Manager Extension Mobility Configuring and Troubleshooting Cisco Unified CM Unified Mobility Implementing Cisco Unified Communications Manager Express Implementing Globalized Call Routing Implementing Remote Site Survivability Implementing Call Admission Control in Cisco Unified Communications Manager Implementing URI Calling in Cisco Unified Communications Manager Troubleshooting Multisite Cisco Unified Communications Manager Deployments Examining Global Dial Plan Replication Configuring and Troubleshooting Cisco Unified Border Element Lab outline Analyze SIP, H.323, and Media Protocols Troubleshoot SIP and Media Protocols Implement Cisco Unified Communications Manager Supplemental Services Implement Call Hunting and Call Queueing in Cisco Unified Communications Manager Configure Device Mobility Troubleshoot Cisco Unified Communications Manager Device Mobility Configure Cisco Unified Communications Manager Extension Mobility Troubleshoot Cisco Unified Communications Manager Extension Mobility Configure Cisco Unified Mobility Troubleshoot Cisco Unified Mobility Implement Endpoints in Cisco Unified Communications Manager Express Implement Endpoint Addressing and Call Routing in Cisco Unified Communications Manager Express Implement Calling Privileges in Cisco Unified Communications Manager Express Implement Hunt Groups, Call Park, and Paging in Cisco United Communications Manager Express Implement Globalized Call Routing Implement TEHO, PSTN Backup, and CoS in a Globalized Call-Routing Deployment Implement MGCP Fallback and Survivable Remote Site Telephony Implement Call Admission Control Implement a URI-Based Dial Plan for Multisite Deployments Troubleshoot Globalized Call Routing Troubleshoot Call Admission Control Implement Global Dial Plan Replication Implement Cisco Unified Border Element Troubleshoot Cisco Unified Border Element

What will you learn in this course? Understand newspaper articles, the news and lectures and participate in discussions on a wide range of professional and specialised topics. Communicate with native speakers in all situations - everyday and formal. Deal with simple and more complex situations related to education, health system etc. Understand a wide range of simple and demanding texts and easily identify any information presented. Express yourselves spontaneously. Use language effectively for social, academic, and professional purposes. The main topics to be covered in this course are about emotions, images, mind, learning, modern life, truth & lies, technology, environment, greek culture and much more...

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

Duration 4 Days 24 CPD hours This course is intended for This course is best suited to developers, engineers, and architects who want to use use Hadoop and related tools to solve real-world problems. Overview Skills learned in this course include:Creating a data set with Kite SDKDeveloping custom Flume components for data ingestionManaging a multi-stage workflow with OozieAnalyzing data with CrunchWriting user-defined functions for Hive and ImpalaWriting user-defined functions for Hive and ImpalaIndexing data with Cloudera Search Cloudera University?s four-day course for designing and building Big Data applications prepares you to analyze and solve real-world problems using Apache Hadoop and associated tools in the enterprise data hub (EDH). IntroductionApplication Architecture Scenario Explanation Understanding the Development Environment Identifying and Collecting Input Data Selecting Tools for Data Processing and Analysis Presenting Results to the Use Defining & Using Datasets Metadata Management What is Apache Avro? Avro Schemas Avro Schema Evolution Selecting a File Format Performance Considerations Using the Kite SDK Data Module What is the Kite SDK? Fundamental Data Module Concepts Creating New Data Sets Using the Kite SDK Loading, Accessing, and Deleting a Data Set Importing Relational Data with Apache Sqoop What is Apache Sqoop? Basic Imports Limiting Results Improving Sqoop?s Performance Sqoop 2 Capturing Data with Apache Flume What is Apache Flume? Basic Flume Architecture Flume Sources Flume Sinks Flume Configuration Logging Application Events to Hadoop Developing Custom Flume Components Flume Data Flow and Common Extension Points Custom Flume Sources Developing a Flume Pollable Source Developing a Flume Event-Driven Source Custom Flume Interceptors Developing a Header-Modifying Flume Interceptor Developing a Filtering Flume Interceptor Writing Avro Objects with a Custom Flume Interceptor Managing Workflows with Apache Oozie The Need for Workflow Management What is Apache Oozie? Defining an Oozie Workflow Validation, Packaging, and Deployment Running and Tracking Workflows Using the CLI Hue UI for Oozie Processing Data Pipelines with Apache Crunch What is Apache Crunch? Understanding the Crunch Pipeline Comparing Crunch to Java MapReduce Working with Crunch Projects Reading and Writing Data in Crunch Data Collection API Functions Utility Classes in the Crunch API Working with Tables in Apache Hive What is Apache Hive? Accessing Hive Basic Query Syntax Creating and Populating Hive Tables How Hive Reads Data Using the RegexSerDe in Hive Developing User-Defined Functions What are User-Defined Functions? Implementing a User-Defined Function Deploying Custom Libraries in Hive Registering a User-Defined Function in Hive Executing Interactive Queries with Impala What is Impala? Comparing Hive to Impala Running Queries in Impala Support for User-Defined Functions Data and Metadata Management Understanding Cloudera Search What is Cloudera Search? Search Architecture Supported Document Formats Indexing Data with Cloudera Search Collection and Schema Management Morphlines Indexing Data in Batch Mode Indexing Data in Near Real Time Presenting Results to Users Solr Query Syntax Building a Search UI with Hue Accessing Impala through JDBC Powering a Custom Web Application with Impala and Search