452 Developer courses in Cardiff delivered Live Online

Duration 1 Days 6 CPD hours This course is intended for The course is designed for anyone desiring or requiring an understanding of how to manage cloud technologies as a business asset. This includes: IT Asset Managers Hardware Asset Managers Software Asset Managers Cloud Asset Managers Cloud Project Managers IT Managers IT Cloud Managers and Developers Cloud Vendor Managers IT Procurement IT Security Professionals Overview The student will learn the nuances of cloud assets and manage them from a financial, risk, compliance, and efficiency perspective. Upon completion of the course, the student will be able to: Understand the attributes of and requirements for managing cloud assets Define and develop cloud asset management processes Create cloud asset policies Develop and implement a communication plan for managing cloud assets Identify tool requirements to support the cloud asset type Develop cloud vendor contract requirements Understand and articulate individual and department responsibilities for the cloud asset management program Define requirements for managing cloud vendors Assess the organization's cloud asset management readiness This course takes an in-depth look at cloud assets. It defines how to manage these assets using best practical practices for the primary cloud architectures Software-as-a-Service, Platform-as-a-Service, and Infrastructure as-a-Service. What is Information Technology Asset Management? Why Cloud Solutions Need ITAM Introducing Cloud Services Vendor's Tools Cloud Vendor Management Communication Managing SaaS Acquire Phase Receive Phase Deploy Phase In-Use Phase Recover Phase Dispose Phase Example Vendor Reports Terms and Conditions Vendor Scorecard Managing IaaS and PaaS ITAM Data Center Challenges, Before Virtualization ITAM Data Center Challenges, with Virtualization The Data Center Transformation The End-User ITAM Supporting Processes Acquire Phase Receive Phase Deploy Phase In-Use Phase Recover Phase Dispose Phase Software Asset Management Example Vendor Reports Terms and Conditions Vendor Scorecard Disaster Recovery PlanDisposal of Replaced IT AssetsCAM and the ITAM Hierarchy Additional course details: Nexus Humans The Definitive Guide to Cloud Asset Management 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 The Definitive Guide to Cloud Asset Management 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 course is for analysts, developers, and administrators of IBM Watson Explorer Deep Analytics Edition oneWEX. Overview Identify oneWEX platformsIdentify the process and data flows of oneWEX projectsExplore the oneWEX user interfaceExplain ingestion and conversionUtilize Content MinerDefine enrichmentIdentify advanced features of oneWEX This course is designed to teach students core concepts of IBM Watson Explorer Deep Analytics Edition oneWEX. Students will learn to identify the oneWEX platforms as well as the process flow and data flow of oneWEX projects. Students will explore oneWEX tools, such as Content Miner and the Admin Console, while gaining hands-on experience in data acquisition and enrichment. Finally, students will be exposed to more advanced topics, such as Application Builder, Content Analytics Studio, and API usage. Overview of oneWEX Introduction to oneWEX Explore oneWEX architecture Identify installation options Navigation in oneWEX Explore the Admin Console Explore navigation using Content Miner The Collection detail view The REST API Data flow Explore the data flow of oneWEX Search and Analytics collection templates Identify data acquisition Data ingestion Work with datasets Work with crawlers Use an importer Explore conversion Data ingestion log files Analysis using oneWEX Content Miner Explore analysis using Content Miner The Guided Analysis Experience The Guided Analysis view Explore Annotators Enrichment using Annotators Annotator types Enrichment using Labeler Identify enrichment Identify document classification Classify using training data Classification versus clustering The document classification process Enrichment using Ranker Identify enrichment using Ranker The ranking process Migrate annotators from Content Analytics Studio Migrate Content Analytics Studio annotators Identify the UIMA pipeline configuration for oneWEX Update annotators Using Application Builder with oneWEX Application Builder and user roles Explore Application Builder Set up a oneWEX data source Functionality for oneWEX data sources Additional course details: Nexus Humans O3201 Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX (V12.0.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 O3201 Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX (V12.0.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 2 Days 12 CPD hours This course is intended for This course is designed for developers who want to learn about Git and GitHub. Overview Upon completion of this course, participants will be able to: ? Install and run Git ? Describe basic concepts of Git version control ? Work on multiple branches ? Optimize merging and fixing merge conflicts ? Create and manage GitHub repositories ? Collaborate using GitHub This hands-on course teaches participants how to integrate Git and GitHub into their daily command-line workflow. Git operations, customizations of Git functionality, and how to connect to Git via Eclipse are covered as well. Introduction Introduction to Version Control Systems The Birth of Git and Why Git? What is GitHub? GitHub Repository Concepts Getting Started With Git Installing and Running Git The Git command Line Configuration Files Creating your First Git Repository Staging Area Git Commit Viewing History Creating Aliases and Shortcuts Hands-on Lab Session Getting Started with GitHub Creating and Configuring a Repository in GitHub Uploading your Repository to GitHub Understand Repository?s Main Page Using the README Hands-on Lab Session File Management in Git Locally The Index File Classifications in Git Rename a File Delete a File Ignore Files using .gitignore File Hands-on Lab Session Collaboration on Pull Requests Cloning and Forking Repositories Creating a Pull Request Collaborating a Pull Request Merging on a Pull Request Working with Branches Hands-on Lab Session Integrating GitHub with Eclipse Introducing EGit Plugin Configuring GitHub in Eclipse Working with Eclipse Hands-on Lab Session Reviewing and Configuring a Project on GitHub Configuring a Repository Adding Collaborators Creating Organizations Managing Teams Introducing Issues Merging, Rebasing and Resolving Conflicts Merging Branches Git diff and Commit Ranges Working with Merge Conflicts Merge Strategies Introduction to Rebasing Rebasing Branches Reverting and Fixing Bad Commits Hands-on Lab Session Additional course details: Nexus Humans Learning Git and GitHub 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 Learning Git and GitHub 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 Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek an understanding of the parallel framework architecture. In this course, students will develop a deeper understanding of the DataStage architecture, including a deeper understanding of the DataStage development and runtime environments. Introduction to the Parallel Framework Architecture Describe the parallel processing architecture Describe pipeline and partition parallelism Describe the role of the configuration file Design a job that creates robust test data Compiling & Executing Jobs Describe the main parts of the configuration file Describe the compile process and the OSH that the compilation process generates Describe the role and the main parts of the Score Describe the job execution process Partitioning & Collecting Data Understand how partitioning works in the Framework Viewing partitioners in the Score Selecting partitioning algorithms Generate sequences of numbers (surrogate keys) in a partitioned, parallel environment Sorting Data Sort data in the parallel framework Find inserted sorts in the Score Reduce the number of inserted sorts Optimize Fork-Join jobs Use Sort stages to determine the last row in a group Describe sort key and partitioner key logic in the parallel framework Buffering in Parallel Jobs Describe how buffering works in parallel jobs Tune buffers in parallel jobs Avoid buffer contentions Parallel Framework Data Types Describe virtual data sets Describe schemas Describe data type mappings and conversions Describe how external data is processed Handle nulls Work with complex data Reusable Components Create a schema file Read a sequential file using a schema Describe Runtime Column Propagation (RCP) Enable and disable RCP Create and use shared containers Balanced Optimization Enable Balanced Optimization functionality in Designer Describe the Balanced Optimization workflow List the different Balanced Optimization options. Push stage processing to a data source Push stage processing to a data target Optimize a job accessing Hadoop HDFS file system Understand the limitations of Balanced Optimizations Additional course details: Nexus Humans KM404 IBM InfoSphere Advanced DataStage - Parallel Framework (v11.5) 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 KM404 IBM InfoSphere Advanced DataStage - Parallel Framework (v11.5) 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 4 Days 24 CPD hours This course is intended for This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Overview Skills gained in this training include:The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysisThe fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with HadoopHow Pig, Hive, and Impala improve productivity for typical analysis tasksJoining diverse datasets to gain valuable business insightPerforming real-time, complex queries on datasets Cloudera University?s four-day data analyst training course focusing on Apache Pig and Hive and Cloudera Impala will teach you to apply traditional data analytics and business intelligence skills to big data. Hadoop Fundamentals The Motivation for Hadoop Hadoop Overview Data Storage: HDFS Distributed Data Processing: YARN, MapReduce, and Spark Data Processing and Analysis: Pig, Hive, and Impala Data Integration: Sqoop Other Hadoop Data Tools Exercise Scenarios Explanation Introduction to Pig What Is Pig? Pig?s Features Pig Use Cases Interacting with Pig Basic Data Analysis with Pig Pig Latin Syntax Loading Data Simple Data Types Field Definitions Data Output Viewing the Schema Filtering and Sorting Data Commonly-Used Functions Processing Complex Data with Pig Storage Formats Complex/Nested Data Types Grouping Built-In Functions for Complex Data Iterating Grouped Data Multi-Dataset Operations with Pig Techniques for Combining Data Sets Joining Data Sets in Pig Set Operations Splitting Data Sets Pig Troubleshoot & Optimization Troubleshooting Pig Logging Using Hadoop?s Web UI Data Sampling and Debugging Performance Overview Understanding the Execution Plan Tips for Improving the Performance of Your Pig Jobs Introduction to Hive & Impala What Is Hive? What Is Impala? Schema and Data Storage Comparing Hive to Traditional Databases Hive Use Cases Querying with Hive & Impala Databases and Tables Basic Hive and Impala Query Language Syntax Data Types Differences Between Hive and Impala Query Syntax Using Hue to Execute Queries Using the Impala Shell Data Management Data Storage Creating Databases and Tables Loading Data Altering Databases and Tables Simplifying Queries with Views Storing Query Results Data Storage & Performance Partitioning Tables Choosing a File Format Managing Metadata Controlling Access to Data Relational Data Analysis with Hive & Impala Joining Datasets Common Built-In Functions Aggregation and Windowing Working with Impala How Impala Executes Queries Extending Impala with User-Defined Functions Improving Impala Performance Analyzing Text and Complex Data with Hive Complex Values in Hive Using Regular Expressions in Hive Sentiment Analysis and N-Grams Conclusion Hive Optimization Understanding Query Performance Controlling Job Execution Plan Bucketing Indexing Data Extending Hive SerDes Data Transformation with Custom Scripts User-Defined Functions Parameterized Queries Choosing the Best Tool for the Job Comparing MapReduce, Pig, Hive, Impala, and Relational Databases Which to Choose?

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 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

Duration 3 Days 18 CPD hours This course is intended for Developers, Functional Testers, Test Automation Specialists, Performance Specialists, Environment and Data Specialists, Security Specialists Prerequisites for taking part in the workshop: It is recommended that participants should have completed the ISTQB© Certified Tester Foundation Level certification, or have attended the workshop. Overview Defined tasks need to be structured according to the technical requirements and the internal structure of the system needs to be analysed in detail in order to achieve the expected level of quality and detect errors during development. The ISTQB© Advanced Level Technical Test Analyst certification will teach you on the basis of the current ISTQB© Advanced Level syllabus. The various procedures, techniques and tools for non-functional system testing will be explained, and you will then be in a position to apply these in your future work as a Technical Test Analyst. The three-day certification will be followed by a two-hour examination. During the workshop, our experienced trainers will fully prepare you for the ISTQB© Advanced Level Technical Test Analyst examination. Following on from the ISTQB© Certified Tester Foundation Level training, this workshop covers the increasing technical challenges faced by system testing in particular. Topic 1 Tasks of a Technical Test Analyst in risk-based testing Topic 2 Structure-based testing: Simple condition test, condition/decision test, modified condition/decision test, multiple condition test, path test, API test, selection of structure-based procedures Topic 3 Analytical testing methods: static analysis (control flow analysis, data flow analysis, improved maintainability/adaptability with static analysis, call graphs), dynamic analysis (detection of memory leaks/?rogue? pointers, analysis of system performance) Topic 4 Quality features in technical tests (ISO 25000 standard): Planning aspects of technical testing, security testing, reliability testing, performance testing, resource usage, maintainability testing, portability testing Topic 5 Review checklists (architecture and code reviews) Topic 6 Testing tools and automation, tool integration, test automation projects, specific testing tools Topic 7 Practical exercises on all core topics Notes In order to take the examination, you must show at least 18 months? practical experience as a tester and be certified at ISTQB© Foundation Level. Confirmation from your employer or from your reference customers are accepted as proof of practical experience. Additional course details: Nexus Humans ISTQB Certified Tester, Advanced Level - Technical Test Analyst 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 ISTQB Certified Tester, Advanced Level - Technical Test Analyst 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.