490 Courses

XML primer training course description This course has been designed for web and intranet developers who want to accelerate their learning of XML and its applications without the grind of book learning. Although a basic knowledge of HTML and JavaScript is assumed, it is also assumed you know very little about XML and how to use it. On completion of this course you should understand the benefits of using XML and be able to design XML solutions where applicable to your company's Internet/intranet requirements. The course will be particularly beneficial if you want to know how to communicate data to diverse applications over the Internet or company intranet. What will you learn Write XML. Debug XML. Examine existing code and determine its function. XML primer training course details Who will benefit: Anyone working with XML. Prerequisites: HTML5 development fundamentals Duration 3 days XML primer training course contents The origins of XML Markup languages, SGML, document type definitions and validity, introducing XML, IE and XML, accessing content and adding style. Basic XML XML document structure, elements and attributes, grammar, well formed documents, other XML elements and references. Document Type Definition (DTDs) Creating a DTD, basic declaration, declaring elements, content definitions, entities, entity declarations, notations, defining attributes, attribute types, forcing inclusion or exclusion of DTD sections, validation. Namespaces Declaring namespaces, scoping, removing and changing namespaces, qualified names, attribute namespaces. An introduction to schemas Constructing schemas, defining the root element and its contents,<ELEMENTTYPE>, defining root element contents, adding attributes definitions, <ATTRIBUTETYPE>, <ELEMENT>, <ATTRIBUTE>. XML & the Document Object Model (DOM) What the DOM offers, DOM and W3C. Basic DOM concepts XML documents as trees, terminology of tree elements. Key DOM Objects: The document object and its creation, base objects, IE specifics, the XML node hierarchy. Programming DOM Viewing a DOM model as XML, getting the root element of a document, iterating nodes of a DOM, basic node properties, collection objects, searching for specific values, filtering a nodelist by tagname, more filtering methods, selecting nodes from their attributes. Amending Content and Structure Creating/saving a DOM as XML, changing content/structure, dynamically building a DOM. Using ASP and other techniques ASP techniques, HTTPREQUEST object, XSL, transforming and formatting XML. Formatting Using CSS. CSS And XML. XSL Transformations - XSLT Introduction, the XSL root element, applying XSL stylesheets to XML, XSL elements and operations, instructions - creating text nodes and applying templates, a 'drill-down' approach, simple output formatting, pattern filters - patterns based on position, the Match and Select attributes and their patterns, formatting output, creating new XML in output.

Securing Kubernetes training course description This course introduces concepts, procedures, and best practices to harden Kubernetes based systems and container-based applications against security threats. It deals with the main areas of cloud-native security: Kubernetes cluster setup, Kubernetes cluster hardening, hardening the underlying operating system and networks, minimizing microservices vulnerabilities, obtaining supply chain security as well as monitoring, logging, and runtime security. What will you learn Harden Kubernetes systems and clusters. Harden containers. Configure and use Kubernetes audit logs. Securing Kubernetes training course details Who will benefit: Technical staff working with Kubernetes Prerequisites: Kubernetes_for_engineers_course.htm Definitive Docker for engineers Duration 2 days Securing Kubernetes training course contents This course does not only deal with the daily security administration of Kubernetes-based systems but also prepares delegates for the official Certified Kubernetes Security Specialist (CKS) exams of the Cloud Native Computing Foundation (CNCF). Structure: 50% theory 50% hands on lab exercise Module 1: User and authorization management Users and service accounts in Kubernetes Authenticating users Managing authorizations with RBAC Module 2: Supply chain security Vulnerabilit checking for images Image validation in Kubernetes Reducing image footprint Secure image registries Module 3: Validating cluster setup and penetration testing Use CIS benchmark to review the security configuration of Kubernetes components. Modify the cluster components' configuration to match the CIS Benchmark. Penetration testing Kubernetes for known vulnerabilities. Module 4: System hardening Use kernel hardening tools Setup appropriate OS level security domains Container runtime sandboxes Limit network access Module 5: Monitoring and logging Configure Kubernetes audit logs Configure Audit Policies Monitor applications behaviour with Falco

Time Management 1 Day Training in St Asaph

Time Management 1 Day Training in Middlesbrough

Time Management 1 Day Training in Northampton

Time Management 1 Day Training in Carlisle

Business Intelligence Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Networks demystified training course description A concise overview course covering all aspects of networking with particular emphasis of use of the 7 layer model as a framework for discussing and learning new network terms enabling delegates to recognise the main buzzwords used in the industry. What will you learn Use the 7 layer model to classify networking terms. Differentiate between LANS and WANS. Recognise bandwidth measurements. List LAN and WAN technologies. Recognise cabling issues in a network. Networks demystified training course details Who will benefit: Sales staff, managers and other non-technical personnel. Technical personnel may benefit more from our Intro to data communications and networking course. Prerequisites: None. Duration 1 day Networks demystified training course contents What are networks? What is a network? Types of network, Local Area Networks (LANs), Wide Area Networks (WANs), connecting networks together with routers. The 7 layer model What is the 7 layer model? The importance of standards, using the 7 layer model to classify networking terms. Cables Copper, Fibre, Air, standards, connectors, LAN cables, WAN cables, distance limitations, hubs and repeaters, other issues. The radio spectrum. Bandwidth Bits and bytes. Bandwidth measurements, common technologies and their bandwidth, the impact of applications on bandwidth. Full and half duplex. Joining cables together to increase bandwidth (Link aggregation). LANs and WANs What is Ethernet? What is WiFi? What are Leased lines? What is MPLS? Ethernet switches Ethernet 'packets', MAC addresses, what is a switch, what is the difference between a hub and a switch. TCP/IP What is TCP/IP? What is a protocol? What is IP? What is TCP? The role of routers in joining LANS and WANS, What is the Internet? Applications Ways to use the network, clients, servers, web browsing and HTTP, Email, instant messaging, multimedia applications.

Business Intelligence: In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Overview This course is designed to evaluate the financial statement, budget and making an effective decision. It will help to understand Discounted Cash Flow and its techniques, applications of financial statements and decision-making process.  In this programme, you will challenge representatives to learn how to make use of financial statements to assess the strategic or financial performance of an organization. It will help to understand DCF Discounted Cash Flow techniques along with their apps for financial making decisions and making use of ratios in order to identify the major areas of concern. Find out the elements like weaker financial signals, major success factors, and robust financial signals within your own industry. It Projects future performance assuredly through real-world budgeting.