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Lean Six Sigma Green Belt Certification Program: Virtual In-House Training This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps

Querying Microsoft SQL Server course description This course covers the technical skills required to write basic Transact-SQL queries for Microsoft SQL Server and provides the foundation for all SQL Server-related disciplines; namely, database administration, database development and business intelligence. This course helps prepare for exam 70-761. Note: This course is designed for SQL Server 2014or SQL Server 2016. What will you learn Write SELECT statements. Create and implement views and table-valued functions. Transform data by implementing pivot, unpivot, rollup and cube. Create and implement stored procedures. Add programming constructs such as variables, conditions, and loops to T-SQL code. Querying Microsoft SQL Server course details Who will benefit: Database administrators, database developers, and business intelligence professionals. SQL power users, namely, report writers, business analysts and client application developers. Prerequisites: Database fundamentals Duration 5 days Querying Microsoft SQL Server course contents Introduction to Microsoft SQL Server Management studio, creating and organizing T-SQL scripts, using books online. Hands on working with SQL Server tools. T-SQL querying Introducing T-SQL, sets, predicate logic, logical order of operations in SELECT statements, basic SELECT statements, queries that filter data using predicates, queries that sort data using ORDER BY. Hands on introduction to T-SQL querying. Writing SELECT queries Writing simple SELECT statements, eliminating duplicates with DISTINCT, column and table aliases, simple CASE expressions. Hands on writing basic SELECT statements. Querying multiple tables cross joins and self joins, write queries that use Inner joins, write queries that use multiple-table inner joins, write queries that use self-joins, write queries that use outer joins, write queries that use cross joins. Hands on querying multiple tables. Sorting and filtering data Sorting data, filtering data with predicates, filtering data with TOP and OFFSET-FETCH, working with unknown values, WHERE clause, ORDER BY clause, TOP option, OFFSET-FETCH clause. Hands on sorting and filtering data. SQL Server data types Introducing SQL Server data types, Character data, date and time data, queries that return date and time data, write queries that use date and time functions, write queries that return character data, write queries that return character functions. Hands on working with SQL Server data types. DML Adding data to tables, modifying and removing data, generating automatic column values, Inserting records with DML, updating and deleting records using DML. Hands on using DML to modify data. Built-in functions Queries with built-in functions, conversion functions, logical functions, functions with NULL, queries that use conversion functions, queries that use logical functions, queries that test for nullability. Hands on built-in functions Grouping and aggregating data Aggregate functions, the GROUP BY clause, filtering groups with HAVING, queries that use the GROUP BY clause, queries that use aggregate functions, queries that use distinct aggregate functions, queries that filter groups with the HAVING clause. Hands on grouping and aggregating data. Subqueries Self-contained subqueries, correlated subqueries, EXISTS predicate with subqueries, scalar and multi-result subqueries. Hands on subqueries. Table expressions Views, inline table-valued functions, derived tables, common table expressions. queries that use views, write queries that use derived tables, Common Table Expressions (CTEs), write queries that se inline Table valued expressions (TVFs). Hands on table expressions. Set operators The UNION operator, EXCEPT and INTERSECT, APPLY, queries that use UNION set operators and UNION ALL, CROSS APPLY and OUTER APPLY operators. Hands on set operators. Windows ranking, offset, and aggregate functions OVER, window functions, ranking functions, offset functions, window aggregate functions. Hands on; windows ranking, offset, and aggregate functions. Pivoting and grouping sets PIVOT and UNPIVOT, grouping sets, queries that use the PIVOT operator, queries that use the UNPIVOT operator, queries that use the GROUPING SETS CUBE and ROLLUP subclauses. Hands on pivoting and grouping sets Executing stored procedures Querying data with stored procedures, passing parameters to stored procedures, simple stored procedures, dynamic SQL, the EXECUTE statement to invoke stored procedures. Hands on executing stored procedures. Programming with T-SQL T-SQL programming elements, controlling program flow, declaring variables and delimiting batches, control-of-flow elements, variables in a dynamic SQL statement, synonyms. Hands on programming with T-SQL Error handling T-SQL error handling, structured exception handling, redirect errors with TRY/CATCH, THROW to pass an error message back to a client. Hands on implementing error handling. Implementing transactions Transactions and the database engines, controlling transactions, BEGIN, COMMIT, and ROLLBACK, adding error handling to a CATCH block. Hands on implementing transactions.

Historical Association webinar series: Practical approaches to disciplinary concepts in primary history Presenter: Emmy Quinn This session will show practical ways to introduce change and continuity to children, starting from the basics of change between a time in the past and today; to change and continuity within and across time periods. The session will give practical examples of how to frame a unit around change and continuity and how to demonstrate it within individual lessons. To use your corporate webinar offer for this webinar please complete this form: https://forms.office.com/e/95945xGxdh

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Introduction to data engineering on Azure What is data engineering Important data engineering concepts Data engineering in Microsoft Azure 2 - Introduction to Azure Data Lake Storage Gen2 Understand Azure Data Lake Storage Gen2 Enable Azure Data Lake Storage Gen2 in Azure Storage Compare Azure Data Lake Store to Azure Blob storage Understand the stages for processing big data Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - Introduction to Azure Synapse Analytics What is Azure Synapse Analytics How Azure Synapse Analytics works When to use Azure Synapse Analytics 4 - Use Azure Synapse serverless SQL pool to query files in a data lake Understand Azure Synapse serverless SQL pool capabilities and use cases Query files using a serverless SQL pool Create external database objects 5 - Use Azure Synapse serverless SQL pools to transform data in a data lake Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement Encapsulate data transformations in a stored procedure Include a data transformation stored procedure in a pipeline 6 - Create a lake database in Azure Synapse Analytics Understand lake database concepts Explore database templates Create a lake database Use a lake database 7 - Analyze data with Apache Spark in Azure Synapse Analytics Get to know Apache Spark Use Spark in Azure Synapse Analytics Analyze data with Spark Visualize data with Spark 8 - Transform data with Spark in Azure Synapse Analytics Modify and save dataframes Partition data files Transform data with SQL 9 - Use Delta Lake in Azure Synapse Analytics Understand Delta Lake Create Delta Lake tables Create catalog tables Use Delta Lake with streaming data Use Delta Lake in a SQL pool 10 - Analyze data in a relational data warehouse Design a data warehouse schema Create data warehouse tables Load data warehouse tables Query a data warehouse 11 - Load data into a relational data warehouse Load staging tables Load dimension tables Load time dimension tables Load slowly changing dimensions Load fact tables Perform post load optimization 12 - Build a data pipeline in Azure Synapse Analytics Understand pipelines in Azure Synapse Analytics Create a pipeline in Azure Synapse Studio Define data flows Run a pipeline 13 - Use Spark Notebooks in an Azure Synapse Pipeline Understand Synapse Notebooks and Pipelines Use a Synapse notebook activity in a pipeline Use parameters in a notebook 14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics Understand hybrid transactional and analytical processing patterns Describe Azure Synapse Link 15 - Implement Azure Synapse Link with Azure Cosmos DB Enable Cosmos DB account to use Azure Synapse Link Create an analytical store enabled container Create a linked service for Cosmos DB Query Cosmos DB data with Spark Query Cosmos DB with Synapse SQL 16 - Implement Azure Synapse Link for SQL What is Azure Synapse Link for SQL? Configure Azure Synapse Link for Azure SQL Database Configure Azure Synapse Link for SQL Server 2022 17 - Get started with Azure Stream Analytics Understand data streams Understand event processing Understand window functions 18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics Stream ingestion scenarios Configure inputs and outputs Define a query to select, filter, and aggregate data Run a job to ingest data 19 - Visualize real-time data with Azure Stream Analytics and Power BI Use a Power BI output in Azure Stream Analytics Create a query for real-time visualization Create real-time data visualizations in Power BI 20 - Introduction to Microsoft Purview What is Microsoft Purview? How Microsoft Purview works When to use Microsoft Purview 21 - Integrate Microsoft Purview and Azure Synapse Analytics Catalog Azure Synapse Analytics data assets in Microsoft Purview Connect Microsoft Purview to an Azure Synapse Analytics workspace Search a Purview catalog in Synapse Studio Track data lineage in pipelines 22 - Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts 23 - Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data 24 - Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook Additional course details: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure 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 DP-203T00 Data Engineering on Microsoft Azure 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.

Historical Association webinar series: Making GCSE history accessible: supporting all learners at Key Stage 4 Presenters: Dale Banham   "This session explores how to help SEND learners retain historical knowledge by applying research-informed strategies that reduce cognitive overload and support long-term memory formation within the context of history teaching. Key topics: • Applying cognitive load theory to history-specific content and tasks • Using dual coding, retrieval practice, and spaced learning frameworks to support retention • Embedding effective homework, revision routines and explicit instruction to strengthen pupils’ historical schema " To use your corporate recording offer on this webinar please fill in this form: https://forms.office.com/e/bdNUSwLNrL Image: A Squire "Old English" padlock on a gate latch in Devon (Image: Partonez/Wikimedia Commons)

About this Training Course More energy companies today are setting ambitious net-zero targets and are expected to pour billions into the voluntary carbon offset market by the end of this decade. To get to net zero emissions, companies will need to balance emissions with nature and technology-based offsets. Markets are the best tool for connecting carbon sources and sinks. Many countries will not have enough supply inside their borders and will need to co-operate with those who have extra greenhouse gas removal potential. The energy industry is in search of effective climate tools as pressure mounts from investors and consumers for more progress on fighting rising emissions. Corporations fighting to cut their carbon footprint have for years focused on internal reduction measures. Many are now adding to that effort by turning to carbon credits, a process made easier as verification and registration tools mature. One particular category of carbon offsets leads the way: high-quality, nature-based carbon credits. These represent the largest category of carbon credit projects in the voluntary carbon market, comprising nearly half of credits issued. Public concern about this practice focused on the additionality, leakage, and integrity of carbon offsets that are created through reforestation, land preservation, carbon capture and other projects. Lack of standardization and government regulation has also increased uncertainty for all participants in carbon markets, creating risks for developers of credit-generating projects and offset purchasers. Demand for higher-quality offsets will value projects that were subjected to due diligence and rely upon reputable third-party verification. Companies purchasing offsets generated by permanent and quantifiable projects will therefore be in the best position moving forward. In this highly interactive training course, your course instructor will guide you through the latest developments and best procurement practices to successfully operate in the voluntary carbon market. Training Objectives At the end of this course, the participants will be able to: Discover the current state of the carbon economy Gain insights into the voluntary carbon market Learn about the different type carbon credits available Examine how companies can reach net zero target by using carbon offsets Uncover best practices in carbon credit procurement strategy Learn the pricing dynamics carbon credits Examine how to identify and ensure high quality credits Obtain key learning from flawed carbon offset projects Target Audience This course is intended for: Energy transition team leaders Carbon credit procurement professionals ESG strategy team leaders Finance and accounting professionals Low carbon business analysts or economists Corporate business sustainability professionals Legal, compliance and regulatory professionals Carbon trading professionals Course Level Intermediate Trainer Your expert course leader is a skilled and accomplished professional with over 25 years of extensive C-level experience in the energy markets worldwide. He has a strong expertise in all the aspects of (energy) commodity markets, international sales, marketing of services, derivatives trading, staff training and risk management within dynamic and high-pressure environments. He received a Master's degree in Law from the University of Utrecht in 1987. He started his career at the NLKKAS, the Clearing House of the Commodity Futures Exchange in Amsterdam. After working for the NLKKAS for five years, he was appointed as Member of the Management Board of the Agricultural Futures Exchange (ATA) in Amsterdam at the age of 31. While working for the Clearing House and exchange, he became an expert in all the aspects of trading and risk management of commodities. In 1997, he founded his own specialist-consulting firm that provides strategic advice about (energy) commodity markets, trading and risk management. He has advised government agencies such as the European Commission, investment banks, major utilities and commodity trading companies and various energy exchanges and market places in Europe, CEE countries, North America and Asia. Some of the issues he has advised on are the development and implementation of a Risk Management Framework, investment strategies, trading and hedging strategies, initiation of Power Exchanges (APX) and other trading platforms, the set-up of (OTC) Clearing facilities, and feasibility and market studies like for the Oil, LNG and the Carbon Market. The latest additions are (Corporate) PPAs and Artificial Intelligence for energy firms. He has given numerous seminars, workshops and (in-house) training sessions about both the physical and financial trading and risk management of commodity and carbon products. The courses have been given to companies all over the world, in countries like Japan, Singapore, Thailand, United Kingdom, Germany, Poland, Slovenia, Czech Republic, Malaysia, China, India, Belgium and the Netherlands. He has published several articles in specialist magazines such as Commodities Now and Energy Risk and he is the co-author of a book called A Guide to Emissions Trading: Risk Management and Business Implications published by Risk Books in 2004. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

Duration 4 Days 24 CPD hours This course is intended for This four-day course is intended for Windows Server Hybrid Administrators who have experience working with Windows Server and want to extend the capabilities of their on-premises environments by combining on-premises and hybrid technologies. Windows Server Hybrid Administrators who already implement and manage on-premises core technologies want to secure and protect their environments, migrate virtual and physical workloads to Azure Iaas, enable a highly available, fully redundant environment, and perform monitoring and troubleshooting. This course teaches IT Professionals to configure advanced Windows Server services using on-premises, hybrid, and cloud technologies. The course teaches IT Professionals how to leverage the hybrid capabilities of Azure, how to migrate virtual and physical server workloads to Azure IaaS, and how to secure Azure VMs running Windows Server. The course also teaches IT Professionals how to perform tasks related to high availability, troubleshooting, and disaster recovery. The course highlights administrative tools and technologies including Windows Admin Center, PowerShell, Azure Arc, Azure Automation Update Management, Microsoft Defender for Identity, Azure Security Center, Azure Migrate, and Azure Monitor. Prerequisites An understanding of the following concepts as related to Windows Server technologies: High availability and disaster recovery Automation Monitoring Troubleshooting 1 - Secure Windows Server user accounts Configure user account rights Protect user accounts with the Protected Users group Describe Windows Defender Credential Guard Block NTLM authentication Locate problematic accounts 2 - Hardening Windows Server Describe Local Password Administrator Solution Configure Privileged Access Workstations Secure domain controllers Analyze security configuration with Security Compliance Toolkit Secure SMB traffic 3 - Windows Server update management Explore Windows Update Outline Windows Server Update Services server deployment options Define Windows Server Update Services update management process Describe the process of Update Management 4 - Secure Windows Server DNS Implement split-horizon DNS Create DNS policies Implement DNS policies Secure Windows Server DNS Implement DNSSEC 5 - Implement Windows Server IaaS VM network security Implement network security groups and Windows IaaS VMs Implement adaptive network hardening Implement Azure Firewall and Windows IaaS VMs Implement Windows firewall with Windows Server IaaS VMs Choose the appropriate filtering solution Deploy and configure Azure firewall using the Azure portal Capture network traffic with network watcher Log network traffic to and from a VM using the Azure portal 6 - Audit the security of Windows Server IaaS Virtual Machines Describe Azure Security Center Enable Azure Security Center in hybrid environments Implement and assess security policies Protect your resources with Azure Security Center Implement Azure Sentinel 7 - Manage Azure updates Describe update management Enable update management Deploy updates View update assessments Manage updates for your Azure Virtual Machines 8 - Create and implement application allowlists with adaptive application control Describe adaptive application control Implement adaptive application control policies 9 - Configure BitLocker disk encryption for Windows IaaS Virtual Machines Describe Azure Disk Encryption and server-side encryption Configure Key Vault for Azure Disk Encryption Encrypt Azure IaaS Virtual Machine hard disks Back up and recover data from encrypted disks Create and encrypt a Windows Virtual Machine 10 - Implement change tracking and file integrity monitoring for Windows IaaS VMs Implement Change Tracking and Inventory Manage Change Tracking and Inventory Manage tracked files Implement File Integrity Monitoring Select and monitor entities Use File Integrity Monitoring 11 - Introduction to Cluster Shared Volumes Determine the functionality of Cluster Shared Volumes Explore the architecture and components of Cluster Shared Volumes Implement Cluster Shared Volumes 12 - Implement Windows Server failover clustering Define Windows Server failover clustering Plan Windows Server failover clustering Implement Windows Server failover clustering Manage Windows Server failover clustering Implement stretch clusters Define cluster sets 13 - Implement high availability of Windows Server VMs Select high-availability options for Hyper-V Consider network load balancing for Hyper-V VMs Implement Hyper-V VM live migration Implement Hyper-V VMs storage migration 14 - Implement Windows Server File Server high availability Explore the Windows Server File Server high-availability options Define Cluster Shared Volumes Implement Scale-Out File Server Implement Storage Replica 15 - Implement scale and high availability with Windows Server VM Describe virtual machine scale sets Implement scaling Implement load-balancing VMs Create a virtual machine scale set in the Azure portal Describe Azure Site Recovery Implement Azure Site Recovery 16 - Implement Hyper-V Replica Define Hyper-V Replica Plan for Hyper-V Replica Configure and implement Hyper-V Replica Define extended replication Define Azure Site Recovery Implement Site Recovery from on-premises site to Azure Implement Site Recovery from on-premises site to on-premises site 17 - Protect your on-premises infrastructure from disasters with Azure Site Recovery Azure Site Recovery overview Workloads supported for protection with Azure Site Recovery Run a disaster recovery drill Failover and failback 18 - Implement hybrid backup and recovery with Windows Server IaaS Describe Azure Backup Implement recovery vaults Implement Azure Backup policies Recover Windows IaaS Virtual Machines Perform file and folder recovery Perform backup and restore of on-premises workloads Manage Azure Virtual Machine backups with Azure Backup service 19 - Protect your Azure infrastructure with Azure Site Recovery What is Azure Site Recovery Prepare for disaster recovery with Azure Site Recovery Run a disaster recovery drill Failover and failback using Azure Site Recovery 20 - Protect your virtual machines by using Azure Backup Azure Backup features and scenarios Back up an Azure virtual machine by using Azure Backup Restore virtual machine data 21 - Active Directory Domain Services migration Examine upgrade vs. migration Upgrade a previous version of Active Directory Domain Services to Windows Server 2022 Migrate to Active Directory Domain Services in Windows Server 2022 from a previous version Explore the Active Directory Migration Tool 22 - Migrate file server workloads using Storage Migration Service Storage Migration Service overview and usage scenarios Storage migration requirements Migrate a server with Storage migration Evaluate storage migration considerations 23 - Migrate Windows Server roles Describe the Windows Server Migration Tools Install the Migration Tools Migrate roles using the Migration Tools 24 - Migrate on-premises Windows Server instances to Azure IaaS virtual machines Plan your migration Describe Azure Migrate Perform server assessment Assess physical servers with Azure Migrate Migrate Windows Server workloads by using Azure Migrate 25 - Upgrade and migrate Windows Server IaaS virtual machines Describe Azure Migrate Migrate Windows Server workloads by using Azure Migrate Describe storage migration Migrate file servers by using Storage Migration Service 26 - Containerize and migrate ASP.NET applications to Azure App Service Azure Migrate App Containerization overview 27 - Monitor Windows Server performance Use Performance Monitor to identify performance problems Use Resource Monitor to review current resource usage Review reliability with Reliability Monitor Implement a performance monitoring methodology Use Data Collector Sets to analyze server performance Monitor network infrastructure services Monitor virtual machines running Windows Server Monitor performance with Windows Admin Center Use System Insights to help predict future capacity issues Optimize the performance of Windows Server 28 - Manage and monitor Windows Server event logs Describe Windows Server event logs Use Windows Admin Center to review logs Use Server Manager to review logs Use custom views Implement event log subscriptions 29 - Implement Windows Server auditing and diagnostics Describe basic auditing categories Describe advanced categories Log user access Enable setup and boot event collection 30 - Troubleshoot Active Directory Recover objects from the AD recycle bin Recover the AD DS database Recover SYSVOL Troubleshoot AD DS replication Troubleshoot hybrid authentication issues 31 - Monitor Windows Server IaaS Virtual Machines and hybrid instances Enable Azure Monitor for Virtual Machines Monitor an Azure Virtual Machine with Azure Monitor Enable Azure Monitor in hybrid scenarios Collect data from a Windows computer in a hybrid environment Integrate Azure Monitor with Microsoft Operations Manager 32 - Monitor your Azure virtual machines with Azure Monitor Monitoring for Azure VMs Monitor VM host data Use Metrics Explorer to view detailed host metrics Collect client performance counters by using VM insights Collect VM client event logs 33 - Troubleshoot on-premises and hybrid networking Diagnose DHCP proble

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  European Data Protection   Principles of Data Protection in Europe covers the essential pan-European and national data protection laws, as well as industry-standard best practices for corporate compliance with these laws. Those taking this course will gain an understanding of the European model for privacy enforcement, key privacy terminology and practical concepts concerning the protection of personal data and trans-border data flows.   The training is based on the body of knowledge for the IAPP's ANSI-accredited Certified Information Privacy Professional/Europe (CIPP/E) certification program. Privacy Programme Management   Principles of Privacy Management is the how-to training on implementing a privacy program framework, managing the privacy program operational lifecycle and structuring a knowledgeable, high-performing privacy team. Those taking this course will learn the skills to manage privacy in an organisation through process and technology-regardless of jurisdiction or industry.   The Principles of Privacy Program Management training is based on the body of knowledge for the IAPP's ANSI-accredited Certified Information Privacy Manager (CIPM) certification programme. Make a difference in your organization and in your career. The CIPM designation says that you're a leader in privacy program administration and that you've got the goods to establish, maintain and manage a privacy program across all stages of its lifecycle.  About This Course   Delivered in a modular format, this four day course covers   Days 1 & 2   Module 1: Data Protection Laws Introduces key European data protection laws and regulatory bodies, describing the evolution toward a Harmonised European Legislative Framework.  Module 2: Personal Data Defines and differentiates between types of data-including personal, anonymous, pseudo-anonymous and special categories.  Module 3: Controllers and Processors Describes the roles and relationships of controllers and processors.  Module 4: Processing Personal Data Defines data processing and GDPR processing principles, Explains the application of the GDPR and outlines the legitimate bases for processing personal data. Module 5: Information provision Explains controller obligations for providing information about data processing activities to data subjects and Supervisory Authorities.  Module 6: Data Subjects 'Rights Describes data subjects' rights, applications of rights and obligations controller and processor.  Module 7: Security or Processing Discusses considerations and duties of controllers and processors for Ensuring security of personal data and providing notification of data breaches.  Module 8: Accountability Investigates accountability requirements, data protection management systems, data protection impact assessments, privacy policies and the role of the data protection officer.  Module 9: International Data Transfers Outlines options and obligations for transferring data outside the European Economic Area, Decisions adequacy and appropriateness safeguards and derogations.  Module 10: Supervision and Enforcement Describes the role, powers and procedures or Supervisory Authorities; the composition and tasks of the European Data Protection Board; the role of the European Data Protection Supervisor; and remedies, liabilities and penalties for non-compliance.  Module 11: Compliance Discusses the applications of European data protection law, legal bases and compliance requirements for processing personal data in practice, employers-including processing employee data, surveillance, direct marketing, Internet technology and communications and outsourcing.    Days 3 & 4   Module 1: Introduction to privacy program management Identifies privacy program management responsibilities, and describes the role of accountability in privacy program management.  Module 2: Privacy governance Examines considerations for developing and implementing a privacy program, including the position of the privacy function within the organization, role of the DPO, program scope and charter, privacy strategy, support and ongoing involvement of key functions and privacy frameworks.  Module 3: Applicable laws and regulations Discusses the regulatory environment, common elements across jurisdictions and strategies for aligning compliance with organizational strategy.  Module 4: Data assessments Relates practical processes for creating and using data inventories/maps, gap analyses, privacy assessments, privacy impact assessments/data protection impact assessments and vendor assessments.  Module 5: Policies Describes common types of privacy-related policies, outlines components and offers strategies for implementation.  Module 6: Data subject rights Discusses operational considerations for communicating and ensuring data subject rights, including privacy notice, choice and consent, access and rectification, data portability, and erasure and the right to be forgotten.  Module 7: Training and awareness Outlines strategies for developing and implementing privacy training and awareness programs.  Module 8: Protecting personal information Examines a holistic approach to protecting personal information through privacy by design.  Module 9: Data breach incident plans Provides guidance on planning for and responding to a data security incident or breach.  Module 10: Measuring, monitoring and auditing program performance Relates common practices for monitoring, measuring, analyzing and auditing privacy program performance Prerequisites   There are no prerequisites for this course but attendees would benefit from a review of the materials on the IAPP SITE What's Included?   1 years membership of the IAPP Breakfast, Lunch, mid-morning and afternoon snacks, teas, coffees Official Study Guides* Official Participant Guides* Official Exam Q&A's* Both exam fees * In electronic format for Live Online and hard copy for Classroom delegates     Who Should Attend?   This course is suitable for aspiring Data Protection Officers, as well as Information Security Managers, Lawyers, Data Managers, Analysts and Risk Teams. Provided by Our Guarantee   We are an approved IAPP Training Partner. You can learn wherever and whenever you want with our robust classroom and interactive online training courses. Our courses are taught by qualified practitioners with a minimum of 25 years commercial experience. We strive to give our delegates the hands-on experience. Our courses are all-inclusive with no hidden extras.  The one-off cost covers the training, all course materials, and exam voucher. Our aim: To achieve a 100% first time pass rate on all our instructor-led courses. Our Promise: Pass first time or 'train' again for FREE. *FREE training offered for retakes - come back within a year and only pay for the exam.

OpenView training course description A hands-on course focusing on network management using HP OpenView network node manager on Microsoft Windows or UNIX. What will you learn Recognise the benefits of ADSL. Describe the network management architecture. Use HP OpenView. Diagnose faults using HP OpenView. Recognise the MIB structure. OpenView training course details Who will benefit: Technical staff wanting to learn DNS. Prerequisites: TCP/IP Foundation Duration 2 days OpenView training course contents Network management What is network management?, Benefits, issues, demonstration. Getting started with HP OpenView Starting HP OpenView, IP discovery, IP monitoring, controlling IP discovery. Using HP OpenView Mapping devices, map layouts, maps and submaps, objects and symbols, object attributes, colour codings, polling. Agents Configuring Cisco devices for SNMP support, communities, traps, syslog. Parts of SNMP SNMP architecture, MIB's, The protocol. HP OpenView SNMP configuration HP OpenView alarm browser HP OpenView alarms, alarm categories, filtering alarms, alarm details window. MIB's MIB1, MIB2, The MIB2 groups, additional MIB's, MIB compilers, vendor MIB's. HP OpenView MIB loader and browser. Monitoring devices Polling, obtaining MIB information. Diagnostic tools Poll node, the ping window, protocol test, locate route HP OpenView fault management Alarms, polling, fault management, setting thresholds and configuring traps.