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  ISO 13485 Foundation training enables you to learn the basic elements to implement and manage a Medical Devices Quality Management System (MDQMS) as specified in ISO 13485. During this training course, you will be able to understand the different modules of a MDQMS, including MDQMS policy, procedures, performance measurements, management commitment, internal audit, management review and continual improvement. After completing this course, you can sit for the exam and gain "Certified ISO 13485 Foundation' Certification. This Certificate shows that you have understood the fundamental methodologies, requirements, framework and management approach.  About This Course   Learning Objectives Understand the elements and operations of a Medical Devices Quality Management System (MDQMS) Acknowledge the correlation between ISO 13485 and other standards and regulatory frameworks Understand the approaches, methods and techniques used for the implementation and management of a MDQMS   Course Agenda Day 1: Introduction to Medical Devices Quality Management System (MDQMS) concepts as required by ISO 13485 Day 2: Medical Devices Quality Management System requirements and Certification Exam   Assessment     Delegates sit a combined exam, consisting of in-course quizzes and exercises, as well as a final 40 question, multiple choice exam on Day 2 of the course. The overall passing score is 70%, to be achieved within the 60 minute time allowance. Exam results are provided within 24 hours, with both a Certificate and a digital badge provided as proof of success.   Prerequisites   None What's Included?   Certification fees are included on the exam price Training material containing over 200 pages of information and practical examples will be distributed An attestation of course completion worth 14 CPD (Continuing Professional Development) credits will be issued to the participants who have attended the training course. Who Should Attend?   Individuals involved in Medical Devices Quality Management Individuals seeking to gain knowledge about the main processes of Medical Devices Quality Management Systems (MDQMS) Individuals interested to pursue a career in Medical Devices Quality Management Accreditation Provided by   This course is Accredited by NACS and Administered by the IECB

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

Discover how to elevate your career as an executive assistant or personal assistant with our comprehensive EA Mastery Workshop. Gain new skills, strategies, and tools to maximize your impact and achieve success.

Duration 5 Days 30 CPD hours This course is intended for Candidates for this course design, develop, secure, and troubleshoot Power Platform solutions. Candidates implement components of a solution that include application enhancements, custom user experience, system integrations, data conversions, custom process automation, and custom visualizations. Candidates will gain applied knowledge of Power Platform services, including in-depth understanding of capabilities, boundaries, and constraints. Overview After completing this course, students will be able to: Create a technical design Configure Common Data Service Create and configure Power Apps Configure business process automation Extend the user experience Extend the platform Develop Integrations The Microsoft Power Platform helps organizations optimize their operations by simplifying, automating and transforming business tasks and processes. In this course, students will learn how to build Power Apps, Automate Flows and extend the platform to complete business requirements and solve complex business problems. Create a model-driven application in Power Apps This module introduces you to creating a model-driven app in Power Apps that uses Common Data Service. Get started using Common Data Service This module will explain the concepts behind and benefits of Common Data Service. Creating an environment, entities, fields and options sets are also discussed. Create a canvas app in Power Apps This module introduces you to Power Apps, helps you create and customize an app, and then manage and distribute it. It will also show you how to provide the best app navigation, and build the best UI using themes, icons, images, personalization, different form factors, and controls. Automate a business process using Power Automate This module introduces you to Power Automate, teaches you how to build workflows, and how to administer flows. Create a business process flow in Power Automate This module introduces you to creating business process flows in Power Automate Introduction to developing with Power Platform This module is the first step in learning about platform, tools, and the ecosystem of the Power Platform Extending the Power Platform user experience Model Driven apps This module describes how to create client scripting, perform common actions with client script, and automate business process flow with client scrip. Learn about what client script can do, rules, and maintaining scripts. Discover when to use client script as well as when not to use client script. Create components with Power Apps Component Framework This module describes how to get started with Power Apps Component Framework with an introductory module on the core concepts and components. Then it shows you how to build a component and work with advanced Power Apps Component Framework features. Extending the Power Platform Common Data Service This module looks at the tools and resources needed for extending the Power Platform. We'll start with looking at the SDKs, the extensibility model, and event framework. This learning path also covers when to use plug-ins. Configuration of plug-ins as well as registering and deploying plug-ins. Integrate with Power Platform and Common Data Service This module describes how to integrate with Common Data Service using code by learning about Common Data Service API. Get an in-depth overview of options available with Common Data Service to integrate data and events to Azure. Extend Power Apps portals This module describes how to transform a content portal into a full web app interacting with Common Data Service. We will also cover the options available to customizers and developers to extend the portal functionality and integrate with Office 365, Power Platform, and Azure components. Additional course details: Nexus Humans PL-400T00 Microsoft Power Platform Developer 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 PL-400T00 Microsoft Power Platform Developer 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.

Program Management Skills: Virtual In-House Training Program managers coordinate and give oversight to the efforts of marketing groups, project teams, product delivery, maintenance and support, operations and staff from various functional groups, including suppliers, business partners, and other external bodies. The goal is to ensure that proposed business transformation, through the delivery of complex products and processes, is implemented to realize the organization's strategic benefits and objectives, for which the program was selected. The goals of this course are twofold: To provide participants with key program management principles and techniques, recognized as best practices, to enable more effective program management; and to leverage core elements of the program management life cycle, processes, tools and techniques, to enable program management effectiveness. The participant will learn and apply the principles of program management through discussions, activities, and case study exercises. What You Will Learn At the end of this workshop, you will be able to: Maximize the transformational impact of a program according to the business needs Explain management principles and techniques and apply them within a program context Implement program governance and organization that will produce expected benefits Plan for and manage benefit realization, risks, issues, and quality Manage component projects' interdependencies that are linked to both program and strategic objectives Engage program stakeholders effectively. Improve communication and action planning effectiveness for programs in organizations Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Fundamental definitions and concepts Program challenges and benefits Program best practices and success criterion Stakeholder management Governance: program management office and program boards Standard for Program Management overview Vision, Leadership, and the Business Case What is vision, why, and how? Leadership vs. Management Program business case Program Organization and Governance Program organization Program governance Program board roles and responsibilities Benefits Management Benefits explored Benefits management Benefits realization Program Management Planning Program management plan Program blueprint and roadmap Program component dossier Program tranches Program estimating Program scheduling Program Monitoring and Controlling Program Control - An Overview Program Monitoring and Controlling Monitoring and Controlling Transition Program Risk and Issue Management Risk and issue management overview Program risk management Program issue management Program Quality Management Program quality management overview Program quality management principles Program Stakeholder Management Stakeholder engagement overview Stakeholder engagement planning EI, trust, communication and stakeholder engagement Program Closure and Benefits Sustainment Program closure overview Closing the program Program benefits sustainment Summary What did we learn, and how can we implement this in our work environments?

Lean Six Sigma Black Belt Certification Program: Virtual In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

Essential 5G training course description This course is designed to give delegates an explanation of the technologies and interworking requirements of the next generation of cellular communications. It is not a definitive set of descriptions but a possibility of the final deployment. we will investigate the 10 pillars for 5G which will include various Radio Access Technologies that are required to interwork smoothly. We will look at the 4G Pro features and other RATs. What will you learn List the ten pillars of 5G deployment. Describe the 5G Internet. Explain virtualization and RAT virtulization. Describe Software Defined Networks (SDN). Explain carrier aggregation. Describe the mobile cloud. Explain an overall picture of 5G architecture. Essential 5G training course details Who will benefit: Anyone looking for an understanding of the technologies and interworking requirements of the next generation of cellular communications. Prerequisites: None. Duration 3 days Essential 5G training course contents Drivers for 5G 5G Road Map, 10 Pillars of 5G, evolving RATs, oSON, MTCm, mm-wave, backhaul, EE, new spectrum, spectrum sharing, RAN virtualisation. 4G LTE Advanced MIMO technology in release 8, Downlink & uplink MIMO R8, MIMO technology in LTE advanced, Downlink 8-layer SU-MIMO, Downlink MU-MIMO, Uplink MU-MIMO, Uplink transmit diversity, Coordinated multi-point operation (CoMP), Independent eNB & remote base station configurations, Downlink CoMP. ICIC & eICIC ICIC, Homogeneous to heterogeneous network evolution, Introduction to eICIC, Macro-pico scenario, Macro-femto scenario, Time orthogonal frequencies. Almost Blank Subframe (ABS). Carrier aggregation Component carriers (CC), CC aggregation deployments, Intra-band contiguous solutions, Intra-band non-contiguous solutions, Inter-band non-contiguous solutions, CA bandwidth classes, Aggregated transmission bandwidth configurations (ATBC), Possible carrier aggregation configs. eIMTA TDD UL-DL reconfig. for traffic adaptation, Reconfig. mechanisms, Interference mitigation schemes, Dynamic & flexible resource allocation. 5G architectures 5G in Europe, horizon 2020 framework, 5G infrastructure PPP, METIS project, 5G in North America, academy research, company R&D, 5G specifications. The 5G internet High-level view of Cloud Services, The Internet of Things & context awareness, Network reconfiguration & virtualization support, server proliferation, how VMs fix underutilised server problem, enter the hypervisor, why are VM such a big deal? SDN, evolution of the data centre network, high availability, low latency, scalability, security, cost model explodes, service-oriented API. OpenFlow switches, OpenFlow controllers, how SDN works. The big picture, pulling it all together, why the network had to change, how SDN & NFV tie together. Evolutionary approach to the internet, architectures for distributed mobility management, MEDIEVAL & MEDIVO projects, a clean slate approach, mobility first architecture. VNet, INM, NetInf, ForMux, MEEM. Generic Path (GP) & anchorless mobility (AM), Quality of Service support, network resource provisioning, resourcing inside a network. IntServ, RSVP, DiffServ, CoS. Emerging approach for resource over- provisioning, example use case architecture for scalable resource control scenarios in the 5G internet. Integrating SDN/NFV for efficient resource over-reservation control, control information repository, service admission control policies, network resource provisioning, control enforcement functions, network configurations & operations. Small cells for 5G Average spectral efficiency evolution, WiFi & Femto cells, Capacity limits. Achievable gains with densifications, multi-antenna techniques, small cells. Mobile data demand, approach & methodology, subscriber density and traffic demand projections to 2020. Demand versus capacity, global mobile data traffic increase modelling, country level backhaul traffic projections, Small cell challenges, backhaul, spectrum, automation. Cooperation for next gen wireless networks Diversity & relaying strategies, cooperation & network coding, ARQ & MAC protocols, NCCARQ & PRCSMA packet exchange, Physical layer impact on MAC protocol analysis, NCCARQ overview, PHY layer impact, Case study on NCCARQ. Mobile clouds Mobile cloud, Mobile cloud enablers, mobile user domain, wireless technologies, WWAN WLAN and WPAN range, Bluetooth, IEEE.802.15.4 & software stacks, infrared, near field communications (NFC). Network coding, store & forward vs compute & forward, linear network coding, random linear coding. Security for 5G communications Potential 5G communication systems architectures, Security issues & challenges. Mobile malware attacks targeting the UE, 5G mobile botnets, access networks, attacks on 4G networks, C-RNTI & packet sequence number based UE location tracking, false buffer status reports attacks, message insertion attacks, HeNB attacks, physical attacks, credential attacks, configuration and protocol attacks, attacks on MON, user data & identity attacks, mobile operator's core network, DDoS attacks targeting MON, signalling amplification, HSS saturation, external IP networks.

Aligned with the AIGP certification program, AI Governance Professional Training is for professionals tasked with implementing AI governance and risk management in their organizations. It provides baseline knowledge and strategies for responding to complex risks associated with the evolving AI landscape. This training meets the rapidly growing need for professionals who can develop, integrate and deploy trustworthy AI systems in line with emerging laws and policies. About This Course This training teaches critical artificial intelligence governance concepts that are also integral to the AIGP certification exam. While not purely a 'test prep' course, this training is appropriate for professionals who plan to certify, as well as for those who want to deepen their AI governance knowledge. Both the training and the exam are based on the same body of knowledge.   Module 1: Foundations of artificial intelligence Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context. Module 2: AI impacts on people and responsible AI principles Outlines the core risks and harms posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI. Module 3: AI development life cycle Describes the AI development life cycle and the broad context in which AI risks are managed. Module 4: Implementing responsible AI governance and risk management Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while acknowledging AI systems' potential societal benefits. Module 5: Implementing AI projects and systems Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment. Module 6: Current laws that apply to AI systems Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform. Module 7: Existing and emerging AI laws and standards Describes global AI-specific laws and the major frameworks and standards that exemplify how AI systems can be responsibly governed. Module 8: Ongoing AI issues and concerns Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues. Accreditation The associated exam is accredited by the IAPP under its ANSI Accreditation Who Should Attend? Any professionals tasked with developing AI governance and risk management in their operations, and anyone pursuing IAPP Artificial Intelligence Governance Professional certification. Prerequisites A general understanding of AI, Corporate Governance, and Business value would be of benefit to participants. Assessment As with all IAPP exams, the AIGP is a 90 question, multiple choice exam to be completed within 150 minutes. Exams are hosted by Pearsonvue and can be taken either remotely, or via any one of hundreds of exam venues globally. A passing score is achieved at 70% Our Guarantee We are an approved IAPP training provider Exam pass guarantee, or retrain until you do, for free What's Included? Participant Guide Study Guide Practice Exam Exam voucher Breakfast, lunch, coffees and snacks (Classroom courses only) Certification Logo

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is any IT, facilities or data centre professional who works in and around the data centre and has the responsibility to achieve and improve efficiency and environmental sustainability, whilst maintaining the availability and manageability of the data centre. Overview After completion of the course the participant will be able to: Understand the impact of data centres on the environment Describe the various environmental/energy management standards Understand the purpose and goals of the legally binding international treaties on climate change Implement various sustainable performance metrics and how to use them in the data centre environment Manage data centre environmental sustainability using international standards Set up the measurement, monitoring and reporting of energy usage Use power efficiency indicators in a variety of data centre designs Use best practices for energy savings in the electrical infrastructure and in the mechanical (cooling) infrastructure Use best practices for energy savings for the ICT equipment and data storage Understand the importance of water management and waste management Understand the different ways to use sustainable energy in the data centre Get practical tips and innovative ideas to make a data centre more sustainable The CDESS© course is aimed at providing knowledge of the standards and guidelines related to environmental sustainability, and how to move your data centre (existing or new) to a more environmentally sustainable design and operations. Impact of Data Centres on the Environment Predictions in 2010 Current situation Outlook and commitments What is Environmental Sustainability The importance of sustainability Senior management commitment Environmental sustainability framework Sustainability policies Performance standards and metrics Information policies Transparency Awareness Service charging models Environmental Management Environmental sustainability framework (ISO 14001) Standards and guidelines ? ISO 50001 / ISO 30134 Measurement and categories Baselining Trend analysis Reporting Power Effiðciency Indicators Various eðfficiency indicators Power Usage Effectiveness (PUE) PUE measurement levels Factors affecting PUE Measurement points and intervals PUE in mixed source environments Measuring PUE in a mixed-use building PUE reporting Impact of PUE after optimising IT load Electrical Energy Savings (Electrical) Identifying the starting point for saving energy Sizing of power DC power Generators UPS systems Power Factor (PF) Energy savings on lighting Electrical Energy Savings (Mechanical) Energy savings on the cooling infrastructure Temperature and humidity setpoints Various energy eðcient cooling technologies Energy savings on the airflow Liquid cooling Energy reusage PUE, ERE/ERF and Control Volume Electrical Energy Savings (ICT) Procurement IT equipment energy eðfficiency ITEEsv, SMPE, SMPO IT equipment utilisation Server virtualisation Open compute project Electrical Energy Savings (Data Storage) Data management Data storage management Data storage equipment effiðciency Water Management Water Usage Effectiveness (WUE) Improving WUE Water usage at the power generation source Energy Water Intensity Factor (EWIF) Waste Management Waste management policies Life-cycle assessment (Cradle to the grave) 3 R?s for waste management Reduce Reuse Second-hand market Recycle Sustainable Energy Usage Sustainable energy sources Power purchase agreements Energy attribute certificates Renewable Energy Factor (REF) Matching renewable energy supply and demand Sustainable energy storage Carbon trading Automated Environmental Management Systems Use of AI and machine learning Load migration Data Centre Infrastructure Management (DCIM) solutions

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.