Oversikt over relevante kurs innen IT-kurs i Nordreisa

Du vil få tilsendt en «Core guidance» bok og sertifiserings-voucher slik at du kan ta sertifiseringstesten for eksempel hjemme eller på jobb. Denne vil være gyldig i ett år. Tid for sertifiseringstest avtales som beskrevet i e-post med voucher. Eksamen overvåkes av en web-basert eksamensvakt.   Eksamen er på engelsk. Eksamensformen er multiple choice - 40 spørsmål skal besvares, og du består med 70% riktige svar (dvs. 28 av 40). Deltakerne har 1 time og 30 minutter til rådighet på eksamen.  Ingen hjelpemidler er tillatt.  Nødvendige forkunnskaper: Bestått ITIL Foundation sertifisering Gjennomført godkjent kurs/e-læring [-]

I kurset finner du en rekke videoklipp som viser i programmet hvordan man utfører de ulike oppgavene og presenterer resultatet av dette. Du får innsendingsoppgaver underveis som vil bli fulgt opp av en faglærer, og du har tilgang til faglærer i hele kursperioden. Du kan du stille spørsmål, både til faglærer, men også i et forum som er tilgjengelig for deltakere i kurset.Du får tilgang til vår e-læringsportal som vil gi deg god oversikt over progresjonen i kurset i et brukervennlig og enkelt system.I kurset ser vi blant annet på følgende temaer:Funksjoner: ANTALL og ANTALLA HVIS-funksjonen FINN.RAD og FINN.KOLONNE ANTALL.HVIS og SUMMERHVIS AVRUND Formatering: Dato- og tidfunksjoner Tekstfunksjoner Formatering av datoer Betinget formatering Kopiering av formatering Avansert tallformatering Beskyttelse av celler Formler og navngivning: Låsing av celler Navngivning av celler Målsøking og scenariobehandling Jobbe med lister og database: Sortering og filtrering Fjerne duplikater Pivottabeller: Datagrunnlaget og datakilder Oppsett av felt Delsummer og totalsummer Gruppere på dato Velge beregning i verdifelt Vis verdier som Formatere tall Formatere tabell Diagrammer Kurset består av tekst, bilder og en rekke videoklipp i leksjonene i kurset. Det er ikke behov for noe ytterligere dokumentasjon. Du får tilbakemeldinger fra faglærer på innsendingsoppgaver og du har tilgang til hjelp i hele kursperioden (ett år). Mer informasjon om kurset her. [-]

ITIL® 4 Foundation - 2 days course for ITIL experienced [-]

Introduksjon Kurset gir deg en grunnleggende innføring i ITIL® beste praksis rammeverket versjon 4. Kurset gir innføring i basis konseptet, prinsippene, prosessene og funksjonene som er definert som beste praksis. Kurset vil også forberede deg til å gjennomføre ITIL Foundation sertifiseringtest. ForutsetningerIngen forutsetninger for å delta på kurset.Faglige kvalifikasjonKurset leder frem til ITIL Foundation Certificate.(Sertifiseringstest gjennomføres på siste kursdag)KursdokumentasjonOmfattende kursdokumentasjon som inneholder Kurskompendium, ITIL Pocket Guide, Norsk-Engelsk ordliste, 115 testoppgaver.SertifiseringInkludert i kursprisen er ITIL Fondation eksamen EXIN.Eksamen gjennomføres på ettermiddagen dag 3 - den avholdes skriftlig og er på engelsk.Eksamensformen er multiple choice - 40 spørsmål skal besvares, og du består ved 65% korrekte svar (dvs 26 av 40 spørsmål). Deltakerne har 1 time og 15 minutter til rådighet på eksamen. ITIL® is a registered trade mark of AXELOS Limited.   Kursinnhold Service Management as a practise • Innføring i IT Service Management• BESTE PRAKSIS: Forstå hva og hvorfor• Tjenesteorientering The Service Lifecycle Innføring i alle fasene av livssyklusen - målene og forretningsverdien for hver fase.• Service Strategy• Service Design• Service Transition• Service Operations• Continual Service Improvement Service Management processes Hvordan de ulike prosessene spiller inn i livssyklusen. Vi diskuterer mål, omfang, aktiviteter, nøkkeltall og annet: Service Strategy • Strategy Management• Service Portfolio Management• Demand Management• Financial Management Service Design • Design Coordination• Service Catalogue Management• Service Level Management• Supplier Management• Availability Management• Capacity Management• IT Service Continuity Management• Information Security Management Service Transition • Transition planning and support• Change Management• Service Asset and Configuration Management• Release and Deployment Management Service Operations • Event Management• Incident Management• Request Fulfilment• Problem Management Continual Service Operations • Continual Service Improvement model• The seven-step improvement process Continual Service Operations • Continual Service Improvement model• The seven-step improvement process Functions Forstå mål, organisasjonsstruktur, bemanning, nøkkeltall og sammenhenger i ulike funksjoner• Service Desk• Technical Management• Application Management• IT Operations Management (IT Operations Control, Facilities Management) Roles Ansvar og funksjon hos de to nøkkelrollene i Service Management og innblikk i øvrige roller.• RACI modell• Process owner• Service owner Technology and Architecture • Service Management Technology [-]

Bli kjent med Revu (Bruksområder, grensesnitt, menyer, verktøy, paneler og profiler) Grunnleggende PDF-håndtering med Revu Markeringsverktøy og måleverktøy Innføring i Tool Chest Innføring i Markeringslisten Innføring i Studio [-]

COURSE OVERVIEW This course is comprised of the following Microsoft Official Curriculum modules: MS-500T01 Managing Microsoft 365 Identity and Access, MS-500T02 Implementing Microsoft 365 Threat Protection, MS-500T03 Implementing Microsoft 365 Information Protection and MS-500T04 Administering Microsoft 365 Built-in Compliance.   MS-500T01 Managing Microsoft 365 Identity and Access Help protect against credential compromise with identity and access management. In this course you will learn how to secure user access to your organization’s resources. Specifically, this course covers user password protection, multi-factor authentication, how to enable Azure Identity Protection, how to configure Active Directory federation services, how to setup and use Azure AD Connect, and introduces you to Conditional Access. You will also learn about solutions for managing external access to your Microsoft 365 system.   MS500T02 Implementing Microsoft 365 Threat Protection Threat protection helps stop damaging attacks with integrated and automated security. In this course you will learn about threat protection technologies that help protect your Microsoft 365 environment. Specifically, you will learn about threat vectors and Microsoft’s security solutions for them. You will learn about Secure Score, Exchange Online protection, Azure Advanced Threat Protection, Windows Defender Advanced Threat Protection, and how to use Microsoft 365 Threat Intelligence. It also discusses securing mobile devices and applications. The goal of this course is to help you configure your Microsoft 365 deployment to achieve your desired security posture.   MS500T03 Implementing Microsoft 365 Information Protection Information protection is the concept of locating and classifying data anywhere it lives. In this course you will learn about information protection technologies that help secure your Microsoft 365 environment. Specifically, this course discusses information rights managed content, message encryption, as well as labels, policies and rules that support data loss prevention and information protection. Lastly, the course explains the deployment of Microsoft Cloud App Security.   MS500T04 Administering Microsoft 365 Built-in Compliance Internal policies and external requirements for data retention and investigation may be necessary for your organization. In this course you will learn about archiving and retention in Microsoft 365 as well as data governance and how to conduct content searches and investigations. Specifically, this course covers data retention policies and tags, in-place records management for SharePoint, email retention, and how to conduct content searches that support eDiscovery investigations. The course also helps your organization prepare for Global Data Protection Regulation (GDPR).   Virtual Learning   This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins. TARGET AUDIENCE This course is for the Microsoft 365 security administrator role. This role collaborates with the Microsoft 365 Enterprise Administrator, business stakeholders and other workload administrators to plan and implement security strategies and ensures that the solutions comply with the policies and regulations of the organization. COURSE CONTENT Module 1: User and Group Security This module explains how to manage user accounts and groups in Microsoft 365. It introduces you to Privileged Identity Management in Azure AD as well as Identity Protection. The module sets the foundation for the remainder of the course.   Module 2: Identity Synchronization This module explains concepts related to synchronizing identities. Specifically, it focuses on Azure AD Connect and managing directory synchronization to ensure the right people are connecting to your Microsoft 365 system.   Module 3: Federated Identities This module is all about Active Directory Federation Services (AD FS). Specifically, you will learn how to plan and manage AD FS to achieve the level of access you want to provide users from other directories.   Module 4: Access Management This module describes Conditional Access for Microsoft 365 and how it can be used to control access to resources in your organization. The module also explains Role Based Access Control (RBAC) and solutions for external access.   Module 5: Security in Microsoft 365 This module starts by explaining the various cyber-attack threats that exist. It then introduces you to the Microsoft solutions to thwart those threats. The module finishes with an explanation of Microsoft Secure Score and how it can be used to evaluate and report your organizations security posture.   Module 6: Advanced Threat Protection This module explains the various threat protection technologies and services available in Microsoft 365. Specifically, the module covers message protection through Exchange Online Protection, Azure Advanced Threat Protection and Windows Defender Advanced Threat Protection.   Module 7: Threat Intelligence This module explains Microsoft Threat Intelligence which provides you with the tools to evaluate and address cyber threats. You will learn how to use the Security Dashboard in the Microsoft 365 Security and Compliance Center. It also explains and configures Microsoft Advanced Threat Analytics.   Module 8: Mobility This module is all about securing mobile devices and applications. You will learn about Mobile Device Management and how it works with Intune. You will also learn about how Intune and Azure AD can be used to secure mobile applications.   Module 9: Information Protection This module explains information rights management in Exchange and SharePoint. It also describes encryption technologies used to secure messages. The module introduces how to implement Azure Information Protection and Windows Information Protection.   Module 10: Data Loss Prevention This module is all about data loss prevention in Microsoft 365. You will learn about how to create policies, edit rules, and customize user notifications.   Module 11: Cloud Application Security This module is all about cloud app security for Microsoft 365. The module will explain cloud discovery, app connectors, policies, and alerts.     [-]

Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms TARGET AUDIENCE Students in this course are interested in designing and implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam. COURSE OBJECTIVES Plan for the transformation with shared goals and timelines Select a project and identify project metrics and Key Performance Indicators (KPI's) Create a team and agile organizational structure Design a tool integration strategy Design a license management strategy (e.g., Azure DevOps and GitHub users) Design a strategy for end-to-end traceability from work items to working software Design an authentication and access strategy Design a strategy for integrating on-premises and cloud resources Describe the benefits of using Source Control Describe Azure Repos and GitHub Migrate from TFVC to Git Manage code quality, including technical debt SonarCloud, and other tooling solutions Build organizational knowledge on code quality Explain how to structure Git repos Describe Git branching workflows Leverage pull requests for collaboration and code reviews Leverage Git hooks for automation Use Git to foster inner source across the organization Explain the role of Azure Pipelines and its components Configure Agents for use in Azure Pipelines Explain why continuous integration matters Implement continuous integration using Azure Pipelines Design processes to measure end-user satisfaction and analyze user feedback Design processes to automate application analytics Manage alerts and reduce meaningless and non-actionable alerts Carry out blameless retrospectives and create a just culture Define an infrastructure and configuration strategy and appropriate toolset for a release pipeline and application infrastructure Implement compliance and security in your application infrastructure Describe the potential challenges with integrating open-source software Inspect open-source software packages for security and license compliance Manage organizational security and compliance policies Integrate license and vulnerability scans into build and deployment pipelines Configure build pipelines to access package security and license ratings   COURSE CONTENT Module 1: Get started on a DevOps transformation journey Module 1 Lessons Introduction to DevOps Choose the right project Describe team structures Choose the DevOps tools Plan Agile with GitHub Projects and Azure Boards Introduction to source control Describe types of source control systems Work with Azure Repos and GitHub Lab 1: Agile planning and portfolio management with Azure Boards   Lab 2: Version controlling with Git in Azure Repos   After completing Module 1, students will be able to: Understand what DevOps is and the steps to accomplish it Identify teams to implement the process Plan for the transformation with shared goals and timelines Plan and define timelines for goals Understand different projects and systems to guide the journey Select a project to start the DevOps transformation Identify groups to minimize initial resistance Identify project metrics and Key Performance Indicators (KPI's) Understand agile practices and principles of agile development Create a team and agile organizational structure Module 2: Development for enterprise DevOps Module 2 Lessons Structure your Git Repo Manage Git branches and workflows Collaborate with pull requests in Azure Repos Explore Git hooks Plan foster inner source Manage Git repositories Identify technical debt Lab 3: Version controlling with Git in Azure Repos   After completing Module 2, students will be able to: Understand Git repositories Implement mono repo or multiple repos Explain how to structure Git Repos Implement a change log Describe Git branching workflows Implement feature branches Implement GitFlow Fork a repo Leverage pull requests for collaboration and code reviews Give feedback using pull requests Module 3: Implement CI with Azure Pipelines and GitHub Actions Module 3 Lessons Explore Azure Pipelines Manage Azure Pipeline agents and pools Describe pipelines and concurrency Explore Continuous integration Implement a pipeline strategy Integrate with Azure Pipelines Introduction to GitHub Actions Learn continuous integration with GitHub Actions Design a container build strategy Lab 4: Configuring agent pools and understanding pipeline styles   Lab 5: Enabling continuous integration with Azure Pipelines   Lab 6: Integrating external source control with Azure Pipelines   Lab 7: Implementing GitHub Actions by using DevOps Starter   Lab 8: Deploying Docker Containers to Azure App Service web apps   After completing Module 3, students will be able to: Describe Azure Pipelines Explain the role of Azure Pipelines and its components Decide Pipeline automation responsibility Understand Azure Pipeline key terms Choose between Microsoft-hosted and self-hosted agents Install and configure Azure pipelines Agents Configure agent pools Make the agents and pools secure Use and estimate parallel jobs Module 4: Design and implement a release strategy Module 4 Lessons Introduction to continuous delivery Create a release pipeline Explore release strategy recommendations Provision and test environments Manage and modularize tasks and templates Automate inspection of health Lab 9: Creating a release dashboard   Lab 10: Controlling deployments using Release Gates   After completing Module 4, students will be able to: Explain continuous delivery (CD) Implement continuous delivery in your development cycle Understand releases and deployment Identify project opportunities to apply CD Explain things to consider when designing your release strategy Define the components of a release pipeline and use artifact sources Create a release approval plan Implement release gates Differentiate between a release and a deployment Module 5: Implement a secure continuous deployment using Azure Pipelines Module 5 Lessons Introduction to deployment patterns Implement blue-green deployment and feature toggles Implement canary releases and dark launching Implement A/B testing and progressive exposure deployment Integrate with identity management systems Manage application configuration data Lab 11: Configuring pipelines as code with YAML   Lab 12: Setting up and running functional tests   Lab 13: Integrating Azure Key Vault with Azure DevOps   After completing Module 5, students will be able to: Explain the terminology used in Azure DevOps and other Release Management Tooling Describe what a Build and Release task is, what it can do, and some available deployment tasks Implement release jobs Differentiate between multi-agent and multi-configuration release job Provision and configure target environment Deploy to an environment securely using a service connection Configure functional test automation and run availability tests Setup test infrastructure Use and manage task and variable groups Module 6: Manage infrastructure as code using Azure and DSC Module 6 Lessons Explore infrastructure as code and configuration management Create Azure resources using Azure Resource Manager templates Create Azure resources by using Azure CLI Explore Azure Automation with DevOps Implement Desired State Configuration (DSC) Implement Bicep Lab 14: Azure deployments using Azure Resource Manager templates   After completing Module 6, students will be able to: Understand how to deploy your environment Plan your environment configuration Choose between imperative versus declarative configuration Explain idempotent configuration Create Azure resources using ARM templates Understand ARM templates and template components Manage dependencies and secrets in templates Organize and modularize templates Create Azure resources using Azure CLI Module 7: Implement security and validate code bases for compliance Module 7 Lessons Introduction to Secure DevOps Implement open-source software Software Composition Analysis Static analyzers OWASP and Dynamic Analyzers Security Monitoring and Governance Lab 15: Implement security and compliance in Azure Pipelines   Lab 16: Managing technical debt with SonarQube and Azure DevOps   After completing Module 7, students will be able to: Identify SQL injection attack Understand DevSecOps Implement pipeline security Understand threat modeling Implement open-source software Explain corporate concerns for open-source components Describe open-source licenses Understand the license implications and ratings Work with Static and Dynamic Analyzers Configure Microsoft Defender for Cloud Module 8: Design and implement a dependency management strategy Module 8 Lessons Explore package dependencies Understand package management Migrate, consolidate, and secure artifacts Implement a versioning strategy Introduction to GitHub Packages Lab 17: Package management with Azure Artifacts   After completing Module 8, students will be able to: Define dependency management strategy Identify dependencies Describe elements and componentization of a dependency management Scan your codebase for dependencies Implement package management Manage package feed Consume and create packages Publish packages Identify artifact repositories Migrate and integrate artifact repositories Module 9: Implement continuous feedback Module 9 Lessons Implement tools to track usage and flow Develop monitor and status dashboards Share knowledge within teams Design processes to automate application analytics Manage alerts, Blameless retrospectives and a just culture Lab 18: Monitoring application performance with Application Insights   Lab 19: Integration between Azure DevOps and Microsoft Teams   Lab 20: Sharing Team Knowledge using Azure Project Wikis   After completing Module 9, students will be able to: Implement tools to track feedback Plan for continuous monitoring Implement Application Insights Use Kusto Query Language (KQL) Implement routing for mobile applications Configure App Center Diagnostics Configure alerts Create a bug tracker Configure Azure Dashboards Work with View Designer in Azure Monitor [-]

På webinaret vil vi vise deg hvordan du kan lage nettbaserte spørreundersøkelse, tester og påmeldingsskjemaer ved hjelp av Microsoft Forms. Microsoft Forms er en enkel og elegant app i Microsoft 365 familien for opprettelse av undersøkelser og tester. Du kan lage skjema med flere språk i samme skjema. Du kan ha forgreninger til ulike svarretninger alt etter hva som velges som svar. Det er mange ulike spørsmålsalternativer å velge mellom. Svarene kan være anonyme om ønskelig. Du kan også sette inn undersøkelser (poll) i et Teams-møte eller som en del av en presentasjon i PowerPoint. Resultatene behandler og analyserer du enkelt i Excel. Hva er Forms | Forskjell undersøkelser og tester | Personlige skjema vs gruppeskjema | Opprette skjema | Spørsmålstyper | Forgreninger | Innstillinger | Flere språk i samme skjema | Simulere skjema | Delingsmåter (samle inn svar) | Samarbeide om samme skjema eller duplisere skjema (gi kopi til andre) | Resultater og analyser | Forms og Teams | Forms og PowerPoint Pris: 1690 kroner [-]

 You will also learn how to apply Lean thinking to identify Epics, break them down into Features and Stories, plan and execute Iterations, and plan Program Increments. Finally, you learn about the Continuous Delivery Pipeline and DevOps culture, how to effectively integrate as a Product Owner and a Product Manager, and what it takes to relentlessly improve the ART.    TOPICS COVERED -Product Owner/Product Manager in the SAFe enterprise-Preparing for PI Planning-Leading PI Planning-Executing Iterations-Executing the Program Increment-Becoming a Certified SAFe® Product Owner/Product Manager ONLINE TRAINING - 3 days – from 09:00 AM – 03: PM- Pre-meeting before class to check the technical setup and greet each other- Homework before class to increase the benefits of the training- Online discussions and feedback on exercises- Additional help for certification and exam LEARNING GOALS To perform the role of a SAFe® Product Owner/Product Manager, attendees should be able to:- Articulate the Product Owner and Product Manager roles- Connect SAFe Lean-Agile principles and values to the PO/PM roles- Decompose Epics into Features and decompose Features into Stories- Manage Program and Team backlogs- Collaborate with Agile teams in estimating and forecasting work- Represent Customer needs in Program Increment Planning- Execute the Program Increment and deliver continuous value WHO WILL BENEFIT? -Product Owners, Product Managers, Product Line Managers, Business Owners, and BusinessAnalysts-Solution Managers, Portfolio Managers, Program Managers, and members of the LACE-Enterprise, Solution, and System Architects PREREQUISITES All are welcome to attend the course, regardless of experience. However, the following prerequisites are highly recommended for those who intend to take the SAFe® 5 Product Owner/Product Manager (POPM) certification exam:- Attend a Leading SAFe® course- Experience working in a SAFe environment- Experience with Lean, Agile, or other relevant certifications [-]

Fleksible kurs for fremtidenNy kunnskap skal gi umiddelbar effekt, og samtidig være holdbar og bærekraftig på lang sikt. NTI AS har 30 års erfaring innen kurs og kompetanseheving, og utdanner årlig rundt 10.000 personer i Nord Europa innen CAD, BIM, industri, design og konstruksjon.   Målsetning: Oppnå grunnleggende ferdigheter i å navigere, kommunisere, og gjøre mengdeuttak fra BIM-modeller i IFC-formatet med bruk av Solibri Site.   På kurset vil du lære å: Sammenstille og navigere i IFC-modeller Velge ut grupper av objekter for nærmere studier Legge inn snitt, måle, markere og opprette slides fra visninger av modellen Opprette og følge opp pågående saker i form av Excel- og BCF-rapporter Se på resultatet av utførte regelsjekker i modellen Høste informasjoner og mengder fra modellen basert på eksisterende maler [HF-NA1] og klassifikasjoner Skape egne klassifikasjoner og definisjoner for mengdeuttak Spesialtilpasset kurs: NTI anbefaler spesialtilpassede kurs for bedrifter som planlegger å sende to eller flere deltakere på Solibri-kurs. Grunnen til dette er at Solibri brukes av mange forskjellige aktører og profesjoner i BAE-bransjen, og følgelig blir de åpne kursene ofte for generelle for enkelte kursdeltakere. I et spesialtilpasset kurs vil vår kurskonsulent kartlegge fokusområdene i forkant av kurset, og gjennomføre kurset i henhold til selskapets behov, gjerne basert på kundens egne modeller. Utbyttet av kurset blir følgelig mye større. Ta kontakt med oss på telefon 483 12 300, epost: salg-no@nti.biz eller les mer på www.nti.biz [-]

COURSE OVERVIEW . It also prepares delegates for the ITIL Foundation Certificate Examination. The course is based on the ITIL4 best practice service value system featured in the latest 2019 guidelines. TARGET AUDIENCE This course is aimed at all levels of IT professional and those involved in designing, building, delivering and managing modern digital products and services. COURSE OBJECTIVES After you complete this course you will be able to: Key IT service management concepts. How ITIL guiding principles can help and organization to adopt and adapt service management. The 4 dimensions of service management. The purpose and components of the service value system. The activities of the service value chain and how the interconnect. Know the purpose of key ITIL practices. Sit the ITIL4 foundation examination - Sample papers are set during the class by instructors to take during the class or as homework exercises. COURSE CONTENT IT Service Management definitions; Service, Utility, Warranty, Customer, User, Service management, Sponsor Key concepts of value creation Key concepts of service relationships; service offering; service provision; service consumption; service relationship management The nature, use and interaction of 7 ITIL guiding principles; Focus on value; Start where you are; Progress iteratively with feedback; Collaborate and promote visibility; Think and work holistically; Keep it simple and practical; Optimize and automate The 4 dimensions of service management; Organizations and people; Information and technology; Partners and suppliers; Value streams and processes    The ITIL service value system The service value chain, its inputs and outputs, and its role in supporting value streams Service value chain elements; Plan, Improve, Engage, Design & transition, Obtain / Build, Deliver & support Detail of how the following ITIL practices support the service value chain: -  Continual Improvement (including continual improvement model); Change control; Incident management; Problem Management; Service request management;  Service desk; Service level management The purpose of the following ITIL practices: - Information security management; Relationship management; Supplier management; Availability management; Capacity and performance management; Service configuration management;    IT asset management; Business analysis; Service continuity management; Deployment management; Monitoring and event management; Release management   TEST CERTIFICATION Recommended preparation for exam(s): ITIL4 Foundation Certificate in IT Service Management This is a pre-requisite for other ITIL4 qualifications. The examination is a 1 hour, closed book, multiple choice paper of 40 questions taken after completion of the course - exam vouchers are provided with this course. These will have a validity of 12 months. You will need to schedule your exams within this time frame. The pass mark is 65% (26 out of 40) Cost of the exam is included in the course fee [-]

I dette kurset kombinerer vi teori med praksis. Gjennom relevante oppgaver får du forståelse og ferdigheter til å trekke ut data og gjøre analyser av hva som skjer på ditt nettsted. Du vil lære hvordan du kan måle effekt av endringer i løsningen, design og markedsføringstiltak. Google Analytics gir deg det datagrunnlaget du trenger for å lage rapporter og analyser for en faktabasert forståelse av hvordan den digitale løsningen fungerer.  Etter kurset vil du kunne hente ut data og lage analyserapporter som gir innsikt og støtte til din markedsføring og kommunikasjon, samt en god utvikling og forbedring av nettstedet. Noen av temaene som dekkes i kurset er: Hva er webanalyse og hvordan fungerer Google Analytics Sentrale begreper De viktigste rapportene Eventtracking / brukeradferd Hva må du vite om oppsett KPIer og måling - hva er viktig å måle Hvordan bruke GA sammen med andre relevante verktøy som Google Data Studio, Google Tag Manager, Google Search Console [-]

Excel controllere/økonomer kurs vinklet fra en Controllers hverdag med fokus på gode metoder for å arbeide med Excel-lister. Påfyllet kurset gir deg, gjør deg i stand til å jobbe mer effektivt i Excel. Kursets mange eksempler, viser hva du virkelig kan få til i Excel, enten det er å jobbe med formler / funksjoner, lister eller store Excel-modeller. Kurset er utviklet av controllere, med det for øye at du skal kunne angripe dine Excel-utfordringer på en smart og effektiv måte. Kurset kan også spesialtilpasses og holdes bedriftsinternt i deres eller våre lokaler.   Kursinnhold:     Datautveksling/Klargjøring av data Mulige inndatametoder: Importering av tekstfil, webspørringer, innliming av data fra WWW. Importere data med ulikt dataformat: tekst - eller databaseformat Formatproblemer ifm. dataimport: ”feil” formater, fjerne deler av informasjon i en celle, fjerne duplikater, kjapt finne skrivefeil   Data/Konsolider Konsolider data: hvor data ligger i samme regneark Konsolidering data: hvor dataene skal behandles på tvers av regneark. Konsolidering data: hvor data ligger i ulike arbeidsbøker   Tabeller/Listefunksjonalitet Definisjonen av en tabell: Viktig å huske når tabellen skal behandles videre. Jobbe med en liste: få gode råd angående arbeid med lister Sortere tabellen: kjapt og enkelt med egendefinerte sorteringsnøkler Filter med Autofilter: filtrere ut bare de data du ønsker eller slette tomme rader. Filter med Avansert filter: få råd om i hvilke situasjoner det er smart å bruke avansert filter og hvordan du enklest bruker dette filteret. Beregninger i tabeller og lister Beregninger med flere variabler: Funksjonene Dsummer, Dantall og DGjennomsnitt Organiser og beregne data : Ved hjelp av delsammendrag. Lær hvordan resultatet kan kopieres til et annet sted. Oppslag i en liste: Funksjonene Finn.Kolonne og Finn.Rad Lag rapporter ved hjelp av Pivotteknikk: Opplev hvor enkelt det er å lage rapporter ved hjelp av pivotteknikk!   "Hva hvis"-analyser og optimalisering Sensitivitetsanalyse: Målsøking er en måte å regne ”baklengs” på. Sensitivitetsanalyse: Tabeller med 1 og 2 variabler Optimalisering: Ved hjelp av Problemløseren   Samarbeid med andre Deling av arbeidsbøker: ved ønske om å jobbe samtidig i samme arbeidsbok Sporing av endringer: når du ønsker å plukke opp de endringer andre har gjort     4 gode grunner til å velge KnowledgeGroup 1. Best practice kursinnhold 2. Markedets beste instruktører 3. Små kursgrupper 4. Kvalitets- og startgaranti   [-]

  Fleksible kurs for fremtidenNy kunnskap skal gi umiddelbar effekt, og samtidig være holdbar og bærekraftig på lang sikt.NTI AS har 30 års erfaring innen kurs og kompetanseheving, og utdanner årlig rundt 10.000 personer i Nord Europa innen CAD, BIM, industri, design og konstruksjon. Twinmotion oppstartskurs for arkitekter og byggebransjen Visuell kommunikasjon er nødvendig i alle operasjoner og i alle ledd. Du kan bruke et bilde internt for å øke forståelsen for hva du jobber med, du kan opptre forebyggende og oppdage feil i planleggingen og skape bedre arbeid raskere. Bilder er svært nyttige mellom arkitekter og deres kunder; kommunikasjonen flyter bedre og du kommer raskere overens. Du vet, visuelt, at du er på samme bølgelengde. Og til slutt er det store gevinster med bilder i markedsføring, vinne anbud eller konkurranser osv. Eksempler på modeller laget i Revit og Sketchup: Bildene som du lager out-of-the-box i Twinmotion kan oppleves godt, men på kurset får du ferdigheter til å heve bildenivået til et nytt nivå! Se noen eksempler nedenfor: Kurset passer for de som jobber i Revit, samt de som skisserer og modellerer i Sketchup, Infraworks, 3dsMax eller andre 3d-modellerings- og designverktøy. Kursinnhold Arbeid med en enkel eksteriørmodell Grensesnitt, navigasjon, hurtigtaster, objekthierarkier Eksisterende objekter, modeller, materialer og lyskilder Import: innstillinger, beste praksis, Revit & FBX-formater Arbeid med egne bibliotek: gjenstander og materialer Bilde- og kamerainnstillinger, lys og vær Urbane objekter, menneske- og kjøretøybevegelse, vegetasjon Bildebehandling / gjengivelse: innstillinger, oppløsning, effekter   Målsetting Målet er at du som kursdeltaker skal kunne være i stand til og lage gode visualiseringer på egenhånd som lever opp til bransjestandarden, og være uavhengig av tredjeparter. Vi tror på mottoet om at «alle skal kunne visualisere» og hjelpe deg å ta i bruk verktøyet som et hverdagsverktøy.   Tilpassete kurs for bedrifterVi vil at kundene våre skal være best på det de gjør - hele tiden. Derfor tenker vi langsiktig om kompetanseutvikling og ser regelmessig kunnskapsløft som en naturlig del av en virksomhet. Vårt kurskonsept bygger på et moderne sett av ulike læringsmiljøer, som gjør det enkelt å finne riktig løsning uansett behov. Ta kontakt med oss på telefon 483 12 300, epost: salg-no@nti.biz eller les mer på www.nti.biz [-]

COURSE OVERVIEW Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. They will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics. TARGET AUDIENCE 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 data analysts and data scientists who work with analytical solutions built on Microsoft Azure. COURSE OBJECTIVES   Explore compute and storage options for data engineering workloads in Azure Design and Implement the serving layer Understand data engineering considerations Run interactive queries using serverless SQL pools Explore, transform, and load data into the Data Warehouse using Apache Spark Perform data Exploration and Transformation in Azure Databricks Ingest and load Data into the Data Warehouse Transform Data with Azure Data Factory or Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Analyze and Optimize Data Warehouse Storage Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Perform end-to-end security with Azure Synapse Analytics Perform real-time Stream Processing with Stream Analytics Create a Stream Processing Solution with Event Hubs and Azure Databricks Build reports using Power BI integration with Azure Synpase Analytics Perform Integrated Machine Learning Processes in Azure Synapse Analytics COURSE CONTENT Module 1: Explore compute and storage options for data engineering workloads This module provides an overview of the Azure compute and storage technology options that are available to data engineers building analytical workloads. This module teaches ways to structure the data lake, and to optimize the files for exploration, streaming, and batch workloads. The student will learn how to organize the data lake into levels of data refinement as they transform files through batch and stream processing. Then they will learn how to create indexes on their datasets, such as CSV, JSON, and Parquet files, and use them for potential query and workload acceleration. Introduction to Azure Synapse Analytics Describe Azure Databricks Introduction to Azure Data Lake storage Describe Delta Lake architecture Work with data streams by using Azure Stream Analytics Lab 1: Explore compute and storage options for data engineering workloads Combine streaming and batch processing with a single pipeline Organize the data lake into levels of file transformation Index data lake storage for query and workload acceleration After completing module 1, students will be able to: Describe Azure Synapse Analytics Describe Azure Databricks Describe Azure Data Lake storage Describe Delta Lake architecture Describe Azure Stream Analytics Module 2: Design and implement the serving layer This module teaches how to design and implement data stores in a modern data warehouse to optimize analytical workloads. The student will learn how to design a multidimensional schema to store fact and dimension data. Then the student will learn how to populate slowly changing dimensions through incremental data loading from Azure Data Factory. Design a multidimensional schema to optimize analytical workloads Code-free transformation at scale with Azure Data Factory Populate slowly changing dimensions in Azure Synapse Analytics pipelines Lab 2: Designing and Implementing the Serving Layer Design a star schema for analytical workloads Populate slowly changing dimensions with Azure Data Factory and mapping data flows After completing module 2, students will be able to: Design a star schema for analytical workloads Populate a slowly changing dimensions with Azure Data Factory and mapping data flows Module 3: Data engineering considerations for source files This module explores data engineering considerations that are common when loading data into a modern data warehouse analytical from files stored in an Azure Data Lake, and understanding the security consideration associated with storing files stored in the data lake. Design a Modern Data Warehouse using Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics Lab 3: Data engineering considerations Managing files in an Azure data lake Securing files stored in an Azure data lake After completing module 3, students will be able to: Design a Modern Data Warehouse using Azure Synapse Analytics Secure a data warehouse in Azure Synapse Analytics Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools In this module, students will learn how to work with files stored in the data lake and external file sources, through T-SQL statements executed by a serverless SQL pool in Azure Synapse Analytics. Students will query Parquet files stored in a data lake, as well as CSV files stored in an external data store. Next, they will create Azure Active Directory security groups and enforce access to files in the data lake through Role-Based Access Control (RBAC) and Access Control Lists (ACLs). Explore Azure Synapse serverless SQL pools capabilities Query data in the lake using Azure Synapse serverless SQL pools Create metadata objects in Azure Synapse serverless SQL pools Secure data and manage users in Azure Synapse serverless SQL pools Lab 4: Run interactive queries using serverless SQL pools Query Parquet data with serverless SQL pools Create external tables for Parquet and CSV files Create views with serverless SQL pools Secure access to data in a data lake when using serverless SQL pools Configure data lake security using Role-Based Access Control (RBAC) and Access Control List After completing module 4, students will be able to: Understand Azure Synapse serverless SQL pools capabilities Query data in the lake using Azure Synapse serverless SQL pools Create metadata objects in Azure Synapse serverless SQL pools Secure data and manage users in Azure Synapse serverless SQL pools Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark This module teaches how to explore data stored in a data lake, transform the data, and load data into a relational data store. The student will explore Parquet and JSON files and use techniques to query and transform JSON files with hierarchical structures. Then the student will use Apache Spark to load data into the data warehouse and join Parquet data in the data lake with data in the dedicated SQL pool. Understand big data engineering with Apache Spark in Azure Synapse Analytics Ingest data with Apache Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics Integrate SQL and Apache Spark pools in Azure Synapse Analytics Lab 5: Explore, transform, and load data into the Data Warehouse using Apache Spark Perform Data Exploration in Synapse Studio Ingest data with Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Spark pools in Azure Synapse Analytics Integrate SQL and Spark pools in Azure Synapse Analytics After completing module 5, students will be able to: Describe big data engineering with Apache Spark in Azure Synapse Analytics Ingest data with Apache Spark notebooks in Azure Synapse Analytics Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics Integrate SQL and Apache Spark pools in Azure Synapse Analytics Module 6: Data exploration and transformation in Azure Databricks This module teaches how to use various Apache Spark DataFrame methods to explore and transform data in Azure Databricks. The student will learn how to perform standard DataFrame methods to explore and transform data. They will also learn how to perform more advanced tasks, such as removing duplicate data, manipulate date/time values, rename columns, and aggregate data. Describe Azure Databricks Read and write data in Azure Databricks Work with DataFrames in Azure Databricks Work with DataFrames advanced methods in Azure Databricks Lab 6: Data Exploration and Transformation in Azure Databricks Use DataFrames in Azure Databricks to explore and filter data Cache a DataFrame for faster subsequent queries Remove duplicate data Manipulate date/time values Remove and rename DataFrame columns Aggregate data stored in a DataFrame After completing module 6, students will be able to: Describe Azure Databricks Read and write data in Azure Databricks Work with DataFrames in Azure Databricks Work with DataFrames advanced methods in Azure Databricks Module 7: Ingest and load data into the data warehouse This module teaches students how to ingest data into the data warehouse through T-SQL scripts and Synapse Analytics integration pipelines. The student will learn how to load data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. The student will also learn how to use workload management along with a Copy activity in a Azure Synapse pipeline for petabyte-scale data ingestion. Use data loading best practices in Azure Synapse Analytics Petabyte-scale ingestion with Azure Data Factory Lab 7: Ingest and load Data into the Data Warehouse Perform petabyte-scale ingestion with Azure Synapse Pipelines Import data with PolyBase and COPY using T-SQL Use data loading best practices in Azure Synapse Analytics After completing module 7, students will be able to: Use data loading best practices in Azure Synapse Analytics Petabyte-scale ingestion with Azure Data Factory Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines This module teaches students how to build data integration pipelines to ingest from multiple data sources, transform data using mapping data flowss, and perform data movement into one or more data sinks. Data integration with Azure Data Factory or Azure Synapse Pipelines Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines Lab 8: Transform Data with Azure Data Factory or Azure Synapse Pipelines Execute code-free transformations at scale with Azure Synapse Pipelines Create data pipeline to import poorly formatted CSV files Create Mapping Data Flows After completing module 8, students will be able to: Perform data integration with Azure Data Factory Perform code-free transformation at scale with Azure Data Factory Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines. Orchestrate data movement and transformation in Azure Data Factory Lab 9: Orchestrate data movement and transformation in Azure Synapse Pipelines Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines After completing module 9, students will be able to: Orchestrate data movement and transformation in Azure Synapse Pipelines Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse In this module, students will learn strategies to optimize data storage and processing when using dedicated SQL pools in Azure Synapse Analytics. The student will know how to use developer features, such as windowing and HyperLogLog functions, use data loading best practices, and optimize and improve query performance. Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics Lab 10: Optimize Query Performance with Dedicated SQL Pools in Azure Synapse Understand developer features of Azure Synapse Analytics Optimize data warehouse query performance in Azure Synapse Analytics Improve query performance After completing module 10, students will be able to: Optimize data warehouse query performance in Azure Synapse Analytics Understand data warehouse developer features of Azure Synapse Analytics Module 11: Analyze and Optimize Data Warehouse Storage In this module, students will learn how to analyze then optimize the data storage of the Azure Synapse dedicated SQL pools. The student will know techniques to understand table space usage and column store storage details. Next the student will know how to compare storage requirements between identical tables that use different data types. Finally, the student will observe the impact materialized views have when executed in place of complex queries and learn how to avoid extensive logging by optimizing delete operations. Analyze and optimize data warehouse storage in Azure Synapse Analytics Lab 11: Analyze and Optimize Data Warehouse Storage Check for skewed data and space usage Understand column store storage details Study the impact of materialized views Explore rules for minimally logged operations After completing module 11, students will be able to: Analyze and optimize data warehouse storage in Azure Synapse Analytics Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link In this module, students will learn how Azure Synapse Link enables seamless connectivity of an Azure Cosmos DB account to a Synapse workspace. The student will understand how to enable and configure Synapse link, then how to query the Azure Cosmos DB analytical store using Apache Spark and SQL serverless. Design hybrid transactional and analytical processing using Azure Synapse Analytics Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark pools Query Azure Cosmos DB with serverless SQL pools Lab 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark for Synapse Analytics Query Azure Cosmos DB with serverless SQL pool for Azure Synapse Analytics After completing module 12, students will be able to: Design hybrid transactional and analytical processing using Azure Synapse Analytics Configure Azure Synapse Link with Azure Cosmos DB Query Azure Cosmos DB with Apache Spark for Azure Synapse Analytics Query Azure Cosmos DB with SQL serverless for Azure Synapse Analytics Module 13: End-to-end security with Azure Synapse Analytics In this module, students will learn how to secure a Synapse Analytics workspace and its supporting infrastructure. The student will observe the SQL Active Directory Admin, manage IP firewall rules, manage secrets with Azure Key Vault and access those secrets through a Key Vault linked service and pipeline activities. The student will understand how to implement column-level security, row-level security, and dynamic data masking when using dedicated SQL pools. Secure a data warehouse in Azure Synapse Analytics Configure and manage secrets in Azure Key Vault Implement compliance controls for sensitive data Lab 13: End-to-end security with Azure Synapse Analytics Secure Azure Synapse Analytics supporting infrastructure Secure the Azure Synapse Analytics workspace and managed services Secure Azure Synapse Analytics workspace data After completing module 13, students will be able to: Secure a data warehouse in Azure Synapse Analytics Configure and manage secrets in Azure Key Vault Implement compliance controls for sensitive data Module 14: Real-time Stream Processing with Stream Analytics In this module, students will learn how to process streaming data with Azure Stream Analytics. The student will ingest vehicle telemetry data into Event Hubs, then process that data in real time, using various windowing functions in Azure Stream Analytics. They will output the data to Azure Synapse Analytics. Finally, the student will learn how to scale the Stream Analytics job to increase throughput. Enable reliable messaging for Big Data applications using Azure Event Hubs Work with data streams by using Azure Stream Analytics Ingest data streams with Azure Stream Analytics Lab 14: Real-time Stream Processing with Stream Analytics Use Stream Analytics to process real-time data from Event Hubs Use Stream Analytics windowing functions to build aggregates and output to Synapse Analytics Scale the Azure Stream Analytics job to increase throughput through partitioning Repartition the stream input to optimize parallelization After completing module 14, students will be able to: Enable reliable messaging for Big Data applications using Azure Event Hubs Work with data streams by using Azure Stream Analytics Ingest data streams with Azure Stream Analytics Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks In this module, students will learn how to ingest and process streaming data at scale with Event Hubs and Spark Structured Streaming in Azure Databricks. The student will learn the key features and uses of Structured Streaming. The student will implement sliding windows to aggregate over chunks of data and apply watermarking to remove stale data. Finally, the student will connect to Event Hubs to read and write streams. Process streaming data with Azure Databricks structured streaming Lab 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks Explore key features and uses of Structured Streaming Stream data from a file and write it out to a distributed file system Use sliding windows to aggregate over chunks of data rather than all data Apply watermarking to remove stale data Connect to Event Hubs read and write streams After completing module 15, students will be able to: Process streaming data with Azure Databricks structured streaming Module 16: Build reports using Power BI integration with Azure Synpase Analytics In this module, the student will learn how to integrate Power BI with their Synapse workspace to build reports in Power BI. The student will create a new data source and Power BI report in Synapse Studio. Then the student will learn how to improve query performance with materialized views and result-set caching. Finally, the student will explore the data lake with serverless SQL pools and create visualizations against that data in Power BI. Create reports with Power BI using its integration with Azure Synapse Analytics Lab 16: Build reports using Power BI integration with Azure Synpase Analytics Integrate an Azure Synapse workspace and Power BI Optimize integration with Power BI Improve query performance with materialized views and result-set caching Visualize data with SQL serverless and create a Power BI report After completing module 16, students will be able to: Create reports with Power BI using its integration with Azure Synapse Analytics Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics This module explores the integrated, end-to-end Azure Machine Learning and Azure Cognitive Services experience in Azure Synapse Analytics. You will learn how to connect an Azure Synapse Analytics workspace to an Azure Machine Learning workspace using a Linked Service and then trigger an Automated ML experiment that uses data from a Spark table. You will also learn how to use trained models from Azure Machine Learning or Azure Cognitive Services to enrich data in a SQL pool table and then serve prediction results using Power BI. Use the integrated machine learning process in Azure Synapse Analytics Lab 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics Create an Azure Machine Learning linked service Trigger an Auto ML experiment using data from a Spark table Enrich data using trained models Serve prediction results using Power BI After completing module 17, students will be able to: Use the integrated machine learning process in Azure Synapse Analytics     [-]