Oversikt over relevante kurs innen IT-kurs i Krokom

Understand the purpose and key concepts of the Service Level Management Practice, elucidating its significance in defining, negotiating, and managing service levels to meet customer expectations. This eLearning is: Interactive Self-paced   Device-friendly   2-3 hours content   Mobile-optimised   Practical exercises   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]

Understand the key concepts of Relationship Management, Supplier Management, Service Level Management, Continual Improvement, and Information Security Management, elucidating their significance in fostering collaboration, ensuring service quality, driving continual improvement, and maintaining information security. This eLearning is: Interactive Self-paced   Device-friendly   12 hours content   Mobile-optimised   Practical exercises   Exam: 60 questions Multiple choise 90 minutes Closed book Minimum required score to pass: 65% [-]

AZ-1008: Administer Active Directory Domain Services [-]

Understand the purpose and key concepts of the Service Desk practice, including how it serves as the central point of contact between the service provider and the users, facilitating effective communication. This eLearning is: Interactive Self-paced Device-friendly 2-3 hours content mobil-optimised practical exercises     Exam: 20 questions Multiple Choice 30 minutes Closed book Minimum required score to pass: (65%)   [-]

Understand the purpose and key concepts of the Continual Improvement Practice, elucidating its significance in fostering a culture of ongoing improvement and innovation within the organisation. This eLearning is: Interactive Self-paced   Device-friendly   2-3 hours content   Mobile-optimised   Practical exercises   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]

Understand the purpose and key concepts of Service Configuration Management, including its role in maintaining accurate and reliable information about configuration items (CIs) within the IT infrastructure. This eLearning is: Interactive Self-paced Device-friendly 2-3 hours content Mobile-optimised Practical exercises   Exam: 20 questions Multiple Choice 30 Minutes Closed book Pass Mark: 65% [-]

Understand the purpose and key concepts of Deployment Management, highlighting its importance in managing the deployment of new or changed services into the live environment. This eLearning is: Interactive Self-paced   Device-friendly   2-3 hours of content   Mobile-optimised   Exam: 20 questions Multiple choise 30 minutes Closed book Minimum required score to pass: 65% [-]

Excelkurs Basis - elæringskurs [-]

Kursinstruktør Terje Berg-Hansen Terje Berg-Hansen har bred erfaring fra prosjektledelse, utvikling og drift med små og store databaser, både SQL- og NoSQL-baserte. I tillegg til å undervise i etablerte teknologier leder han også Oslo Hadoop User Group, og er levende interessert i nye teknologier, distribuerte databaser og Big Data Science.    Kursinnhold XML er en moden standard for å utveksle informasjon mellom applikasjoner. Med XML og relaterte standarder som XSL(T) og XQuery er det mulig å utvikle distribuerte nettbaserte tjenester for utveksling av data i et standardisert format.    Målsetting Deltakerne vil etter kurset ha en grunnleggende forståelse av og kjennskap til hvorfor og hvordan XML kan anvendes for å oppnå en bedre utveksling og deling av strukturert og ustrukturert informasjon.   Forkunnskaper Grunnleggende kunnskaper om internett, HTML og CSS er en fordel, men ikke nødvendig for å ta dette kurset.   Kursinnhold Introduksjon Introduksjon til XML og XML-relaterte teknologier, som XPath, XQuery og XSL XML-verktøy Editorer og verktøy for validering, søk og endring av XML Grunnleggende XML XML struktur og syntaks. Gjennomgang av målene for XML. Lage og utforme XML dokumenter Navnerom (namespaces) Oppretting og bruk av navnerom for å skille elementer og funksjoner med samme navn. Validering av  XML Gjennomgang av teknologier som Document Type Definitions (DTD's) og XML Schemas for å kontrollere og styre struktur og data i XML filer Presentasjon av XML Bruk av html og CSS til å presentere XML data Søking i XML Søk i XML-dokumenter med XPath . Introduksjon til XSL(T) Kort om XSL og XSL Transformations. Bruk av XSLT til å formatere, sortere, filtrere og konvertere XML Data   Gjennomføring Kurset gjennomføres med en kombinasjon av online læremidler, gjennomgang av temaer og problemstillinger og praktiske øvelser. Det er ingen avsluttende eksamen, men det er øvelsesoppgaver til hovedtemaene som gjennomgås.   [-]

COURSE OVERVIEW These professionals manage and support an infrastructure that includes on-premises and Azure IaaS-hosted Windows Server-based workloads. The course teaches IT professionals how to leverage the hybrid capabilities of Azure, how to migrate virtual and physical server workloads to Azure IaaS, and how to manage and secure Azure VMs running Windows Server. The course also covers how to perform tasks related to high availability, troubleshooting, and disaster recovery. The course highlights various administrative tools and technologies including Windows Admin Center, PowerShell, Azure Arc, Azure Automation Update Management, Microsoft Defender for Identity, Azure Security Center, Azure Migrate, and Azure Monitor. TARGET AUDIENCE This four-day course is intended for Windows Server Hybrid Administrators who have experience working with Windows Server and want to extend the capabilities of their on-premises environments by combining on-premises and hybrid technologies. Windows Server Hybrid Administrators who already implement and manage on-premises core technologies want to secure and protect their environments, migrate virtual and physical workloads to Azure Iaas, enable a highly available, fully redundant environment, and perform monitoring and troubleshooting. COURSE OBJECTIVES After you complete this course you will be able to: Harden the security configuration of the Windows Server operating system environment. Enhance hybrid security using Azure Security Center, Azure Sentinel, and Windows Update Management. Apply security features to protect critical resources. Implement high availability and disaster recovery solutions. Implement recovery services in hybrid scenarios. Plan and implement hybrid and cloud-only migration, backup, and recovery scenarios. Perform upgrades and migration related to AD DS, and storage. Manage and monitor hybrid scenarios using WAC, Azure Arc, Azure Automation and Azure Monitor. Implement service monitoring and performance monitoring, and apply troubleshooting. COURSE CONTENT Module 1: Windows Server security This module discusses how to protect an Active Directory environment by securing user accounts to least privilege and placing them in the Protected Users group. The module covers how to limit authentication scope and remediate potentially insecure accounts. The module also describes how to harden the security configuration of a Windows Server operating system environment. In addition, the module discusses the use of Windows Server Update Services to deploy operating system updates to computers on the network. Finally, the module covers how to secure Windows Server DNS to help protect the network name resolution infrastructure. Lessons for module 1 Secure Windows Sever user accounts Hardening Windows Server Windows Server Update Management Secure Windows Server DNS Lab : Configuring security in Windows Server Configuring Windows Defender Credential Guard Locating problematic accounts Implementing LAPS After completing module 1, students will be able to: Diagnose and remediate potential security vulnerabilities in Windows Server resources. Harden the security configuration of the Windows Server operating system environment. Deploy operating system updates to computers on a network by using Windows Server Update Services. Secure Windows Server DNS to help protect the network name resolution infrastructure. Implement DNS policies. Module 2: Implementing security solutions in hybrid scenarios This module describes how to secure on-premises Windows Server resources and Azure IaaS workloads. The module covers how to improve the network security for Windows Server infrastructure as a service (IaaS) virtual machines (VMs) and how to diagnose network security issues with those VMs. In addition, the module introduces Azure Security Center and explains how to onboard Windows Server computers to Security Center. The module also describes how to enable Azure Update Management, deploy updates, review an update assessment, and manage updates for Azure VMs. The modules explains how Adaptive application controls and BitLocker disk encryption are used to protect Windows Server IaaS VMs. Finally, the module explains how to monitor Windows Server Azure IaaS VMs for changes in files and the registry, as well as monitoring modifications made to application software. Lessons for module 2 Implement Windows Server IaaS VM network security. Audit the security of Windows Server IaaS Virtual Machines Manage Azure updates Create and implement application allowlists with adaptive application control Configure BitLocker disk encryption for Windows IaaS Virtual Machines Implement change tracking and file integrity monitoring for Windows Server IaaS VMs Lab : Using Azure Security Center in hybrid scenarios Provisioning Azure VMs running Windows Server Configuring Azure Security Center Onboarding on-premises Windows Server into Azure Security Center Verifying the hybrid capabilities of Azure Security Center Configuring Windows Server 2019 security in Azure VMs After completing module 2, students will be able to: Diagnose network security issues in Windows Server IaaS virtual machines. Onboard Windows Server computers to Azure Security Center. Deploy and manage updates for Azure VMs by enabling Azure Automation Update Management. Implement Adaptive application controls to protect Windows Server IaaS VMs. Configure Azure Disk Encryption for Windows IaaS virtual machines (VMs). Back up and recover encrypted data. Monitor Windows Server Azure IaaS VMs for changes in files and the registry. Module 3: Implementing high availability This module describes technologies and options to create a highly available Windows Server environment. The module introduces Clustered Shared Volumes for shared storage access across multiple cluster nodes. The module also highlights failover clustering, stretch clusters, and cluster sets for implementing high availability of Windows Server workloads. The module then discusses high availability provisions for Hyper-V and Windows Server VMs, such as network load balancing, live migration, and storage migration. The module also covers high availability options for shares hosted on Windows Server file servers. Finally, the module describes how to implement scaling for virtual machine scale sets and load-balanced VMs, and how to implement Azure Site Recovery. Lessons for module 3 Introduction to Cluster Shared Volumes. Implement Windows Server failover clustering. Implement high availability of Windows Server VMs. Implement Windows Server File Server high availability. Implement scale and high availability with Windows Server VMs. Lab : Implementing failover clustering Configuring iSCSI storage Configuring a failover cluster Deploying and configuring a highly available file server Validating the deployment of the highly available file server After completing module 3, students will be able to: Implement highly available storage volumes by using Clustered Share Volumes. Implement highly available Windows Server workloads using failover clustering. Describe Hyper-V VMs load balancing. Implement Hyper-V VMs live migration and Hyper-V VMs storage migration. Describe Windows Server File Server high availablity options. Implement scaling for virtual machine scale sets and load-balanced VMs. Implement Azure Site Recovery. Module 4: Disaster recovery in Windows Server This module introduces Hyper-V Replica as a business continuity and disaster recovery solution for a virtual environment. The module discusses Hyper-V Replica scenarios and use cases, and prerequisites to use it. The module also discusses how to implement Azure Site Recovery in on-premises scenarios to recover from disasters. Lessons for module 4 Implement Hyper-V Replica Protect your on-premises infrastructure from disasters with Azure Site Recovery Lab : Implementing Hyper-V Replica and Windows Server Backup Implementing Hyper-V Replica Implementing backup and restore with Windows Server Backup After completing module 4, students will be able to: Describe Hyper-V Replica, pre-requisites for its use, and its high-level architecture and components Describe Hyper-V Replica use cases and security considerations. Configure Hyper-V Replica settings, health monitoring, and failover options. Describe extended replication. Replicate, failover, and failback virtual machines and physical servers with Azure Site Recovery. Module 5: Implementing recovery services in hybrid scenarios This module covers tools and technologies for implementing disaster recovery in hybrid scenarios, whereas the previous module focus on BCDR solutions for on-premises scenarios. The module begins with Azure Backup as a service to protect files and folders before highlighting how to implementRecovery Vaults and Azure Backup Policies. The module describes how to recover Windows IaaS virtual machines, perform backup and restore of on-premises workloads, and manage Azure VM backups. The modules also covers how to provide disaster recovery for Azure infrastructure by managing and orchestrating replication, failover, and failback of Azure virtual machines with Azure Site Recovery. Lessons for module 5 Implement hybrid backup and recovery with Windows Server IaaS Protect your Azure infrastructure with Azure Site Recovery Protect your virtual machines by using Azure Backup Lab : Implementing Azure-based recovery services Implementing the lab environment Creating and configuring an Azure Site Recovery vault Implementing Hyper-V VM protection by using Azure Site Recovery vault Implementing Azure Backup After completing module 5, students will be able to: Recover Windows Server IaaS virtual machines by using Azure Backup. Use Azure Backup to help protect the data for on-premises servers and virtualized workloads. Implement Recovery Vaults and Azure Backup policies. Protect Azure VMs with Azure Site Recovery. Run a disaster recovery drill to validate protection. Failover and failback Azure virtual machines. Module 6: Upgrade and migrate in Windows Server This module discusses approaches to migrating Windows Server workloads running in earlier versions of Windows Server to more current versions. The module covers the necessary strategies needed to move domain controllers to Windows Server 2022 and describes how the Active Directory Migration Tool can consolidate domains within a forest or migrate domains to a new AD DS forest. The module also discusses the use of Storage Migration Service to migrate files and files shares from existing file servers to new servers running Windows Server 2022. Finally, the module covers how to install and use the Windows Server Migration Tools cmdlets to migrate commonly used server roles from earlier versions of Windows Server. Lessons for module 6 Active Directory Domain Services migration Migrate file server workloads using Storage Migration Service Migrate Windows Server roles Lab : Migrating Windows Server workloads to IaaS VMs Deploying AD DS domain controllers in Azure Migrating file server shares by using Storage Migration Service After completing module 6, students will be able to: Compare upgrading an AD DS forest and migrating to a new AD DS forest. Describe the Active Directory Migration Tool (ADMT). Identify the requirements and considerations for using Storage Migration Service. Describe how to migrate a server with storage migration. Use the Windows Server Migration Tools to migrate specific Windows Server roles. Module 7: Implementing migration in hybrid scenarios This module discusses approaches to migrating workloads running in Windows Server to an infrastructure as a service (IaaS) virtual machine. The module introduces using Azure Migrate to assess and migrate on-premises Windows Server instances to Microsoft Azure. The module also covers how migrate a workload running in Windows Server to an infrastructure as a service (IaaS) virtual machine (VM) and to Windows Server 2022 by using Windows Server migration tools or the Storage Migration Service. Finally, this module describes how to use the Azure Migrate App Containerization tool to containerize and migrate ASP.NET applications to Azure App Service. Lessons for module 7 Migrate on-premises Windows Server instances to Azure IaaS virtual machines Upgrade and migrate Windows Server IaaS virtual machines Containerize and migrate ASP.NET applications to Azure App Service Lab : Migrating on-premises VMs servers to IaaS VMs Implementing assessment and discovery of Hyper-V VMs using Azure Migrate Implementing migration of Hyper-V workloads using Azure Migrate After completing module 7, students will be able to: Plan a migration strategy and choose the appropriate migration tools. Perform server assessment and discovery using Azure Migrate. Migrate Windows Server workloads to Azure VM workloads using Azure Migrate. Explain how to migrate workloads using Windows Server Migration tools. Migrate file servers by using the Storage Migration Service. Discover and containerize ASP.NET applcations running on Windows. Migrate a containerized application to Azure App Service. Module 8: Server and performance monitoring in Windows Server This module introduces a range of tools to monitor the operating system and applications on a Windows Server computer as well as describing how to configure a system to optimize efficiency and to troublshoot problems. The module covers how Event Viewer provides a convenient and accessible location for observing events that occur, and how to interpret the data in the event log. The module also covers how to audit and diagnose a Windows Server environment for regulatory compliance, user activity, and troubleshooting. Finally, the module explains how to troubleshoot AD DS service failures or degraded performance, including recovery of deleted objects and the AD DS database, and how to troubleshoot hybrid authentication issues. Lessons for module 8 Monitor Windows Server performance Manage and monitor Windows Server event logs Implement Windows Server auditing and diagnostics Troubleshoot Active Directory Lab : Monitoring and troubleshooting Windows Server Establishing a performance baseline Identifying the source of a performance problem Viewing and configuring centralized event logs After completing module 8, students will be able to: Explain the fundamentals of server performance tuning. Use built-in tools in Windows Server to monitor server performance. Use Server Manager and Windows Admin Center to review event logs. Implement custom views. Configure an event subscription. Audit Windows Server events. Configure Windows Server to record diagnostic information. Recover the AD DS database and objects in AD DS. Troubleshoot AD DS replication. Troubleshoot hybrid authentication issues. Module 9: Implementing operational monitoring in hybrid scenarios This module covers using monitoring and troubleshooing tools, processes, and best practices to streamline app performance and availabilty of Windows Server IaaS VMs and hybrid instances. The module describes how to implement Azure Monitor for IaaS VMs in Azure, implement Azure Monitor in on-premises environments, and use dependency maps. The module then explains how to enable diagnostics to get data about a VM, and how to view VM metrics in Azure Metrics Explorer, and how to create a metric alert to monitor VM performance. The module then covers how to monitor VM performance by using Azure Monitor VM Insights. The module then describes various aspects of troubleshooting on premises and hybrid network connectivity, including how to diagnose common issues with DHCP, name resolution, IP configuration, and routing. Finally, the module examines how to troubleshoot configuration issues that impact connectivity to Azure-hosted Windows Server virtual machines (VMs), as well as approaches to resolve issues with VM startup, extensions, performance, storage, and encryption. Lessons for module 9 Monitor Windows Server IaaS Virtual Machines and hybrid instances Monitor the health of your Azure virtual machines by using Azure Metrics Explorer and metric alerts Monitor performance of virtual machines by using Azure Monitor VM Insights Troubleshoot on-premises and hybrid networking Troubleshoot Windows Server Virtual Machines in Azure Lab : Monitoring and troubleshooting of IaaS VMs running Windows Server Enabling Azure Monitor for virtual machines Setting up a VM with boot diagnostics Setting up a Log Analytics workspace and Azure Monitor VM Insights After completing module 9, students will be able to: Implement Azure Monitor for IaaS VMs in Azure and in on-premises environments. Implement Azure Monitor for IaaS VMs in Azure and in on-premises environments. View VM metrics in Azure Metrics Explorer. Use monitoring data to diagnose problems. Evaluate Azure Monitor Logs and configure Azure Monitor VM Insights. Configure a Log Analytics workspace. Troubleshoot on-premises connectivity and hybrid network connectivity. Troubleshoot AD DS service failures or degraded performance. Recover deleted security objects and the AD DS database. Troubleshoot hybrid authentication issues. [-]

Dette kurset tilbys som bedriftsinternt kurs   Fra mars 2020 til oktober 2020 økte antall daglige teams-brukere på verdensbasis fra 44 millioner til 115 millioner. Dette er en enorm økning og for mange innebar det å bli kastet inn i noe nytt uten opplæring. Det som egentlig skulle gjøre arbeidsdagen lettere, lagde flere utfordringer.  Appen er brukervennlig og fungerer sømløst med de andre verktøyene i Microsoft 365, men appen vokser ettersom behovene endrer seg, og med 115 millioner brukere er behovene også mange. Microsoft Teams er derfor et stort verktøy for god og effektiv samhandling, men verktøyene kan være så gode de bare vil – dersom de som bruker det ikke er kjent med funksjonalitetene som gjør Microsoft sømløst. I løpet av kurset vil deltagere få en god oversikt på hva Teams er, hva det kan brukes for, og hvordan best mulig bruke det. Kurset gir også tips og triks for best practice, samt hvordan man kan holde seg oppdatert på ny funksjonalitet som kommer.    Metode: Digitalkurs: Kursholder holder informative økter med gjennomgang og demonstrasjoner av de viktigste verktøyene, hvordan de virker sammen, og hvordan du og dine kollegaer bruker de effektivt sammen. Kursdeltakerne vil ha mulighet til å stille spørsmål, enten muntlig eller skriftlig, avhengig av gruppestørrelsen.    Kurs på Bouvethuset på Majorstuen: Kursholdere vil bruke en kombinasjon av undervisning, demonstrasjoner og øvelser så deltagerne kan raskt komme i gang og samtidig bygge en bevisst og robust tilnærming til verktøyet. Deltagkerne får da mulighet til å teste ut funksjonalitet underveis i Bouvet sitt kursmiljø.    Målgruppe Alle som ønsker en grundig introduksjon og opplæring i Teams applikasjonen. Det passer både for deg som aldri har brukt Teams før, og for deg som ønsker å utvikle deg til superbruker. Spesielt egnet for deg som skal være med å spesifisere, tilrettelegge eller være ansvarlig for innføring av samhandlingsløsninger.   Kursinnhold •    Teams som del av Office 365 plattformen•    Oversikt over begreper, lisensmodeller og relatert•    Pålogging, navigasjon og grensesnitt i Teams•    Hvordan strukturere velfungerende Teams: kanaler, faner, og mer•    Fillagring og fildeling•    Samtaler, chat og virtuelle møter•    Samtidig redigering•    Beste praksiser, tips og triks•    Innstillinger og sikkerhet•    Administrasjon for Teams eiere•    Kontinuerlig læring i bruk av verktøyet•    Samhandlingsstrategier   [-]

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. After completing this course, students will be able to: 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 prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.Recommended prerequisites:M-DP900 - Microsoft Azure Data FundamentalsM-AZ900 - Microsoft Azure Fundamentals Agenda 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. 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. 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. 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). 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Module 16: Build reports using Power BI integration with Azure Synapase 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. 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. [-]

Bruker du mye tid i Excel på å få gjort enkle arbeidsoppgaver? Kommer det til stadighet prosent og dato i celler hvor du vil ha vanlige tall? Blir en formel ødelagt når du flytter den? Er det vanskelig å lage det diagrammet du ønsker? Blir ikke utskriftene dine slik du ønsker? Dette er vanlige problemstillinger mange sliter med og som blir borte etter endt kurs! På kun 2 dager vil du mestre de vanligste formler og funksjoner du trenger i din arbeidsdag. Du lærer gode rutiner og hurtigtastene du trenger for å kunne arbeide raskt og effektivt. Du vil kunne bygge alt fra enkle til mer avanserte modeller og vil føle deg trygg på at modellen din virker og gir rett resultat. Du vil også få en rekke tips og triks du kan bruke i din arbeidsdag.  Alt du lærer får du repetert gjennom aktiv oppgaveløsning slik at du husker det du har lært når du kommer tilbake på jobb. Kursdokumentasjon, lunsj og pausemat er selvsagt inkludert!   Kursholderne har mer enn 20 års Excel erfaring som de gjerne deler med deg!   Kurset passer for deg med liten erfaring og som ønsker å lære Excel fra grunnen av. Kurset passer også for deg som er selvlært og som ønsker å jobbe mer effektivt. Meld deg på Excel-kurs allerede i dag og sikre deg plass!   Krav til forkunnskaper Grunnleggende kunnskaper i Windows.   Kursinnhold Redigering Merking Sletting Angre muligheter Flytting og kopiering Innsetting og sletting Formler Bruk av formler Autofyll Cellereferanser Formatering Hva er formatering? Kolonnebredde og radhøyde Tallformatering Skriftformatering Justering av celleinnhold Kantlinjer og fyllfarger Betinget formatering Funksjoner Bruk av funksjoner Summering Minst, størst, antall og gjennomsnitt Hvis-funksjonen Betinget summering Diagram Utforming av diagram Diagramtyper Flere regneark Arbeid med regneark Innsetting og sletting av regneark Flytting og kopiering av regneark Referering til andre regneark Enkle formler på tvers av ark Vindus håndtering Lister og tabeller Sortering Tabeller Filtrering Deling og frysing av vindu   [-]

The course is designed for Azure system administrators, solutions architects, and SysOps administrators who are familiar with Azure features and setup and want to gain experience configuring Google Cloud products immediately.  This course uses lectures, demos, and hands-on labs to show you the similarities and differences between the two platforms and teach you about some basic tasks on Google Cloud. Objectives This course teaches participants the following skills: Identify Google Cloud counterparts for Azure IaaS, Azure PaaS, Azure SQL, Azure Blob Storage, Azure Application Insights, and Azure Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto-scaling, load balancing, storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences All courses will be delivered in partnership with ROI Training, Google Cloud Premier Partner, using a Google Authorized Trainer. Course Outline Module 1: Introducing Google Cloud -Explain the advantages of Google Cloud-Define the components of Google’s network infrastructure, including points of presence, data centers, regions, and zones-Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) Module 2: Getting Started with Google Cloud -Identify the purpose of projects on Google Cloud-Understand how Azure’s resource hierarchy differs from Google Cloud’s-Understand the purpose of and use cases for Identity and Access Management-Understand how Azure AD differs from Google Cloud IAM-List the methods of interacting with Google Cloud-Launch a solution using Cloud Marketplace Module 3: Virtual Machines in the Cloud -Identify the purpose and use cases for Google Compute Engine-Understand the basics of networking in Google Cloud-Understand how Azure VPC differs from Google VPC-Understand the similarities and differences between Azure VM and Google Compute Engine-Understand how typical approaches to load-balancing in Google Cloud differ from those in AzureDeploy applications using Google Compute Engine Module 4: Storage in the Cloud -Understand the purpose of and use cases for: Cloud Storage, Cloud SQL, Cloud Bigtable and Cloud Datastore-Understand how Azure Blob compares to Cloud Storage-Compare Google Cloud’s managed database services with Azure SQL-Learn how to choose among the various storage options on Google Cloud-Load data from Cloud Storage into BigQuery Module 5: Containers in the Cloud -Define the concept of a container and identify uses for containers-Identify the purpose of and use cases for Google Container Engine and Kubernetes-Understand how Azure Kubernetes Service differs from Google Kubernetes Engine-Provision a Kubernetes cluster using Kubernetes Engine-Deploy and manage Docker containers using kubectl Module 6: Applications in the Cloud -Understand the purpose of and use cases for Google App Engine-Contrast the App Engine Standard environment with the App Engine Flexible environment-Understand how App Engine differs from Azure App Service-Understand the purpose of and use cases for Google Cloud Endpoints Module 7: Developing, Deploying and Monitoring in the Cloud -Understand options for software developers to host their source code-Understand the purpose of template-based creation and management of resources-Understand how Cloud Deployment Manager differs from Azure Resource Manager-Understand the purpose of integrated monitoring, alerting, and debugging-Understand how Google Monitoring differs from Azure Application Insights and Azure Log Analytics-Create a Deployment Manager deployment-Update a Deployment Manager deployment-View the load on a VM instance using Google Monitoring Module 8: Big Data and Machine Learning in the Cloud -Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms-Understand how Google Cloud BigQuery differs from Azure Data Lake-Understand how Google Cloud Pub/Sub differs from Azure Event Hubs and Service Bus-Understand how Google Cloud’s machine-learning APIs differ from Azure’s-Load data into BigQuery from Cloud Storage-Perform queries using BigQuery to gain insight into data Module 9: Summary and Review -Review the products that make up Google Cloud and remember how to choose among them-Understand next steps for training and certification-Understand, at a high level, the process of migrating from Azure to Google Cloud [-]

Splunk Enterprise System Administration [-]