Oversikt over relevante kurs innen Kurs i programvare og applikasjoner i Inderøy

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

Instruktørbasert opplæring:   PowerPoint nivå 4 - Utvikling av maler Lysbildemal Generelt om maloppsettet Flere lysbildemaler i samme presentasjon Definere temafarger Bytte lysbildemal i en presentasjon Gjøre maler tilgjengelig for "alle" Lysbildeoppsett Tilpasse eksisterende oppsett Lage egendefinerte lysbildeoppsett Kontrollere rekkefølgen på plassholdere   3 gode grunner til å delta 1. Få forståelse av hvordan malen fungerer 2. Lær hvordan temafarger styrer utseende 3. Se hvordan du kan tilpasse lysbildeoppsett, og hvordan lage egne [-]

MB-220: Dynamics 365 Customer Insights - Journeys [-]

Dette kurset er skreddersydd for deltakere som allerede har fullført vårt grunnleggende Excel-kurs og nå ønsker å ta sine ferdigheter til et avansert nivå. Kursinstruktør Espen Faugstad vil veilede deg gjennom en rekke avanserte emner, inkludert opprettelse av pivottabeller, bruk av funksjoner og formler, og mye mer. Kurset dekker grundig bruken av en rekke funksjoner og formler, inkludert SUMMER, MIN, MAKS, AVKORT, AVRUND, ANTALL, ANTALLA, KJEDE.SAMMEN, TRIMME, VENSTRE, HØYRE, DELTEKST, FINN.RAD, HVIS, SUMMERHVIS, ANTALL.HVIS og GJENNOMSNITTHVIS. I tillegg vil kurset veilede deg gjennom henting av ekstern data, sortering og filtrering, fjerning av duplikater, og gruppering av data.   Innhold: Kapittel 1: Pivottabeller Kapittel 2: Formler og Funksjoner Kapittel 3: Formelrevisjon Kapittel 4: Ekstern Data Kapittel 5: Sortering og Filtrering Kapittel 6: Dataverktøy Kapittel 7: Gruppering av Data Kapittel 8: Arkbeskyttelse Kapittel 9: Avslutning   Varighet: 2 timer og 17 minutter   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Vår tjeneste fungerer på samme måte som strømmetjenester for musikk eller TV-serier, der våre kunder betaler en fast månedspris for tilgang til alle kursene vi har tilgjengelig. Vi har opplevd betydelig vekst de siste årene, med over 30 000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling engasjerende, spennende og tilgjengelig for alle, og vi har støtte fra Innovasjon Norge og Forskningsrådet. [-]

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. Fusion 360 Her er et utvalg av temaene du vil lære på kurset: Fusion 360 Dashboard - Data og prosjekthåndtering Formgivning - konseptuelt design og parametrisk Samlinger og 2D-tegninger, inkludert stykklister  Dataimport - håndtering av data fra andre CAD-plattformer Kurset for deg som er industriell designer, arbeider med produktdesign eller annen kompleks forgivning. Kurset har fokus på oppbygning av modeller med kompliserte overflater. Du vil få kunnskap til å skape og korrigere avanserte og komplekse 3D-modeller, og samtidig lage avanserte 3D-modeller på bakgrunn av konseptuelle skisser, vedlikeholde og dokumentere dem i forskjellige varianter.    Dette er et populært kurs, meld deg på nå! 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@nticad.no eller les mer på www.nticad.no [-]

God formatering i Microsoft Excel handler ikke bare om å få et regneark til å se pent ut; det handler like mye om å kommunisere effektivt. Et dårlig formatert regneark kan gjøre det vanskelig å lese og forstå innholdet. Derimot vil et godt formatert regneark gjøre det enklere å absorbere informasjonen som presenteres. Dette kurset, ledet av Espen Faugstad, vil gi deg ferdighetene du trenger for å formatere data i Microsoft Excel på avansert nivå. Du vil lære hvordan du gjør regnearket mer leselig, forståelig og effektivt. Emner inkluderer formatering av tekstverdier og tallverdier, opprettelse av egendefinerte formateringsregler, tilpasning av rader, kolonner og celler, formatering av tabeller, diagrammer og bilder, og mye mer. Kurset er delt inn i følgende kapitler: Kapittel 1: Introduksjon Kapittel 2: Skrift Kapittel 3: Justering Kapittel 4: Tall Kapittel 5: Stiler Kapittel 6: Celler Kapittel 7: Tabell Kapittel 8: Diagrammer Kapittel 9: Bilder Kapittel 10: Avslutning Etter å ha fullført kurset, vil du kunne bruke avansert formatering i Excel for å forbedre presentasjonen og lesbarheten av dine regneark, noe som er uvurderlig for effektiv kommunikasjon og dataanalyse.   Varighet: 2 timer og 27 minutter   Om Utdannet.no: Utdannet.no tilbyr noen av landets beste digitale nettkurs. Vår tjeneste fungerer på samme måte som strømmetjenester for musikk eller TV-serier, der våre kunder betaler en fast månedspris for tilgang til alle kursene vi har tilgjengelig. Vi har opplevd betydelig vekst de siste årene, med over 30 000 registrerte brukere og 1,5 millioner videoavspillinger. Vårt mål er å gjøre kompetanseutvikling engasjerende, spennende og tilgjengelig for alle, og vi har støtte fra Innovasjon Norge og Forskningsrådet. [-]

Brukergrensesnittet. Opprette profiler med tilpasset oppsett. Verktøy for digital dokumentbehandling, slik som å sette sammen PDF’er, opprette hyperkoblinger, påføre digitale signaturer og stempler. Redigere innhold i PDF-filer Automatisk sammenligning Markeringsverktøy for bruk under designgjennomgang, etc. Bruk av Tool Chest til å spare symboler og tilpassede verktøy for enkel gjenbruk Bruk av markeringslisten til å sette status, kommentere, filtrere og rapportere Kalibrering og måleverktøy. Intro til mengdeberegning Intro til skybasert samarbeid med Studio Projects og Sessions   På kurset lærer du alle de viktigste funksjonene i Revu, noe som gir deg et godt overblikk og utgangspunkt for å jobbe videre med programmet. Du blir i stand til å digitalisere og effektivisere en rekke manuelle arbeidsprosesser, med tidsbesparelse og bedre kvalitet som resultat.   [-]

 Students will learn through a mix of demonstrations and hands-on lab experiences deploying virtual desktop experiences and apps on Windows Virtual Desktop and optimizing them to run in multi-session virtual environments.Students for AZ-140: Configuring and Operating Windows Virtual Desktop on Microsoft Azure are interested in delivering applications on Windows Virtual Desktop and optimizing them to run in multi-session virtual environments. As a Windows Virtual Desktop administrator, you will closely with the Azure Administrators and Architects, along with Microsoft 365 Administrators. Windows Virtual Desktop administrator responsibilities include planning, deploying, packaging, updating, and maintaining the Azure Windows Virtual Desktop infrastructure. They also create session host images, implement and manage FSLogix, monitor Windows Virtual Desktop performance, and automate Windows Virtual Desktop management tasks. COURSE OBJECTIVES   Select an appropriate licensing model for Windows Virtual Desktop Implement networking for Windows Virtual Desktop Manage Windows Virtual Desktop session hosts by using Azure Bastion Configure storage for FSLogix components Create and manage session host images Implement Azure roles and role-based access control (RBAC) for Windows Virtual Desktop Configure user Windows Virtual Desktop experience settings Install and configure apps on a session host Implement business continuity and disaster recovery Monitor and manage Windows Virtual Desktop performance     COURSE CONTENT Module 1: Plan a Windows Virtual Desktop Architecture In this module, you will learn how to assess existing physical and virtual desktop environments, plan and configure name resolution for Active Directory (AD) and Azure Active Directory Domain Services (Azure AD DS), and plan for Windows Virtual Desktop client deployments. LESSONS M1 Windows Virtual Desktop Architecture Design the WVD architecture Design for user identities and profiles LAB: PREPARE FOR DEPLOYMENT OF AZURE WINDOWS VIRTUAL DESKTOP (AZURE AD DS) LAB: PREPARE FOR DEPLOYMENT OF AZURE WINDOWS VIRTUAL DESKTOP (AD DS) After completing module 1, students will be able to: Understand Windows Virtual Desktop Components Understand personal and pooled desktops Recommend an operating system for a WVD implementation Plan a host pools architecture Module 2: Implement a WVD Infrastructure In this module, you will learn how to manage connectivity to the internet and on-premises networks, create a host pool by using the Azure portal, deploy host pools and hosts by using Azure Resource Manager templates, apply OS and application updates to a running WVD host, and create a master image. LESSONS M2 Implement and manage networking for WVD Implement and manage storage for WVD Create and configure host pools and session hosts Create and manage session host image LAB: CREATE AND CONFIGURE HOST POOLS AND SESSION HOSTS (AZURE AD DS) LAB: DEPLOY HOST POOLS AND SESSION HOSTS BY USING THE AZURE PORTAL (AD DS) LAB: IMPLEMENT AND MANAGE STORAGE FOR WVD (AZURE AD DS) LAB: DEPLOY HOST POOLS AND HOSTS BY USING AZURE RESOURCE MANAGER TEMPLATES LAB: DEPLOY AND MANAGE HOST POOLS AND HOSTS BY USING POWERSHELL After completing module 2, students will be able to: Implement Azure virtual network connectivity Manage connectivity to the internet and on-premises networks Understanding Windows Virtual Desktop network connectivity Configure WVD session hosts using Azure Bastion Configure storage for FSLogix components Configure disks and file shares Modify a session host image Create and use a Shared Image Gallery (SIG) Module 3: Manage Access and Security In this module, you will learn how to plan and implement Azure roles and RBAC for WVD, implement Conditional Access policies for connections, plan and implement MFA, and manage security by using Azure Security Center. LESSONS M3 Manage access Manage security LAB: CONFIGURE CONDITIONAL ACCESS POLICIES FOR CONNECTIONS TO WVD (AD DS) After completing module 3, students will be able to: Manage local roles, groups and rights assignment on WVD session hosts. Configure user restrictions by using AD group policies and Azure AD policies Understand Conditional Access policy components Prepare for Azure Active Directory (Azure AD)-based Conditional Access for Windows Virtual Desktop Implement Azure AD-based Conditional Access for Windows Virtual Desktop Module 4: Manage User Environments and Apps In this module, you will learn how to plan for FSLogix, install FSLogix, configure Cloud Cache, deploy an application as a RemoteApp, and implement and manage OneDrive for Business for a multi-session environment. LESSONS M4 Implement and manage FSLogix Configure user experience settings Install and configure apps on a session host LAB: WINDOWS VIRTUAL DESKTOP PROFILE MANAGEMENT (AZURE AD DS) LAB: WINDOWS VIRTUAL DESKTOP PROFILE MANAGEMENT (AD DS) LAB: WINDOWS VIRTUAL DESKTOP APPLICATION PACKAGING (AD DS) After completing module 4, students will be able to: Configure Profile Containers Configure Azure Files to store profile containers for WVD in an AAD DS environment Implement FSLogix based profiles for Windows Virtual Desktop in Azure AD DS environment Implement FSLogix based profiles for Windows Virtual Desktop Prepare for and create MSIX app packages Implement MSIX app attach container for Windows Virtual Desktop in AD DS environmen Module 5: Monitor and maintain a WVD infrastructure In this module, you will learn how to plan and implement a disaster recovery plan for WVD, configure automation for WVD, implement autoscaling in host pools, and optimize session host capacity and performance. LESSONS M5 Plan and implement business continuity and disaster recovery Automate WVD management tasks Monitor and manage performance and health LAB: IMPLEMENT AUTOSCALING IN HOST POOLS (AD DS) After completing module 5, students will be able to: Plan and implement a disaster recovery plan for WVD Configure automation for WVD Monitor WVD by using Azure Monitor Customize Azure Workbooks for WVD monitoring Configure autoscaling of Windows Virtual Desktop session hosts Verify autoscaling of Windows Virtual Desktop session host [-]

  Studieår: 2013-2014   Gjennomføring: Høst og vår Antall studiepoeng: 5.0 Forutsetninger: Du må ha god kjennskap til Windows 2008 server, oppsett av AD og helst Exchange server Innleveringer: Øvinger: 8 må være godkjent.  Vurderingsform: 5 timer praktisk hjemmeeksamen med både teoretiske og praktiske oppgaver. Ansvarlig: Stein Meisingseth Eksamensdato: 09.12.13 / 12.05.14         Læremål: KUNNSKAPER:Kandidaten:- kjenner til bruken av skripting i forskjellige situasjoner i en bedrift/organisasjon- kjenner til forskjellige skripspråk- kan gjøre rede for hvordan skripting kan automatisere oppgaver i en driftssituasjon- kan bruke PowerShell for å automatisere driftsoppgaver i Windows server, VMware og andre driftsmiljøer FERDIGHETER:Kandidaten:- Powershell - historie- kan vise hvordan er PowerShell bygd opp- kan bruke PowerShell i Windows server- kan lage kommandoer og scripts i Powershell- PowerShell og .NET- kan bruke av PowerShell i Active Directory- kan bruke av PowerShell i VMware- kan bruke PowerShell i Exchange GENERELL KOMPETANSE:Kandidaten:- har kompetanse til selvstendig både å formidle og å ta i bruk sine kunnskaper og ferdigheter i en bedrift som vil automatisere typiske driftsoppgaver Innhold:- introduksjon til PowerShell 2 og 3 - hvordan lage script i PowerShell - kommandoer i PowerShell - forenkling og automatisering av drift av Windows OS med PowerShell - forenkling og automatisering av drift av Windows server med PowerShell - forenkling og automatisering av drift av Exchange server med PowerShell - forenkling og automatisering av drift av VMware med PowerShellLes mer om faget her Påmeldingsfrist: 25.08.13 / 25.01.14         Velg semester:  Høst 2013    Vår 2014     Fag Powershell i praktisk scripting 4980,-         Semesteravgift og eksamenskostnader kommer i tillegg.    [-]

COURSE OVERVIEW The Implementing and Configuring Cisco Identity Services Engine course shows you how to deploy and use Cisco Identity Services Engine (ISE) v2.4, an identity and access control policy platform that simplifies the delivery of consistent, highly secure access control across wired, wireless and VPN connections. This hands-on course provides you with the knowledge and skills required to implement and use Cisco ISE, including policy enforcement, profiling services, web authentication and guest access services, BYOD, endpoint compliance services, and TACACS+ device administration. Through expert instruction and hands-on practice, you will learn how to use Cisco ISE to gain visibility into what is happening in your network, streamline security policy management and contribute to operational efficiency.   Delegates will be expected to work in groups and share lab equipment, If you are attending virtually you may also be required to work in virtual breakout rooms. Extended hours may also be required to cover all of the content included in this class.   TARGET AUDIENCE Individuals involved in the deployment and maintenance of the Cisco ISE platform. COURSE OBJECTIVES After completing this course you should be able to: Describe Cisco ISE deployments, including core deployment components and how they interact to create a cohesive security architecture. Describe the advantages of such a deployment and how each Cisco ISE capability contributes to these advantages. Describe concepts and configure components related to 802.1X and MAC Authentication Bypass (MAB) authentication, identity management, and certificate services. Describe how Cisco ISE policy sets are used to implement authentication and authorization, and how to leverage this capability to meet the needs of your organization. Describe third-party network access devices (NADs), Cisco TrustSec®, and Easy Connect. Describe and configure web authentication, processes, operation, and guest services, including guest access components and various guest access scenarios. Describe and configure Cisco ISE profiling services, and understand how to monitor these services to enhance your situational awareness about network-connected endpoints. Describe best practices for deploying this profiler service in your specific environment. Describe BYOD challenges, solutions, processes, and portals. Configure a BYOD solution, and describe the relationship between BYOD processes and their related configuration components. Describe and configure various certificates related to a BYOD solution. Describe the value of the My Devices portal and how to configure this portal. Describe endpoint compliance, compliance components, posture agents, posture deployment and licensing, and the posture service in Cisco ISE. Describe and configure TACACS+ device administration using Cisco ISE, including command sets, profiles, and policy sets. Understand the role of TACACS+ within the authentication, authentication, and accounting (AAA) framework and the differences between the RADIUS and TACACS+ protocols. Migrate TACACS+ functionality from Cisco Secure Access Control System (ACS) to Cisco ISE, using a migration tool. COURSE CONTENT Introducing Cisco ISE Architecture and Deployment Using Cisco ISE as a Network Access Policy Engine Cisco ISE Use Cases Describing Cisco ISE Fucntions Cisco ISE Deployment Models Context Visibility Cisco ISE Policy Enforcement Using 802.1X for Wired and Wireless Access Using MAC Authentication Bypass for Wired and Wireless Access Introducing Identity Management Configuring Certificate Services Introducing Cisco ISE Policy Implementing Third-Party Network Access Device Support Introducing Cisco TrustSec TrustSec Configuration Easy Connect Web Authentication and Guest Services Introducing Web Access with Cisco ISE Introducing Guest Access Components Configuring Guest Access Services Configure Sponsor and Guest Portals Cisco ISE Profiler Introducing Cisco ISE Profiler Profiling Deployment and Best Practices Cisco ISE BYOD Introducing the Cisco ISE BYOD Process Describing BYOD Flow Configuring the My Devices Portal Configuring Certificates in BYOD Scenarios Cisco ISE Endpoint Compliance Services Introducing Endpoint Compliance Services Configuring Client Posture Services and Provisioning Working with Network Access Devices Cisco ISE TACACS+ Device Administration Configure TACACS+ Device Administration Guidelines and Best Practices Migrating from Cisco ACS to Cisco ISE Labs Lab 1: Access the SISE Lab and Install ISE 2.4 Lab 2 : Configure Initial Cisco ISE Setup, Gui Familiarization and System Certificate Usage  Lab 3: Integrate Cisco ISE with Active Directory Lab 4: Configure Cisco ISE Policy Lab 5: Configure Access Policy for Easy Connect Lab 6: Configure Guest Access Lab 7: Configure Guest Access Operations Lab 8: Create Guest Reports Lab 9: Configure Profiling Lab 10: Customize the Cisco ISE Profiling Configuration Lab 11: Create Cisco ISE Profiling Reports Lab 12: Configure BYOD Lab 13: Blacklisting a Device Lab 14: Configure Cisco ISE Compliance Services Lab 15: Configure Client Provisioning Lab 16: Configure Posture Policies Lab 17: Test and Monitor Compliance Based Access Lab 18: Test Compliance Policy Lab 19: Configure Cisco ISE for Basic Device Administration Lab 20: Configure TACACS+ Command Authorization   [-]

I kurset ”Måling og mengdebereging” vil du lære hvordan Revu brukes til å kalibrere og måle på PDF-tegninger, samt hvordan du kan opprette, spare og dele tilpassede markeringsverktøy. Disse kan så brukes til effektiv beregning av mengder og priser på alt fra vegg- og gulvarealer, til prising av utstyr på en riggplan. Å lære å bruke Revu til måling og mengdeberegning vil bl.a. gi følgende fordeler: Stor tidsbesparelse Større nøyaktighet og mindre feil Bedre dokumentasjon av mengdeberegningen Oppnå optimal utnyttelse av Bluebeam Revu i prosjektene [-]

Jira Service Management Essentials (Cloud) [-]

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     [-]

Kurs beskrivelse Er det vanskelig å skjønne hvordan Access fungerer? Har du databaser med bare 1 tabell og ikke flere som de skal ha? Får du ikke orden på dine data? Må du skrive data inn i tabellen istedenfor gjennom et skjema? Er det vanskelig å få data ut fra databasen din? Blir databasen din lite brukervennlig? Dette er vanlige problemstillinger mange sliter med og som blir borte etter endt kurs! Kurset passer for deg med liten erfaring og som ønsker å lære Access fra grunnen av. Kurset passer også for deg som er selvlært og som ønsker å jobbe mer effektivt. På kun 2 dager vil du mestre de vanligste arbeidsoppgavene i Access. Du lærer gode rutiner du trenger for å kunne arbeide raskt og effektivt. Du vil kunne lage og strukturere alt fra enkle til mer avanserte databaser og vil føle deg trygg på at det er du som kontrollerer Access og ikke omvendt! Du lærer også hvordan du skal få data ut fra databasen din gjennom spørringer og rapporter. I tillegg får du 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 Access erfaring som de gjerne deler med deg! Meld deg på Access-kurs allerede i dag og sikre deg plass!   Kursinnhold Grunnleggende begreper Introduksjon til databasedesign/datamodellering Planlegging av en ny databaseOrganisering av data i en database Opprette en database   Tabeller Tabellens utformingsvisningTabellens data arkvisning Spørringer/Queries UtvalgsspørringerHandlingsspørringer/ActionqueriesLag tabell-spørringSlettespørring-Føy til-spørringOppdateringsspørringParameterspørringer Skjemaer Opprette skjemaer med skjemaveivisereSkjemavisningUformingsvisning for skjemaerGjennomgang av designverktøyVerktøyboksenFargepalett, fonter, tekstplasseringBundne, ubundne og kalkulerte kontrollerPostkilde og feltliste for et skjemaEn-til-mange-skjema Rapporter Opprette rapporter med RapportveiviserenUtformingsvisning for en rapportGruppering og sortering i rapporter Etiketter Spesialtilpassede etikettmalerEtikettveiviseren   [-]

Dette kurset tilbys som bedriftsinternt kurs   Workshopen består av et minimum med teori og et maksimum av praktiske øvelser hvor vi lager streams av  Arrays, List, Set, Map og Files - filtrerer, mapper til nye objekter, utfører aggregeringer og konverterer tilbake til nye collections mm.   Workshopen vil dekke bl.a. Sette opp en stream, med Stream.of(), IntStream.of() og DoubleStream.of() Konvertere et Array til en stream med Arrays.stream() Konvertere en collection av typen List, Set eller Map til en stream med stream() Filtrere ut verdier med filter() Mappe til nye objekter med map() og flatMap() Sortere med sorted() og ulike typer Comparators Aggregere med reduce() og collect() Behandle hvert element med forEach() og forEachOrdered() Gruppere og telle opp forekomster i hver gruppe med collect() Konvertere tilbake til en collection med collect() Konvertere til et objekt med get() Begrense reultatet med limit() Hente enkel statistikk (min, max, average, sum) med reduce() og collect() og bl.a. summarizingInt() Bruke :: til metodereferanser Lese en fil inn i en stream med Files.lines() Behandle hvert element med forEach() og forEachOrdered() Workshopen holdes på norsk og går over 2 dager, fra 10.00-14.00, for tiden online, med dedikert lærer og Microsoft Teams som kommunikasjonsplattform.   [-]