Cisco-opplæring

Insoft Services er en av få opplæringsleverandører i EMEAR som tilbyr hele spekteret av Cisco-sertifisering og spesialisert teknologiopplæring.

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Cisco Sertifisering

Opplev en blandet læringstilnærming som kombinerer det beste av instruktørledet opplæring og e-læring i eget tempo for å hjelpe deg med å forberede deg til sertifiseringseksamen.

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Cisco Learning Credits

Cisco Learning Credits (CLC) er forhåndsbetalte opplæringskuponger innløst direkte med Cisco som gjør planleggingen for suksessen din enklere når du kjøper Cisco-produkter og -tjenester.

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Etterutdanning

Cisco Continuing Education Program tilbyr alle aktive sertifiseringsinnehavere fleksible alternativer for å resertifisere ved å fullføre en rekke kvalifiserte opplæringselementer.

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Cisco Digital Learning

Sertifiserte ansatte er verdsatte eiendeler. Utforsk Ciscos offisielle digitale læringsbibliotek for å utdanne deg gjennom innspilte økter.

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Cisco Business Enablement

Cisco Business Enablement Partner Program fokuserer på å skjerpe forretningsferdighetene til Cisco Channel Partners og kunder.

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Cisco opplæringskatalog

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Fortinet Sertifisering

Fortinet Network Security Expert (NSE)-programmet er et opplærings- og sertifiseringsprogram på åtte nivåer for å lære ingeniører om nettverkssikkerheten for Fortinet FW-ferdigheter og -erfaring.

Tekniske kurs

Fortinet-opplæring

Insoft er anerkjent som Fortinet Autorisert Opplæringssenter på utvalgte steder i EMEA.

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Fortinet opplæringskatalog

Utforsk et bredt utvalg av Fortinet Schedule på tvers av forskjellige land så vel som online kurs.

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ATC-status

Sjekk atc-statusen vår på tvers av utvalgte land i Europa.

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Pakker for Fortinet-tjenester

Insoft Services har utviklet en spesifikk løsning for å effektivisere og forenkle prosessen med å installere eller migrere til Fortinet-produkter.

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Microsoft-opplæring

Insoft Services gir Microsoft opplæring i EMEAR. Vi tilbyr Microsofts tekniske opplærings- og sertifiseringskurs som ledes av instruktører i verdensklasse.

Tekniske kurs

Extreme-opplæring

Lær eksepsjonell kunnskap og ferdigheter i ekstreme nettverk.

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Teknisk sertifisering

Vi tilbyr omfattende læreplan over tekniske kompetanseferdigheter om sertifiseringsprestasjonen.

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Extreme opplæringskatalog

Tekniske kurs

ATP-akkreditering

Som autorisert opplæringspartner (ATP) sørger Insoft Services for at du får de høyeste utdanningsstandardene som er tilgjengelige.

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Løsninger og tjenester

Vi tilbyr innovativ og avansert støtte for design, implementering og optimalisering av IT-løsninger. Vår kundebase inkluderer noen av de største Telcos globalt.

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Globalt anerkjent team av sertifiserte eksperter hjelper deg med å gjøre en jevnere overgang med våre forhåndsdefinerte konsulent-, installasjons- og migrasjonspakker for et bredt spekter av Fortinet-produkter.

Om oss

Insoft Tilbyr autoriserte opplærings- og konsulenttjenester for utvalgte IP-leverandører. Finn ut hvordan vi revolusjonerer bransjen.

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  • +47 23 96 21 03
  • Data Warehousing on AWS

    Duration
    3 Dager
    Delivery
    (Online Og På stedet)
    Price
    Pris på forespørsel

    Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift. This course demonstrates how to ingest, store, and transform data in the data warehouse. Topics covered include: the purpose of Amazon Redshift, how Amazon Redshift addresses business and technical challenges, features and capabilities of Amazon Redshift, designing a Data Warehousing Solution on AWS by applying best practices based on the Well-Architected Framework, integration with AWS and non-AWS products and services, performance tuning, orchestration, and securing and monitoring Amazon Redshift.

    • Describe Amazon Redshift architecture and its roles in a modern data architecture
    • Design and implement a data warehouse in the cloud using Amazon Redshift
    • Identify and load data into an Amazon Redshift data warehouse from a variety of sources
    • Analyze data using SQL QEV2 notebooks
    • Design and implement a disaster recovery strategy for an Amazon Redshift data warehouse
    • Perform maintenance and performance tuning on an Amazon Redshift data warehouse
    • Secure and manage access to an Amazon Redshift data warehouse
    • Share data between multiple Redshift clusters in an organization
    • Orchestrate workflows in the data warehouse using AWS Step Functions state machines
    • Create an ML model and configure predictors using Amazon Redshift ML

    Day 1

     

    Module 1: Data Warehouse Concepts

    • Modern data architecture
    • Introduction to the course story
    • Data warehousing with Amazon Redshift
    • Amazon Redshift Serverless architecture
    • Hands-On Lab: Launch and Configure an Amazon Redshift Serverless Data Warehouse

    Module 2: Setting up Amazon Redshift

    • Data models for Amazon Redshift
    • Data management in Amazon Redshift
    • Managing permissions in Amazon Redshift
    • Hands-On Lab: Setting up a Data Warehouse using Amazon Redshift Serverless

    Module 3: Loading Data

    • Overview of data sources
    • Loading data from Amazon Simple Storage Service (Amazon S3)
    • Extract, transform, and load (ETL) and extract, load, and transform (ELT)
    • Loading streaming data
    • Loading data from relational databases
    • Hands-On Lab: Populating the data warehouse

     

    Day 2

     

    Module 4: Deep Dive into SQL Query Editor v2 and Notebooks

    • Features of Amazon Redshift Query Editor v2
    • Demonstration: Using Amazon Redshift Query Editor v2
    • Advanced queries
    • Hands-On Lab: Data Wrangling on AWS

    Module 5: Backup and Recovery

    • Disaster recovery
    • Backing up and restoring Amazon Redshift provisioned
    • Backing up and restoring Amazon Redshift Serverless

    Module 6: Amazon Redshift Performance Tuning

    • Factors that impact query performance
    • Table maintenance and materialized views
    • Query analysis
    • Workload management
    • Tuning guidance
    • Amazon Redshift monitoring
    • Hands-On Lab: Performance Tuning the Data Warehouse

    Module 7: Securing Amazon Redshift

    • Introduction to Amazon Redshift security and compliance
    • Authentication with Amazon Redshift
    • Access control with Amazon Redshift
    • Data encryption with Amazon Redshift
    • Auditing and compliance with Amazon Redshift
    • Hands-On Lab: Securing Amazon Redshift

     

    Day 3

     

    Module 8: Orchestration

    • Overview of data orchestration
    • Orchestration with AWS Step Functions
    • Orchestration with Amazon Managed Workflows for Apache Airflow (MWAA)
    • Hands-On Lab: Orchestrating the Data Warehouse Pipeline

    Module 9: Amazon Redshift ML

    • Machine Learning Overview
    • Getting started with Amazon Redshift ML
    • Amazon Redshift ML workflow scenarios
    • Amazon Redshift ML Usage
    • Hands-On Lab: Predicting customer churn with Amazon Redshift ML

    Module 10: Amazon Redshift Data Sharing

    • Overview of data sharing in Amazon Redshift
    • Amazon DataZone for Data as a service

    Module 11: Wrap-Up

    • Hands-On Lab: End of course challenge la
    • Data engineers
    • Data architects
    • Database architects
    • Database administrators
    • Database developers
    • Fundamentals of Analytics on AWS – Part 1
    • Fundamentals of Analytics on AWS – Part 2
    • Building Data Lakes on AWS (Instructor led Training)
    • Building Data Analytics Solutions Using Amazon Redshift (Instructor led Training)

    Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift. This course demonstrates how to ingest, store, and transform data in the data warehouse. Topics covered include: the purpose of Amazon Redshift, how Amazon Redshift addresses business and technical challenges, features and capabilities of Amazon Redshift, designing a Data Warehousing Solution on AWS by applying best practices based on the Well-Architected Framework, integration with AWS and non-AWS products and services, performance tuning, orchestration, and securing and monitoring Amazon Redshift.

    • Describe Amazon Redshift architecture and its roles in a modern data architecture
    • Design and implement a data warehouse in the cloud using Amazon Redshift
    • Identify and load data into an Amazon Redshift data warehouse from a variety of sources
    • Analyze data using SQL QEV2 notebooks
    • Design and implement a disaster recovery strategy for an Amazon Redshift data warehouse
    • Perform maintenance and performance tuning on an Amazon Redshift data warehouse
    • Secure and manage access to an Amazon Redshift data warehouse
    • Share data between multiple Redshift clusters in an organization
    • Orchestrate workflows in the data warehouse using AWS Step Functions state machines
    • Create an ML model and configure predictors using Amazon Redshift ML

    Day 1

     

    Module 1: Data Warehouse Concepts

    • Modern data architecture
    • Introduction to the course story
    • Data warehousing with Amazon Redshift
    • Amazon Redshift Serverless architecture
    • Hands-On Lab: Launch and Configure an Amazon Redshift Serverless Data Warehouse

    Module 2: Setting up Amazon Redshift

    • Data models for Amazon Redshift
    • Data management in Amazon Redshift
    • Managing permissions in Amazon Redshift
    • Hands-On Lab: Setting up a Data Warehouse using Amazon Redshift Serverless

    Module 3: Loading Data

    • Overview of data sources
    • Loading data from Amazon Simple Storage Service (Amazon S3)
    • Extract, transform, and load (ETL) and extract, load, and transform (ELT)
    • Loading streaming data
    • Loading data from relational databases
    • Hands-On Lab: Populating the data warehouse

     

    Day 2

     

    Module 4: Deep Dive into SQL Query Editor v2 and Notebooks

    • Features of Amazon Redshift Query Editor v2
    • Demonstration: Using Amazon Redshift Query Editor v2
    • Advanced queries
    • Hands-On Lab: Data Wrangling on AWS

    Module 5: Backup and Recovery

    • Disaster recovery
    • Backing up and restoring Amazon Redshift provisioned
    • Backing up and restoring Amazon Redshift Serverless

    Module 6: Amazon Redshift Performance Tuning

    • Factors that impact query performance
    • Table maintenance and materialized views
    • Query analysis
    • Workload management
    • Tuning guidance
    • Amazon Redshift monitoring
    • Hands-On Lab: Performance Tuning the Data Warehouse

    Module 7: Securing Amazon Redshift

    • Introduction to Amazon Redshift security and compliance
    • Authentication with Amazon Redshift
    • Access control with Amazon Redshift
    • Data encryption with Amazon Redshift
    • Auditing and compliance with Amazon Redshift
    • Hands-On Lab: Securing Amazon Redshift

     

    Day 3

     

    Module 8: Orchestration

    • Overview of data orchestration
    • Orchestration with AWS Step Functions
    • Orchestration with Amazon Managed Workflows for Apache Airflow (MWAA)
    • Hands-On Lab: Orchestrating the Data Warehouse Pipeline

    Module 9: Amazon Redshift ML

    • Machine Learning Overview
    • Getting started with Amazon Redshift ML
    • Amazon Redshift ML workflow scenarios
    • Amazon Redshift ML Usage
    • Hands-On Lab: Predicting customer churn with Amazon Redshift ML

    Module 10: Amazon Redshift Data Sharing

    • Overview of data sharing in Amazon Redshift
    • Amazon DataZone for Data as a service

    Module 11: Wrap-Up

    • Hands-On Lab: End of course challenge la
    • Data engineers
    • Data architects
    • Database architects
    • Database administrators
    • Database developers
    • Fundamentals of Analytics on AWS – Part 1
    • Fundamentals of Analytics on AWS – Part 2
    • Building Data Lakes on AWS (Instructor led Training)
    • Building Data Analytics Solutions Using Amazon Redshift (Instructor led Training)
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