Formazione Cisco

Insoft Services è uno dei pochi fornitori di formazione in EMEAR a offrire una gamma completa di certificazione Cisco e formazione tecnologica specializzata.

Dettagli

Certificazioni Cisco

Sperimenta un approccio di apprendimento misto che combina il meglio della formazione con istruttore e dell'e-learning autogestito per aiutarti a prepararti per l'esame di certificazione.

Dettagli

Cisco Learning Credits

I Cisco Learning Credits (CLC) sono voucher di formazione prepagati riscattati direttamente con Cisco che semplificano la pianificazione del successo durante l'acquisto di prodotti e servizi Cisco.

Dettagli

Formazione Continua

The Cisco Continuing Education Program offers all active certification holders flexible options to recertify by completing a variety of eligible training items.

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Cisco Digital Learning

Certified employees are VALUED assets. Explore Cisco official Digital Learning Library to educate yourself through recorded sessions.

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Cisco Business Enablement

The Cisco Business Enablement Partner Program focuses on sharpening the business skills of Cisco Channel Partners and customers.

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Catalogo Cisco

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Certificazioni Fortinet

Il programma Fortinet Network Security Expert (NSE) è un programma di formazione e certificazione di otto livelli per insegnare agli ingegneri la sicurezza della loro rete per le competenze e l'esperienza di Fortinet FW.

Dettagli

Corsi di formazione tecnica

Insoft è riconosciuto come Fortinet Authorized Training Center in sedi selezionate in tutta l'EMEA.

Corsi tecnici

Catalogo Fortinet

Esplora un'ampia varietà di programmi Fortinet in diversi paesi e corsi online.

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Stato ATC

Controlla il nostro stato ATC in tutti i paesi selezionati in Europa.

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Fortinet Servizi Professionale

Il team riconosciuto a livello globale di esperti certificati ti aiuta a fare una transizione più fluida con i nostri pacchetti di consulenza, installazione e migrazione predefiniti per una vasta gamma di prodotti Fortinet.

Dettagli

Catalogo Microsoft

Insoft Services fornisce formazione Microsoft in EMEAR. Offriamo corsi di formazione tecnica e certificazione Microsoft guidati da istruttori di livello mondiale.

Corsi tecnici

Corsi di formazione

Impara conoscenze e abilità eccezionali di Extreme Networks.Find all the Extreme Networks online and instructor led class room based calendar here.

Corsi tecnici

Certificazioni Extreme

Forniamo un curriculum completo di competenze tecniche sul conseguimento della certificazione.

Dettagli

Catalogo Extreme

Dettagli

Accreditamento ATP

In qualità di partner di formazione autorizzato (ATP), Insoft Services garantisce che tu riceva i più alti standard di istruzione disponibili.

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Pacchetti di consulenza

Forniamo un supporto innovativo e avanzato per la progettazione, l'implementazione e l'ottimizzazione delle soluzioni IT.La nostra base di clienti comprende alcune delle più grandi telco a livello globale.

Soluzioni & Servizi

Il team riconosciuto a livello globale di esperti certificati ti aiuta a fare una transizione più fluida con i nostri pacchetti di consulenza, installazione e migrazione predefiniti per una vasta gamma di prodotti Fortinet.

Chi siamo

Insoft fornisce servizi di formazione e consulenza autorizzati per fornitori IP selezionati.Scopri come stiamo rivoluzionando il settore.

Dettagli
  • +39 02 8704 5199
  • CompTIA Data+

    Duration
    5 Giorni
    Delivery
    (Online e in loco)
    Price
    Prezzo su richiesta

    As the importance of data analytics grows, more job roles are required to set a context and better communicate vital business intelligence. Collecting, analysing, and reporting data can drive priorities and lead business decision-making. CompTIA Data+ certification validates professionals have the skills required to facilitate data-driven business decisions, including:

    • Mining data
    • Manipulating data
    • Visualising and reporting data
    • Applying basic statistical methods
    • Analysing complex datasets while adhering to governance and quality standards throughout the entire data life cycle

     

    Associated Certification:

    • Exam Code: DA0-001
    • Instruction from CompTIA approved Data+ Certification preparation course.
    • Receive a CompTIA Data+ Exam Voucher included upon completion of the course.
    • Identify Data Concepts and Environments important in analytics.
    • Execute techniques in Data Mining, Data Mining, and Visualisation.
    • Summarise the importance of Data Governance, Quality, and Controls.
    • Continue learning and face new challenges with after-course one-on-one instructor coaching.

    Module 1: Identifying Basic Concepts of Data Schemas

    • Identify Relational and Non-Relational Databases
    • Understand the Way We Use Tables, Primary Keys, and Normalisation

    Module 2: Understanding Different Data Systems

    • Describe Types of Data Processing and Storage Systems
    • Explain How Data Changes

    Module 3: Understanding Types and Characteristics of Data

    • Understand Types of Data
    • Break Down the Field Data Types

    Module 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages

    • Differentiate between Structured Data and Unstructured Data
    • Recognise Different File Formats
    • Understand the Different Code Languages Used for Data

    Module 5: Explaining Data Integration and Collection Methods

    • Understand the Processes of Extracting, Transforming, and Loading Data
    • Explain API/Web Scraping and Other Collection Methods
    • Collect and Use Public and Publicly-Available Data
    • Use and Collect Survey Data

    Module 6: Identifying Common Reasons for Cleansing and Profiling Data

    • Learn to Profile Data
    • Address Redundant, Duplicated, and Unnecessary Data
    • Work with Missing Values
    • Address Invalid Data
    • Convert Data to Meet Specifications

    Module 7: Executing Different Data Manipulation Techniques

    • Manipulate Field Data and Create Variables
    • Transpose and Append Data
    • Query Data

    Module 8: Explaining Common Techniques for Data Manipulation and Optimisation

    • Use Functions to Manipulate Data
    • Use Common Techniques for Query Optimisation

    Module 9: Applying Descriptive Statistical Methods

    • Use Measures of Central Tendency
    • Use Measures of Dispersion
    • Use Frequency and Percentages

    Module 10: Describing Key Analysis Techniques

    • Get Started with Analysis
    • Recognise Types of Analysis

    Module 11: Understanding the Use of Different Statistical Methods

    • Understand the Importance of Statistical Tests
    • Break Down the Hypothesis Test
    • Understand Tests and Methods to Determine Relationships Between Variables

    Module 12: Using the Appropriate Type of Visualisation

    • Use Basic Visuals
    • Build Advanced Visuals
    • Build Maps with Geographical Data
    • Use Visuals to Tell a Story

    Module 13: Expressing Business Requirements in a Report Format

    • Consider Audience Needs When Developing a Report
    • Describe Data Source Considerations for Reporting
    • Describe Considerations for Delivering Reports and Dashboards
    • Develop Reports or Dashboards
    • Understand Ways to Sort and Filter Data

    Module 14: Designing Components for Reports and Dashboards

    • Design Elements for Reports and Dashboards
    • Utilise Standard Elements
    • Creating a Narrative and Other Written Elements
    • Understand Deployment Considerations

    Module 15: Distinguishing Different Report Types

    • Understand How Updates and Timing Affect Reporting
    • Differentiate Between Types of Reports

    Module 16: Summarising the Importance of Data Governance

    • Define Data Governance
    • Understand Access Requirements and Policies
    • Understand Security Requirements
    • Understand Entity Relationship Requirements

    Module 17: Applying Quality Control to Data

    • Describe Characteristics, Rules, and Metrics of Data Quality
    • Identify Reasons to Quality Check Data and Methods of Data Validation

    Module 18: Explaining Master Data Management Concepts

    • Explain the Basics of Master Data Management
    • Describe Master Data Management Processes
    • Exposure to databases and analytical tools, a basic understanding of statistics, and data visualisation experiences, such as Excel, Power BI, and Tableau.

    As the importance of data analytics grows, more job roles are required to set a context and better communicate vital business intelligence. Collecting, analysing, and reporting data can drive priorities and lead business decision-making. CompTIA Data+ certification validates professionals have the skills required to facilitate data-driven business decisions, including:

    • Mining data
    • Manipulating data
    • Visualising and reporting data
    • Applying basic statistical methods
    • Analysing complex datasets while adhering to governance and quality standards throughout the entire data life cycle

     

    Associated Certification:

    • Exam Code: DA0-001
    • Instruction from CompTIA approved Data+ Certification preparation course.
    • Receive a CompTIA Data+ Exam Voucher included upon completion of the course.
    • Identify Data Concepts and Environments important in analytics.
    • Execute techniques in Data Mining, Data Mining, and Visualisation.
    • Summarise the importance of Data Governance, Quality, and Controls.
    • Continue learning and face new challenges with after-course one-on-one instructor coaching.

    Module 1: Identifying Basic Concepts of Data Schemas

    • Identify Relational and Non-Relational Databases
    • Understand the Way We Use Tables, Primary Keys, and Normalisation

    Module 2: Understanding Different Data Systems

    • Describe Types of Data Processing and Storage Systems
    • Explain How Data Changes

    Module 3: Understanding Types and Characteristics of Data

    • Understand Types of Data
    • Break Down the Field Data Types

    Module 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages

    • Differentiate between Structured Data and Unstructured Data
    • Recognise Different File Formats
    • Understand the Different Code Languages Used for Data

    Module 5: Explaining Data Integration and Collection Methods

    • Understand the Processes of Extracting, Transforming, and Loading Data
    • Explain API/Web Scraping and Other Collection Methods
    • Collect and Use Public and Publicly-Available Data
    • Use and Collect Survey Data

    Module 6: Identifying Common Reasons for Cleansing and Profiling Data

    • Learn to Profile Data
    • Address Redundant, Duplicated, and Unnecessary Data
    • Work with Missing Values
    • Address Invalid Data
    • Convert Data to Meet Specifications

    Module 7: Executing Different Data Manipulation Techniques

    • Manipulate Field Data and Create Variables
    • Transpose and Append Data
    • Query Data

    Module 8: Explaining Common Techniques for Data Manipulation and Optimisation

    • Use Functions to Manipulate Data
    • Use Common Techniques for Query Optimisation

    Module 9: Applying Descriptive Statistical Methods

    • Use Measures of Central Tendency
    • Use Measures of Dispersion
    • Use Frequency and Percentages

    Module 10: Describing Key Analysis Techniques

    • Get Started with Analysis
    • Recognise Types of Analysis

    Module 11: Understanding the Use of Different Statistical Methods

    • Understand the Importance of Statistical Tests
    • Break Down the Hypothesis Test
    • Understand Tests and Methods to Determine Relationships Between Variables

    Module 12: Using the Appropriate Type of Visualisation

    • Use Basic Visuals
    • Build Advanced Visuals
    • Build Maps with Geographical Data
    • Use Visuals to Tell a Story

    Module 13: Expressing Business Requirements in a Report Format

    • Consider Audience Needs When Developing a Report
    • Describe Data Source Considerations for Reporting
    • Describe Considerations for Delivering Reports and Dashboards
    • Develop Reports or Dashboards
    • Understand Ways to Sort and Filter Data

    Module 14: Designing Components for Reports and Dashboards

    • Design Elements for Reports and Dashboards
    • Utilise Standard Elements
    • Creating a Narrative and Other Written Elements
    • Understand Deployment Considerations

    Module 15: Distinguishing Different Report Types

    • Understand How Updates and Timing Affect Reporting
    • Differentiate Between Types of Reports

    Module 16: Summarising the Importance of Data Governance

    • Define Data Governance
    • Understand Access Requirements and Policies
    • Understand Security Requirements
    • Understand Entity Relationship Requirements

    Module 17: Applying Quality Control to Data

    • Describe Characteristics, Rules, and Metrics of Data Quality
    • Identify Reasons to Quality Check Data and Methods of Data Validation

    Module 18: Explaining Master Data Management Concepts

    • Explain the Basics of Master Data Management
    • Describe Master Data Management Processes
    • Exposure to databases and analytical tools, a basic understanding of statistics, and data visualisation experiences, such as Excel, Power BI, and Tableau.
      Programma
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