Cisco-Ausbildung

Insoft Services ist einer der wenigen Schulungsanbieter in EMEAR, der ein umfassendes Angebot an Cisco-Zertifizierungen und spezialisierten Technologieschulungen anbietet.

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Cisco Zertifizierungen

Erleben Sie einen Blended-Learning-Ansatz, der das Beste aus von Lehrern geleiteten Schulungen und E-Learning zum Selbststudium kombiniert, um sich auf Ihre Zertifizierungsprüfung vorzubereiten.

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Cisco Learning Credits

Cisco Learning Credits (CLCs) sind Prepaid-Schulungsgutscheine, die direkt bei Cisco eingelöst werden und die Planung für Ihren Erfolg beim Kauf von Cisco-Produkten und -Services erleichtern.

Lösen Sie Ihre CLCs ein

Cisco Continuing Education

Das Cisco Continuing Education Program bietet allen aktiven Zertifizierungsinhabern flexible Optionen zur Rezertifizierung, indem sie eine Vielzahl von in Frage kommenden Schulungselementen absolvieren.

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Cisco Digital Learning

Zertifizierte Mitarbeiter sind GESCHÄTZTE Vermögenswerte. Erkunden Sie die offizielle Digital Learning Library von Cisco, um sich durch aufgezeichnete Sitzungen weiterzubilden.

CDLL-Katalog

Cisco Business Enablement

Das Cisco Business Enablement Partner Program konzentriert sich auf die Verbesserung der Geschäftsfähigkeiten von Cisco Channel Partnern und Kunden.

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Cisco Schulungskatalog

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Technische Zertifizierung

Das Fortinet Network Security Expert (NSE) -Programm ist ein achtstufiges Schulungs- und Zertifizierungsprogramm, um Ingenieuren ihre Netzwerksicherheit für Fortinet FW-Fähigkeiten und -Erfahrungen beizubringen.

Technische Kurse

Fortinet-Ausbildung

Insoft ist als Fortinet Authorized Training Center an ausgewählten Standorten in EMEA anerkannt.

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Fortinet Schulungskatalog

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ATC Status

Überprüfen Sie unseren ATC-Status in ausgewählten Ländern in Europa.

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Fortinet Service-Pakete

Insoft Services hat eine spezielle Lösung entwickelt, um den Prozess der Installation oder Migration zu Fortinet-Produkten zu rationalisieren und zu vereinfachen.

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Microsoft-Ausbildung

Insoft Services bietet Microsoft-Schulungen in EMEAR an. Wir bieten technische Schulungen und Zertifizierungskurse von Microsoft an, die von erstklassigen Instruktoren geleitet werden.

Technische Kurse

Extreme-Ausbildung

Erfahren Sie außergewöhnliche Kenntnisse und Fähigkeiten von Extreme Networks.

Technische Kurse

Technische Zertifizierung

Wir bieten einen umfassenden Lehrplan für technische Kompetenzen zur Zertifizierung an.

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Extreme Schulungskatalog

Hier finden Sie alle Extreme Networks online und den von Lehrern geleiteten Kalender für den Klassenraum.

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ATP-Akkreditierung

Als autorisierter Schulungspartner (ATP) stellt Insoft Services sicher, dass Sie die höchsten verfügbaren Bildungsstandards erhalten.

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Lösungen & Dienstleistungen

Wir bieten innovative und fortschrittliche Unterstützung bei der Konzeption, Implementierung und Optimierung von IT-Lösungen. Unsere Kundenbasis umfasst einige der größten Telcos weltweit.

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Ein weltweit anerkanntes Team von zertifizierten Experten unterstützt Sie bei einem reibungsloseren Übergang mit unseren vordefinierten Beratungs-, Installations- und Migrationspaketen für eine breite Palette von Fortinet-Produkten.

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Insoft bietet autorisierte Schulungs- und Beratungsdienstleistungen für ausgewählte IP-Anbieter. Erfahren Sie, wie wir die Branche revolutionieren.

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  • +49 6151 277 6496
  • CompTIA Data+

    Duration
    5 Tage
    Delivery
    (Online Und Vor Ort)
    Price
    Preis auf Anfrage

    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.
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