Was ist das eigentlich? Cyberrisiken verständlich erklärt
Es wird viel über Cyberrisiken gesprochen. Oftmals fehlt aber das grundsätzliche Verständnis, was Cyberrisiken überhaupt sind. Ohne diese zu verstehen, lässt sich aber auch kein Versicherungsschutz gestalten.
Beinahe alle Aktivitäten des täglichen Lebens können heute über das Internet abgewickelt werden. Online-Shopping und Online-Banking sind im Alltag angekommen. Diese Entwicklung trifft längst nicht nur auf Privatleute, sondern auch auf Firmen zu. Das Schlagwort Industrie 4.0 verheißt bereits eine zunehmende Vernetzung diverser geschäftlicher Vorgänge über das Internet.
Anbieter von Cyberversicherungen für kleinere und mittelständische Unternehmen (KMU) haben Versicherungen die Erfahrung gemacht, dass trotz dieser eindeutigen Entwicklung Cyberrisiken immer noch unterschätzt werden, da sie als etwas Abstraktes wahrgenommen werden. Für KMU kann dies ein gefährlicher Trugschluss sein, da gerade hier Cyberattacken existenzbedrohende Ausmaße annehmen können. So wird noch häufig gefragt, was Cyberrisiken eigentlich sind. Diese Frage ist mehr als verständlich, denn ohne (Cyber-)Risiken bestünde auch kein Bedarf für eine (Cyber-)Versicherung.
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Exam Number : DA-100
Exam Name : Analyzing Data with Microsoft Power BI
Vendor Name : Microsoft
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DA-100 test Format | DA-100 Course Contents | DA-100 Course Outline | DA-100 test Syllabus | DA-100 test Objectives
Exam Number : DA-100
Exam Name : Analyzing Data with Microsoft Power BI
This course will discuss the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a range of data sources including both relational and non-relational data. This course will also explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution. Finally, this course will show how to build paginated reports within the Power BI service and publish them to a workspace for inclusion within Power BI.
Skills Gained
- Ingest, clean, and transform data
- Model data for performance and scalability
- Design and create reports for data analysis
- Apply and perform advanced report analytics
- Manage and share report assets
- Create paginated reports in Power BI
Specifically:
- Understanding core data concepts.
- Knowledge of working with relational data in the cloud.
- Knowledge of working with non-relational data in the cloud.
- Knowledge of data analysis and visualization concepts.
Course outline
Module 1: Get Started with Microsoft Data Analytics
This module explores the different roles in the data space, outlines the important roles and responsibilities of a Data Analysts, and then explores the landscape of the Power BI portfolio.
Lessons
Data Analytics and Microsoft
Getting Started with Power BI
Lab : Getting Started
Getting Started
After completing this module, you will be able to:
Explore the different roles in data
Identify the tasks that are performed by a data analyst
Describe the Power BI landscape of products and services
Use the Power BI service
Module 2: Prepare Data in Power BI
This module explores identifying and retrieving data from various data sources. You will also learn the options for connectivity and data storage, and understand the difference and performance implications of connecting directly to data vs. importing it.
Lessons
Get data from various data sources
Optimize performance
Resolve data errors
Lab : Preparing Data in Power BI Desktop
Prepare Data
After completing this module, you will be able to:
Identify and retrieve data from different data sources
Understand the connection methods and their performance implications
Optimize query performance
Resolve data import errors
Module 3: Clean, Transform, and Load Data in Power BI
This module teaches you the process of profiling and understanding the condition of the data. They will learn how to identify anomalies, look at the size and shape of their data, and perform the proper data cleaning and transforming steps to prepare the data for loading into the model.
Lessons
Data shaping
Enhance the data structure
Data Profiling
Lab : Transforming and Loading Data
Loading Data
After completing this module, students will be able to:
Apply data shape transformations
Enhance the structure of the data
Profile and examine the data
Module 4: Design a Data Model in Power BI
This module teaches the fundamental concepts of designing and developing a data model for proper performance and scalability. This module will also help you understand and tackle many of the common data modeling issues, including relationships, security, and performance.
Lessons
Introduction to data modeling
Working with tables
Dimensions and Hierarchies
Lab : Data Modeling in Power BI Desktop
Create Model Relationships
Configure Tables
Review the model interface
Create Quick Measures
Lab : Advanced Data Modeling in Power BI Desktop
Configure many-to-many relationships
Enforce row-level security
After completing this module, you will be able to:
Understand the basics of data modeling
Define relationships and their cardinality
Implement Dimensions and Hierarchies
Create histograms and rankings
Module 5: Create Model Calculations using DAX in Power BI
This module introduces you to the world of DAX and its true power for enhancing a model. You will learn about aggregations and the concepts of Measures, calculated columns and tables, and Time Intelligence functions to solve calculation and data analysis problems.
Lessons
Introduction to DAX
DAX context
Advanced DAX
Lab : Introduction to DAX in Power BI Desktop
Create calculated tables
Create calculated columns
Create measures
Lab : Advanced DAX in Power BI Desktop
Use the CALCULATE() function to manipulate filter context
use Time Intelligence functions
After completing this module, you will be able to:
Understand DAX
Use DAX for simple formulas and expressions
Create calculated tables and measures
Build simple measures
Work with Time Intelligence and Key Performance Indicators
Module 6: Optimize Model Performance
In this module you are introduced to steps, processes, concepts, and data modeling best practices necessary to optimize a data model for enterprise-level performance.
Lessons
Optimze the model for performance
Optimize DirectQuery Models
Create and manage Aggregations
After completing this module, you will be able to:
Understand the importance of variables
Enhance the data model
Optimize the storage model
Implement aggregations
Module 7: Create Reports
This module introduces you to the fundamental concepts and principles of designing and building a report, including selecting the correct visuals, designing a page layout, and applying basic but critical functionality. The important Topic of designing for accessibility is also covered.
Lessons
Design a report
Enhance the report
Lab : Designing a report in Power BI
Create a live connection in Power BI Desktop
Design a report
Configure visual fields adn format properties
Lab : Enhancing Power BI reports with interaction and formatting
Create and configure Sync Slicers
Create a drillthrough page
Apply conditional formatting
Create and use Bookmarks
After completing this module, you will be able to:
Design a report page layout
Select and add effective visualizations
Add basic report functionality
Add report navigation and interactions
Improve report performance
Design for accessibility
Module 8: Create Dashboards
In this module you will learn how to tell a compelling story through the use of dashboards and the different navigation tools available to provide navigation. You will be introduced to features and functionality and how to enhance dashboards for usability and insights.
Lessons
Create a Dashboard
Real-time Dashboards
Enhance a Dashboard
Lab : Designing a report in Power BI Desktop - Part 1
Create a Dashboard
Pin visuals to a Dashboard
Configure a Dashboard tile alert
Use Q&A to create a dashboard tile
After completing this module, students will be able to:
Create a Dashboard
Understand real-time Dashboards
Enhance Dashboard usability
Module 9: Create Paginated Reports in Power BI
This module will teach you about paginated reports, including what they are how they fit into Power BI. You will then learn how to build and publish a report.
Lessons
Paginated report overview
Create Paginated reports
Lab : Creating a Paginated report
Use Power BI Report Builder
Design a multi-page report layout
Define a data source
Define a dataset
Create a report parameter
Export a report to PDF
After completing this module, you will be able to:
Explain paginated reports
Create a paginated report
Create and configure a data source and dataset
Work with charts and tables
Publish a report
Module 10: Perform Advanced Analytics
This module helps you apply additional features to enhance the report for analytical insights in the data, equipping you with the steps to use the report for real data analysis. You will also perform advanced analytics using AI visuals on the report for even deeper and meaningful data insights.
Lessons
Advanced Analytics
Data Insights through AI visuals
Lab : Data Analysis in Power BI Desktop
Create animated scatter charts
Use teh visual to forecast values
Work with Decomposition Tree visual
Work with the Key Influencers visual
After completing this module, you will be able to:
Explore statistical summary
Use the Analyze feature
Identify outliers in data
Conduct time-series analysis
Use the AI visuals
Use the Advanced Analytics custom visual
Module 11: Create and Manage Workspaces
This module will introduce you to Workspaces, including how to create and manage them. You will also learn how to share content, including reports and dashboards, and then learn how to distribute an App.
Lessons
Creating Workspaces
Sharing and Managing Assets
Lab : Publishing and Sharing Power BI Content
Map security principals to dataset roles
Share a dashboard
Publish an App
After completing this module, you will be able to:
Create and manage a workspace
Understand workspace collaboration
Monitor workspace usage and performance
Distribute an App
Module 12: Manage Datasets in Power BI
In this module you will learn the concepts of managing Power BI assets, including datasets and workspaces. You will also publish datasets to the Power BI service, then refresh and secure them.
Lessons
Parameters
Datasets
After completing this module, you will be able to:
Create and work with parameters
Manage datasets
Configure dataset refresh
Troubleshoot gateway connectivity
Module 13: Row-level security
This module teaches you the steps for implementing and configuring security in Power BI to secure Power BI assets.
Lessons
Security in Power BI
After completing this module, you will be able to:
Understand the aspects of Power BI security
Configure row-level security roles and group memberships
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Warum sind Cyberrisiken so schwer greifbar?
Als mehr oder weniger neuartiges Phänomen stellen Cyberrisiken Unternehmen und Versicherer vor besondere Herausforderungen. Nicht nur die neuen Schadenszenarien sind abstrakter oder noch nicht bekannt. Häufig sind immaterielle Werte durch Cyberrisiken in Gefahr. Diese wertvollen Vermögensgegenstände sind schwer bewertbar.
Obwohl die Gefahr durchaus wahrgenommen wird, unterschätzen viele Firmen ihr eigenes Risiko. Dies liegt unter anderem auch an den Veröffentlichungen zu Cyberrisiken. In der Presse finden sich unzählige Berichte von Cyberattacken auf namhafte und große Unternehmen. Den Weg in die Presse finden eben nur die spektakulären Fälle. Die dort genannten Schadenszenarien werden dann für das eigene Unternehmen als unrealistisch eingestuft. Die für die KMU nicht minder gefährlichen Cyberattacken werden nur selten publiziert.
Aufgrund der fehlenden öffentlichen Meldungen von Sicherheitsvorfällen an Sicherheitsbehörden und wegen der fehlenden Presseberichte fällt es schwer, Fakten und Zahlen zur Risikolage zu erheben. Aber ohne diese Grundlage fällt es schwer, in entsprechende Sicherheitsmaßnahmen zu investieren.
Erklärungsleitfaden anhand eines Ursache-Wirkungs-Modells
Häufig nähert man sich dem Thema Cyberrisiko anlass- oder eventbezogen, also wenn sich neue Schadenszenarien wie die weltweite WannaCry-Attacke entwickeln. Häufig wird auch akteursgebunden beleuchtet, wer Angreifer oder Opfer sein kann. Dadurch begrenzt man sich bei dem Thema häufig zu sehr nur auf die Cyberkriminalität. Um dem Thema Cyberrisiko jedoch gerecht zu werden, müssen auch weitere Ursachen hinzugezogen werden.
Mit einer Kategorisierung kann das Thema ganzheitlich und nachvollziehbar strukturiert werden. Ebenso hilft eine solche Kategorisierung dabei, eine Abgrenzung vorzunehmen, für welche Gefahren Versicherungsschutz über eine etwaige Cyberversicherung besteht und für welche nicht.
Die Ursachen sind dabei die Risiken, während finanzielle bzw. nicht finanzielle Verluste die Wirkungen sind. Cyberrisiken werden demnach in zwei Hauptursachen eingeteilt. Auf der einen Seite sind die nicht kriminellen Ursachen und auf der anderen Seite die kriminellen Ursachen zu nennen. Beide Ursachen können dabei in drei Untergruppen unterteilt werden.
Nicht kriminelle Ursachen
Höhere Gewalt
Häufig hat man bei dem Thema Cyberrisiko nur die kriminellen Ursachen vor Augen. Aber auch höhere Gewalt kann zu einem empfindlichen Datenverlust führen oder zumindest die Verfügbarkeit von Daten einschränken, indem Rechenzentren durch Naturkatastrophen wie beispielsweise Überschwemmungen oder Erdbeben zerstört werden. Ebenso sind Stromausfälle denkbar.
Menschliches Versagen/Fehlverhalten
Als Cyberrisiken sind auch unbeabsichtigtes und menschliches Fehlverhalten denkbar. Hierunter könnte das versehentliche Veröffentlichen von sensiblen Informationen fallen. Möglich sind eine falsche Adressierung, Wahl einer falschen Faxnummer oder das Hochladen sensibler Daten auf einen öffentlichen Bereich der Homepage.
Technisches Versagen
Auch Hardwaredefekte können zu einem herben Datenverlust führen. Neben einem Überhitzen von Rechnern sind Kurzschlüsse in Systemtechnik oder sogenannte Headcrashes von Festplatten denkbare Szenarien.
Kriminelle Ursachen
Hackerangriffe
Hackerangriffe oder Cyberattacken sind in der Regel die Szenarien, die die Presse dominieren. Häufig wird von spektakulären Datendiebstählen auf große Firmen oder von weltweiten Angriffen mit sogenannten Kryptotrojanern berichtet. Opfer kann am Ende aber jeder werden. Ziele, Methoden und auch das Interesse sind vielfältig. Neben dem finanziellen Interesse können Hackerangriffe auch zur Spionage oder Sabotage eingesetzt werden. Mögliche Hackermethoden sind unter anderem: Social Engineering, Trojaner, DoS-Attacken oder Viren.
Physischer Angriff
Die Zielsetzung eines physischen Angriffs ist ähnlich dem eines Hackerangriffs. Dabei wird nicht auf die Tools eines Hackerangriffs zurückgegriffen, sondern durch das physische Eindringen in Unternehmensgebäude das Ziel erreicht. Häufig sind es Mitarbeiter, die vertrauliche Informationen stehlen, da sie bereits den notwendigen Zugang zu den Daten besitzen.
Erpressung
Obwohl die Erpressung aufgrund der eingesetzten Methoden auch als Hackerangriff gewertet werden könnte, ergibt eine Differenzierung Sinn. Erpressungsfälle durch Kryptotrojaner sind eines der häufigsten Schadenszenarien für kleinere und mittelständische Unternehmen. Außerdem sind auch Erpressungsfälle denkbar, bei denen sensible Daten gestohlen wurden und ein Lösegeld gefordert wird, damit sie nicht veröffentlicht oder weiterverkauft werden.
Ihre Cyberversicherung sollte zumindet folgende Schäden abdecken:
Cyber-Kosten:
- Soforthilfe und Forensik-Kosten (Kosten der Ursachenermittlung, Benachrichtigungskosten und Callcenter-Leistung)
- Krisenkommunikation / PR-Maßnahmen
- Systemverbesserungen nach einer Cyber-Attacke
- Aufwendungen vor Eintritt des Versicherungsfalls
Cyber-Drittschäden (Haftpflicht):
- Befriedigung oder Abwehr von Ansprüchen Dritter
- Rechtswidrige elektronische Kommunikation
- Ansprüche der E-Payment-Serviceprovider
- Vertragsstrafe wegen der Verletzung von Geheimhaltungspflichten und Datenschutzvereinbarungen
- Vertragliche Schadenersatzansprüche
- Vertragliche Haftpflicht bei Datenverarbeitung durch Dritte
- Rechtsverteidigungskosten
Cyber-Eigenschäden:
- Betriebsunterbrechung
- Betriebsunterbrechung durch Ausfall von Dienstleister (optional)
- Mehrkosten
- Wiederherstellung von Daten (auch Entfernen der Schadsoftware)
- Cyber-Diebstahl: elektronischer Zahlungsverkehr, fehlerhafter Versand von Waren, Telefon-Mehrkosten/erhöhte Nutzungsentgelte
- Cyber-Erpressung
- Entschädigung mit Strafcharakter/Bußgeld
- Ersatz-IT-Hardware
- Cyber-Betrug