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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Salesforce PDI : Platform Developer I ACTUAL EXAM QUESTIONS

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Exam Number : PDI
Exam Name : Platform Developer I
Vendor Name : Salesforce
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PDI test Format | PDI Course Contents | PDI Course Outline | PDI test Syllabus | PDI test Objectives

EXAM NAME: Platform Developer I

Content: 60 multiple-choice/multiple-select questions
Time allotted to complete the exam: 110 minutes
Passing Score: 65%
Registration fee: USD 200, plus applicable taxes as required per local law
Retake fee: USD 100, plus applicable taxes as required per local law

 Describe the considerations when developing in a multi-tenant environment.
 Describe how the Salesforce platform features map to the MVC pattern.
 Describe the capabilities of the core CRM objects in the Salesforce schema.
 Identify the common scenarios for extending an application's capabilities using the AppExchange.
 Identify common use cases for declarative customization of the Lightning
Platform, and customization and features of the Heroku platform.
 Given a set of requirements, determine the appropriate data model.
 Describe the capabilities of the various relationship types and the implications
of each on record access, user interface (UI), and object-oriented
 Describe the impact of schema design and modifications on Apex
 Describe how to visualize and create entity relationships.
 Describe the options for and considerations when importing and exporting
data into development environments.
 Describe how to programmatically access and utilize the object schema.
 Describe the capabilities and use cases for formula fields.
 Describe the capabilities and use cases for roll-up summary fields.
 Describe the capabilities of the declarative process automation features.
 Describe when to use declarative automation features vs. Apex classes and
 Describe how to declare variables and constants in Apex and how to assign
values using expressions.
 Describe the primitive and complex Apex data types and when to use them.
 Describe how to use and apply Apex control flow statements.
©Copyright 2018 Salesforce.com, inc. All rights reserved. 7
 Describe how to write and when to use Apex classes and interfaces.
 Describe how to use basic SOSL, SOQL, and DML statements when working
with objects in Apex.
 Describe the basic patterns used in triggers and classes to process data
 Describe when to use and how to write triggers.
 Describe the implications of governor limits on Apex transactions.
 Describe the relationship between Apex transactions, the save order of
execution, and the potential for recursion and/or cascading.
 Describe how to implement exception handling in Apex.
 Describe how to write Visualforce controllers.
 Describe when and how to use standard Visualforce controllers vs. Apex
custom controllers and controller extensions.
 Describe the programmatic techniques to prevent security vulnerabilities in
Apex and Visualforce.
 Describe how Apex impacts the ability to make declarative changes.
 Describe how to display Salesforce data using a Visualforce page.
 Describe the types of web content that can be incorporated into Visualforce
 Describe how to incorporate Visualforce pages into Lightning Platform
 Describe the benefits of the Lightning Component framework.
 Describe the resources that can be contained in a Lightning Component.
 Describe the testing framework and requirements for deployment.
 Describe how to write unit tests for triggers, controllers, and classes.
 Describe when and how to use various sources of test data.
 Describe how to execute one or multiple test classes.
 Describe the differences between invoking Apex in execute anonymous vs. unit

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Salesforce I real Questions


Salesforce Change Management: 6 Tips to Simplify it

In the ever-evolving landscape of business technology, adapting to change is no longer a choice — it’s a necessity. And when it comes to managing those changes seamlessly, Salesforce stands tall as a powerhouse. However, navigating the intricate realm of Salesforce Change Management can often leave even the most seasoned professionals scratching their heads.

We unveil six invaluable tips that promise to unravel the complexities, making the process not just manageable, but downright straightforward. Whether you’re a salesforce novice or a seasoned pro, these insights will empower you to wield change as a tool for growth, without breaking a sweat.

Clear Change Identification and Prioritization

Before embarking on any salesforce changes, it’s essential to meticulously define the scope and objectives of the proposed modifications. This involves a detailed analysis of the current system, identifying pain points, and recognizing opportunities for enhancement. Once potential changes are identified, a rigorous prioritization process should be employed.

This prioritization should be based on factors such as the anticipated business impact, alignment with strategic goals, and feasibility of implementation. The impacts of any change should be thoroughly evaluated, considering both short-term and long-term consequences. This includes assessing potential disruptions to existing processes, workflows, and user experiences, as well as estimating the financial, resource, and time investments required for successful implementation.


Cross-Functional Collaboration

Successful salesforce change management thrives on collaborative efforts across diverse departments. Forming a dedicated change management team comprising representatives from different functional areas fosters a holistic approach. Involving stakeholders early in the process ensures that all perspectives are considered, mitigating resistance and enhancing buy-in.

Open communication channels must be established to facilitate idea sharing, status updates, and issue resolution. This collaborative synergy not only promotes comprehensive change planning but also empowers a sense of ownership among stakeholders. By uniting expertise and insights from various disciplines, organizations can navigate change with collective strength and drive more successful implementations.

Comprehensive Change Documentation

Thorough documentation is the backbone of effective salesforce change management. Detailed records of change requests, requirements, and implementation plans ensure a clear roadmap for all involved. A well-maintained repository of version-controlled documentation facilitates transparency, aiding in tracing the evolution of changes and reducing confusion. This meticulous documentation also supports knowledge transfer, enabling seamless onboarding and continuity.

By meticulously capturing every step and decision, organizations establish a reliable foundation for change, ensuring that stakeholders remain informed and aligned throughout the process. Robust documentation safeguards against uncertainties and serves as a valuable resource for future enhancements.

Thorough Testing and Quality Assurance

Rigorous testing and quality assurance are cornerstones of successful Salesforce change management. Crafting comprehensive test plans and scenarios allows for the meticulous examination of new configurations and functionalities. User Acceptance Testing (UAT) involving end-users validates the changes from a practical standpoint, ensuring they meet user needs and expectations.

Addressing any detected bugs, performance issues, or discrepancies during testing guarantees a smoother transition. A robust testing phase minimizes post-implementation disruptions and fosters user confidence. By prioritizing quality assurance, organizations fortify their change management process, delivering dependable solutions that align seamlessly with business objectives.

User Training and Support

Empowering users through effective training and ongoing support is pivotal in salesforce change management. Developing comprehensive training materials, including guides and tutorials, equips users with the knowledge to navigate new features and processes. Conducting engaging training sessions and workshops enhances user proficiency and fosters a positive transition experience.

Providing accessible avenues for user support, such as help desks or forums, ensures timely issue resolution and knowledge sharing. Prioritizing user training and support cultivates user confidence, reduces frustration, and promotes efficient utilization of the salesforce platform, ultimately contributing to the success of change initiatives.

Effective Change Rollout and Monitoring

A well-executed change rollout and vigilant monitoring are pivotal to salesforce change management success. Careful planning of controlled rollouts or pilot launches ensures gradual adoption and minimizes disruption. Monitoring user adoption, feedback, and system performance provides valuable insights into the effectiveness of implemented changes. Iterative improvements based on real-time data help fine-tune configurations and address evolving needs.

This proactive approach guarantees that the change’s impact aligns with expectations, promoting sustained user satisfaction. By maintaining a watchful eye on the ongoing change process, organizations can swiftly adapt, optimize, and enhance the Salesforce environment, driving long-term success and continuous improvement.

Simplifying Salesforce change management is a multi-faceted endeavor that demands strategic planning, collaboration, documentation, testing, training, and vigilant monitoring. By adhering to these key principles, organizations can navigate transitions with clarity, engage stakeholders effectively, and ensure seamless system enhancements. Embracing change as an iterative process allows for agility and continuous improvement, leading to a Salesforce environment that not only meets current needs but also lays a solid foundation for future innovation and success.


How HVACDirect.com Keeps Customer Connection a Top Priority

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  • Tackling the not-so-hidden risks of ChatGPT and generative AI

    Presented by Coveo

    The hype around ChatGPT and generative AI is real — and the wide-spread excitement stirred up about the technology makes it clear that it will be key to transforming digital experiences. Suddenly enterprise executives recognize that it’s a new paradigm for search and for the digital experience — and what users and customers now expect: a conversational experience that provides not just results, but advice, in a way Google never could.

    “Customers can use the technology to engage in more complex interactions, making pure self-service completely viable and profitable,” says Louis Têtu, chairman and CEO of Coveo. “AI is not about automation and efficiency; it is about augmentation and proficiency. The more I can help you become more proficient on your own, the more satisfied you will be, and the less cost I will engage to satisfy you.”

    But while business leaders are putting pressure on their troops to add generative AI and do it quickly, the technology, as it stands, has several risks — what Têtu calls “the 9 headaches of CIOs with GenAI.”

    Why generative AI must be handled with care

    Behind the hype lie risks that must be addressed before the technology can be unleashed in a sensitive enterprise environment. GenAI requires infrastructure to support ingesting and feeding the right context into those models for them to generate high-quality answers while remaining cost-effective at a large scale — and in a way that respects privacy, security, permissions and proprietary content. Here’s a look at why it’s so hard to lock down a standard Large Language Model [LLM] solution, or generate high-quality answers, and CIOs are rubbing their temples.

    Unsecure environment, lack of confidentiality and privacy

    Right off the bat, one of the greatest challenges of building and implementing an enterprise AI search and answering solution is the difficulty of securing the environment throughout the generative AI process, as well as maintaining permissions and privacy.

    “Does a pharmaceutical company want to upload its IP and customer information into OpenAI? Of course not,” Têtu says “Do I want my customer service people to start loading it up as prompts into GPT, and let GPT store it and use it for someone else? You must isolate the corpus of data that is secure before you even start generating an answer, and control how the generative platform will use the data.”

    Hallucinations, outdated answers, non-compliance and validity

    LLMs have no concept of “truth,” hard rules or factual accuracy — just language understanding, and are trained on finite data, which is frozen in time, generally in the past. Therefore, there’s a genuine danger of hallucinations — connecting a set of facts together to create a novel yet false answer — while enterprise brands cannot hallucinate with customers and other stakeholders. The need for veracity and verifiability, maintaining the connection to the source of truth behind the generative process, and current not outdated answers, supports the enterprise imperatives of compliance and the need to maintain credibility.

    “The enterprise world has constraints, obligations, compliance requirements,” Têtu explains. “If you’re Boeing and a Singapore Airlines engineer with a grounded Dreamliner in Malaysia is trying to solve an engine problem, you cannot hallucinate. On top of that, compliance demands that whatever answer you create, you need to keep the linkage to the source of truth, securely.”

    Content decentralization

    Part of the challenge, and opportunity, is that enterprises also have a huge amount of content, spread across multiple sources, from documents to wikis, intranets, engineering files and customer and service information. The value of generative AI increases exponentially if you can tap into these multiple sources of content to generate answers but exacerbates the security risk unless you can control it well.

    Siloed search and conversational channels

    The world of search, personalization, answers and conversations are all converging into a new, more modern, digital experience expectation. It’s an experience which unifies search relevance and discovery with personalized answers and conversations. The traditional search box has just become bigger, where ‘intent’ is expressed through either traditional queries or long-form questions. Enterprises struggle to unify conversational and search channels, which makes the user experience inconsistent and adds unnecessary friction.

    Treating answering separately is the mistake a majority of enterprises are making right now Têtu says. Pressure from executives means they developed a separate generative AI, forgetting that there’s an existing infrastructure that will probably still serve as the vast majority of interactions.

    “Search is not going away,” he explains. “Not everyone will ask a long-form question. You need to make sure that search and chat will generate the same answer, both grounded in the same corpus of results. The way to do that is to make sure they consume the same secure index for all search, extraction, embedding and the vectordb, and the same relevance logic for search and prompt engineering. In other terms, the LLM portion is really only the answering formulation portion.”

    The cost of an enterprise solution

    A big reason execs should worry about chat and search silos is cost. “The cost of a generative answer right now is approximately 1,000x more expensive than a query event,” Têtu says. “A rich digital experience triggers about 10 queries, so it’s a 100-to-one cost ratio. While this will improve, you would not want to multiply the cost of your search infrastructure by 100.”

    Addressing the risks of generative AI

    How do you adopt generative AI within the enterprise to ensure you deliver a trusted, relevant, accurate content experience which is coherent across all search and conversational channels and is secure, current, verifiable, and cost effective? That’s the real challenge, but Têtu says, it’s doable.

    “You need to be thoughtful about the architecture of how you inject these conversational channels as part of the overall digital experience, and how you feed generative AI. The science here is really in the prompt engineering and grounding data.”

    Security, privacy and relevance

    First, a platform should guarantee secure access to data with an infrastructure that respects permission and data security rules. On top of that, it requires relevance. While traditional search is content-centric, AI is the technology which lets you understand who’s on the other end, their intent and context, and thus can deliver relevant results and recommendations.

    Coveo addressed that issue with Coveo Relevance Cloud. It unifies data across systems to generate a unified enriched index and holistic understanding of content, and uses powerful AI to understand each user who interacts with it, their context and intent. It’s AI ranking algorithms match each query intent to the most relevant content results. This then forms the secure and relevant corpus of content that feeds its new Coveo Relevance Generative Answering technology, built on top of Coveo Relevance Cloud.

    Verifiable and credible answers

    As the solution leverages real-time data sources from its unified index, it can feed generative answers that are grounded and consistent with enterprise content and maintain links with sources of truth, allowing users to verify and validate the accuracy and credibility of generated answers while discovering more supportive content.

    Corralling every source of content

    Instead of putting gen AI on a small FAQ repository or knowledge base, the technology can be geometrically unleashed by indexing all sources of content across the enterprise, from engineering and customer files to supply chain information, customer service data and all the other areas content is generated, and use all these pieces of data to generate answers.

    In fact, Coveo is currently the only company able to deploy generative AI from multiple sources of enterprise data securely, from Salesforce, Adobe, ServiceNow, SAP, Oracle and Microsoft to the swath of databases and apps in an enterprise. The solution is even able to access external content such as YouTube — consider all the companies for whom YouTube offers relevant content for customers.

    Bringing down costs

    By combining advanced indexing, search and relevance algorithms to LLM technology, enterprises get results for a fraction of the cost typically associated with generative AI — reducing the huge cost of generative chat.

    “Coveo is very uniquely positioned because they already have the corpus of data, it’s secure and it’s relevant to the issues that the user has,” Têtu says. “We can bring it all together, feed it in an LLM, and generate an answer at a much lower cost, much faster, that’s accurate to the context, secure, current, respects permissions and so on, and they get an answer that’s truly coherent, relevant and trustworthy.”

    Dig deeper: Learn more here about how Coveo is changing the generative AI landscape for enterprises.

    Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.

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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 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.


    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:


    • 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


    • 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