Amazon DEA-C01 Exam Prep
AWS Certified Data Engineer - Associate DEA-C01 (Page 9 )

• Writing with Apache Spark, typically as Delta tables.
• Reading with Apache Spark for processing and analysis.
• Reading with T-SQL through the lakehouse’s automatically generated SQL analytics endpoint.
• Reading with KQL through Fabric’s query capabilities that can access lakehouse data.

• Eventhouse: Optimized for real-time and KQL workloads, but it is not the natural destination for Spark-based writes or general lakehouse storage.
• Datamart: Intended mainly for relational analytics and Power BI; it is not designed for Spark-based data ingestion.
• Warehouse: Primarily T-SQL-based and structured. It does not provide the same native Spark write experience or flexibility for semi-structured data.

• Works across SaaS and internal applications: TOTP is widely supported by authentication systems and can be integrated into many applications.
• Device manufacturer agnostic: A hardware token or authenticator application can generate the code without depending on a specific computer or phone manufacturer.
• Offline capability: The code is generated locally using a shared secret and the current time; an internet connection or cellular service is not required.

• Username and password: May work offline but provides weaker authentication and does not meet the intended improvement in security.
• Biometrics: Can depend on device hardware, operating-system support, and enrollment mechanisms.
• SMS verification: Requires cellular connectivity and is vulnerable to threats such as SIM swapping.

• Guiding principles
• Governance
• Service value chain
• Practices
• Continual improvement

• Guiding principles: Recommendations that guide decisions and actions; they do not describe the entire system.
• Four dimensions: Perspectives used to ensure a balanced approach to service management.
• Service relationship: Describes cooperation between a service provider and service consumer, rather than the whole value-creation system.

• Interactive development and exploration
• Small datasets
• Lightweight transformations or testing
• Avoiding the overhead and cost of multiple workers

• Automated reports: Jobs may benefit from job clusters or SQL warehouses.
• Working with SQL in Databricks SQL: Databricks SQL warehouses are the relevant compute option.
• Automatically scaling for larger data: A multi-node cluster with autoscaling is more suitable.
• Large amounts of data: Distributed worker nodes are generally needed.

• SQL injection
• Cross-site scripting (XSS)
• Malicious file uploads
• Common web-application exploits

• Layer 4 firewall: Filters primarily by IP addresses, ports, and transport protocols; it lacks detailed web-application inspection.
• NGFW: Provides advanced network filtering and may include application awareness, but a WAF is more specialized for protecting web applications.
• UTM: Combines several security functions in one device, but it is not specifically focused on web-application attacks.

• Low usage during the first three weeks
• Very high usage during the last week

• High availability: Keeps services running despite failures.
• High latency: Means slow response times; it is not a benefit.
• Load balancing: Distributes traffic across resources but does not specifically address scaling resources up and down.

• Which Security policy matches
• Which NAT rule/translation is selected
• Which PBF rule applies
• Which route is used

text 
test security-policy-match ... 
test nat-policy-match ... 
test pbf-policy-match ... 
test routing fib-lookup ...

1. Get Data > Folder

1. Expand the Attributes column

1. Remove the Content column

• Folder connector: lists files and their metadata, but also includes a Content binary column.
• Combine Files: processes and combines the actual CSV contents, which is explicitly disallowed here.

text 
heartrateheartrateheartrate

• Spark column objects can be multiplied, for example:

python 
  df["heartrate"] * 3

• A DataFrame itself cannot be multiplied, but the expression is referring to a column.
• It is also not primarily a Python syntax error; the code was parsed, then Spark failed while resolving the column name.

• Documented and evaluated
• Assessed for security, cost, and operational impact
• Reviewed and approved by the appropriate personnel
• Tested before implementation
• Tracked with version history and rollback procedures

• Risk management process: May help assess the issues, but it does not authorize and manage design changes.
• Product design process: Applies primarily while creating a new design.
• Design review process: Normally evaluates a design before release; this design is already released.

• A single Construction Job can use multiple Machinery records.
• A single Machinery record may be used on multiple Construction Jobs.
• This is a many-to-many relationship, which Salesforce models using a junction object.
• The junction object can contain fields such as:

• Master-detail to Machinery
• Master-detail to Construction Job
• Date and cost fields

• A: Allow SAN certificates — SANs are used to identify valid hostnames in a certificate. They do not bypass trust validation.
• C: Open the secure LDAP port — A blocked port would normally cause a timeout or connection-refused error, not certificate errors.
• D: Increase the TLS version on the RA — The issue concerns certificate trust, not the organization’s registration authority.

• Replace the keyboard: More expensive and unnecessary before simpler causes are ruled out.
• Replace the key switch: Laptop keyboards generally aren’t designed for individual switch replacement.
• Replace the circuit board: Excessive for a single nonworking key and not a cost-effective first step.

• 25 — Traditional SMTP server-to-server delivery; often restricted for client submission and not inherently encrypted.
• 110 — POP3 for retrieving email; unencrypted by default.
• 143 — IMAP for retrieving and synchronizing email; unencrypted by default.
• 587 — Authenticated SMTP submission, commonly secured with STARTTLS.

• A. Modify CommunitiesSelfRegController

• C. Configure Communities registration to use a custom Visualforce page

• B. Modify the self-registration trigger — There is no standard “self-registration trigger” intended for this configuration. The registration logic is handled by the Visualforce controller.
• D. Configure a custom Apex controller — The standard approach is to modify the provided CommunitiesSelfRegController, rather than simply selecting a separate controller configuration.

• Aggregation happens once, during the scheduled job.
• Dashboard users query a relatively small, precomputed table.
• Repeated users do not trigger expensive aggregations against the detailed sales table.
• Overwriting is appropriate because the summary is rebuilt for the reporting period.

• B: Structured Streaming is unnecessary for data that only needs daily refreshes and adds operational/compute overhead.
• C: A view recomputes the aggregation at query time, increasing latency and query cost.
• D: Delta caching may improve reads but does not replace the need to materialize the expensive aggregation, and cache availability is not the main design guarantee.

• Have a definite, clear objective (C): Know exactly what you want to communicate. A clear purpose reduces ambiguity and irrelevant information.
• Plan the communication (E): Decide what to say, who needs the information, the appropriate channel and the best timing.
• Seek feedback (F): Check that the receiver understood the message. This could involve asking for confirmation or inviting questions.

• Ask questions (A): Usually associated with the receiver checking or clarifying information, although a sender may use questions in practice.
• Give feedback (B): Feedback is generally the receiver’s response to the sender’s message. The sender’s responsibility here is to seek feedback.
• Consider their contribution (D): This is not a standard sender-focused step in the communication process. The sender should consider the receiver’s needs and perspective, but the wording is less precise than the three recognised actions above.

• Planning and designing products and services
• Developing and delivering them
• Managing risks, suppliers, and resources
• Measuring performance
• Continually improving value delivery

• Value stream steps describe activities used to create and deliver value; they do not themselves provide the broader capabilities.
• Vision and operating model provide direction and structure, but they are not the practical management capabilities that enable the work.
• Value chain is the operating model showing how activities combine to create value; it is enabled by practices and resources.

• B: Moving the task may affect the critical path and should not be done before evaluating the planned response and impacts.
• C: Excluding a required task is not appropriate without formal analysis and stakeholder approval.
• D: Lessons learned and the risk log should be updated, but only after or alongside managing the immediate issue; updating them is not the first action.

• ARP poisoning: Redirects or intercepts local network traffic; monitoring would typically show suspicious ARP changes or man-in-the-middle behavior.
• Jamming: Interferes with wireless or radio signals. It would affect connectivity, not usually show a server-specific overload.
• Kerberoasting: Attempts to obtain and crack Kerberos service-account hashes; it does not normally cause a system outage.

• A: Using an external OAuth 2.0 identity provider could provide unified identity, but it does not specifically address Salesforce capacity or high-volume login limits.
• B: Making the Experience Cloud community a SAML identity provider and using JIT provisioning is a possible federation pattern, but it may not be appropriate for this scale without Salesforce validation.
• C: A default account is unrelated to solving identity unification and high login throughput. Person Accounts can be supported in appropriate B2C Commerce integrations.

• The identified risk
• Its likelihood and potential impact
• The person or team responsible for handling it
• The response or treatment plan
• Risk thresholds, such as when escalation or action is required
• Current status and review dates

• Risk tolerance: The amount of risk an organization is willing to accept; it is a concept or limit, not usually the primary documentation.
• Risk transfer: Moving the responsibility or financial impact of a risk to another party, such as through insurance.
• Risk analysis: The process of evaluating risk likelihood and impact.

• B. The community must be built with the Customer Account Portal template.

• C. An experience ID (expid) or placeholder parameter must be used in the URL.

• A: The Visualforce + Salesforce Tabs template does not provide this dynamic branding capability.
• D: An external CMS is not required. The branding configuration is handled within Salesforce Experience Cloud.

• Hardware and infrastructure
• System software
• Networks and communications
• Technology platforms and services

• Business Architecture: Defines business strategy, organization, functions, and processes.
• Data Architecture: Defines the structure and management of enterprise data.
• Application Architecture: Describes application systems and how they interact to support business and data processing.

• If the Facebook user is new, Salesforce invokes createUser.
• If the user already exists, Salesforce can invoke updateUser.
• The handler can read the latest data from Facebook, such as name, email, or other profile attributes, and update the corresponding Salesforce user.

• B: A scheduled job is unnecessary and would not provide real-time synchronization during authentication.
• C: A Facebook signed request is not the standard mechanism for updating Salesforce user records in this authentication-provider setup.
• D: SAML Just-in-Time provisioning applies to SAML identity providers, not Facebook OAuth authentication.

• The user authenticates with the external Identity Provider.
• Salesforce receives the SAML assertion.
• Salesforce uses attributes in that assertion—such as username, email, first name, last name, and profile/community information—to create the user during the first login.
• On later logins, Salesforce updates or uses the existing user record.

• On-the-fly provisioning is a general phrase; the Salesforce capability being tested is specifically JIT provisioning.
• Salesforce APIs would require a separate integration and provisioning process.
• Identity Connect is designed primarily to synchronize users from an identity directory, not to create users at the moment of their first SAML login.

• Basic: Self-help only; no technical support or design assessment.
• Standard: Technical support, but not the full proactive architectural guidance required here.
• Professional Direct: Provides proactive guidance and architecture-related assistance.
• Premier: Also supports this, but is a more expensive, enterprise-level option.

• MAC flooding: Overwhelms a switch’s MAC address table, potentially causing traffic to be broadcast.
• DNS spoofing: Provides false DNS responses to redirect users.
• ARP poisoning: Sends false ARP information to associate an attacker’s MAC address with another device’s IP address.

• Customer contains one row per customer and the customer’s Address ID.
• Address contains one row per address and the corresponding location details.

1. Select the Customer query.
2. Choose Merge Queries.
3. Match Customer[Address ID] with Address[Address ID].
4. Use a Left outer join so every customer is retained.
5. Expand the merged Address column and select City, State/Region, and Country.

• Append adds rows vertically and is used for tables with the same structure.
• Group By summarizes rows rather than adding related columns.
• Transpose switches rows and columns and does not establish a relationship.

• Amazon DynamoDB — Managed NoSQL database, not PostgreSQL.
• Amazon Athena — Serverless service for querying data in S3; intended for analytics, not OLTP.
• Amazon EMR — Managed cluster platform for big-data frameworks such as Hadoop and Spark.

• A. Microsoft 365 group with Assigned membership
• C. Microsoft 365 group with Dynamic User membership

Why?

• Assigned membership: You explicitly add User1, User2, and User3.
• Dynamic User membership: Membership is automatically determined by a rule based on user attributes.

Why the other options are incorrect

• B and D: Security groups do not support the Microsoft 365 group expiration policy.
• E: Dynamic Device groups are intended for devices, not these users, and are also security groups.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the tools needed to build, test, and deploy predictive analytics models.
• Azure Machine Learning—including the historical Azure Machine Learning Studio—is designed for the machine-learning lifecycle:

• Check whether the data is accurate, complete, and properly prepared.
• Confirm that the pattern is not caused by an outlier, data-quality problem, or modeling issue.
• If the data is valid, treat the result as a potentially valuable new business insight.

• A: A data scientist may help, but expert validation and data-quality checking come first.
• C: Filtering out inconvenient data risks hiding a valid insight.
• D: Einstein’s result should not be accepted without verification simply because it produced the finding.

• Looking up accounts, contacts, and opportunities
• Logging calls and updating Salesforce records
• Accessing previously available customer information when temporarily offline

• Salesforce Touch App: Primarily an older tablet-focused experience, not the best general solution for the sales team.
• Custom hybrid app: Unnecessary development when Salesforce provides the required capabilities natively.
• SalesforceA: Intended mainly for Salesforce administrators, not sales representatives.

• Microsoft Teams: Connects to Teams-related data, but it isn’t the primary connector for the Power Apps data tables.
• Personal Analytics: Provides personal productivity insights, not application data.
• SQL Server database: Only applies if the app explicitly uses SQL Server as its data source.
• Dataflows: Used for preparing and centralizing data, not as the normal direct connection to a Power Apps app.

• C series: CPU-optimized instances; not designed primarily for LLM training.
• G series: GPU instances generally optimized for graphics and some machine learning workloads, but not specifically large-scale model training efficiency.
• P series: Powerful GPU instances for ML training, but typically consume more energy than Trainium-based instances for suitable training workloads.