DataOps Methodology Cognitive Class Quiz Answers(🔰Trending)

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Here, you will find all module wise answer and final exam answers of DataOps Methodology in Bold Color which are given below.

These answers are updated recently and are 100% correct✅ answers of all modules and final exam answers of DataOps Methodology from Cognitive Class Free Certification Course.

Course Name	DataOps Methodology
Organization	SkillUp
Language	English
Certificate	Yes
Price	Free

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Module 1: Establish DataOps – Prepare for operation Lesson 2 – Establish Data Strategy

Question 1: Before we can put together a data strategy, we need to have a good understanding of the data available and how it is used in the organization.

• True
• False

Question 2: What is a data strategy?

• An architecture and actionable roadmap along with an action plan
• A competitive publication to show that our organization is modern
• A plan to move all legacy data systems to the cloud

Question 3: Implementing a data strategy should always result in cost savings in the year the plan is realized.

• True
• False  

Question 4: Which of the following statements about Data Strategy are ?

• Whatever the type of data, it should only include internally produced data
• All types of data – both structured and unstructured need to be considered
• Volumes of data have increased hugely, but are now starting to stabilize
• Only business executives should be consulted in putting together a strategy

Question 5: Data Governance is a key part of executing a data strategy.

• True
• False

Module 1: Establish DataOps – Prepare for operation Lesson 3 – Establish Team

Question 1: A DataOps team consists of members mostly from IT departments.

• True
• False

Question 2: Which of the following roles are active team members of any DataOps team?

• Chief Technology Officer
• Chief Data Officer
• Data Engineer
• Database Administrator
• Data Steward
• Data Architect
• Data Scientist

Question 3: Creating and maintain business terms is a major responsibility of which following role?

• Data Engineer
• Data Quality Analyst
• Data Steward
• Data Scientist

Question 4: Only Chief Data Officer can update the KPIs for a data sprint.

• True
• False

Question 5: DataOps relies heavily on the use of automation, so that communication among team members is not necessary.

• True
• False

Module 2: Establish DataOps – Optimize for operation Lesson 1 – Establish Toolchain

Question 1: DataOps toolchain helps you deliver quality data slowly.

• True
• False  

Question 2: DataOps Toolchain and DevOps are the same thing.

• True
• False  

Question 3: DataOps Toolchain can work without DataOps API(s).

• True
• False  

Question 4: What are the key components of DataOps Toolchain?

• Continuous Deployment
• Communication
• Source Control
• All of above  

Question 5: Who is responsible for creating DataOps Toolchain? (Choose all that apply)

• Data Scientist
• Administrator
• DBA
• Data Engineer

Module 2: Establish DataOps – Optimize for operation Lesson 2 – Establish Baseline

Question 1: Data Management is the same as Information Governance.

• True
• False

Question 2: What is the most costly result from an external influence to an organization?

• Data Breach Fines and Penalties
• Insurance Policy Payout
• Claim Settlement
• None of these

Question 3: Reference data is defined as data used as a permissible value within a data field.

• True
• False

Module 2: Establish DataOps – Optimize for operation Lesson 3 – Establish Business Priorities

Question 1: Business Priority should be the primary focus when deciding what the DataOps team should do.

• True
• False

Question 2: What is a data backlog?

• A bottleneck in the data pipeline
• A list of all data sources
• A prioritized set of requirements expressed as data tasks
• A plan to move all data into a catalog

Question 3: A prioritized data backlog will reduce the time taken to start the next DataOps iteration.

• True
• False

Question 4: A Data Task should be prioritized by considering:

• The cost of providing the data
• The career advancement possibilities of solving business challenges
• The impact to sales from implementing the data pipeline
• All of the above  

Question 5: KPIs are used to determine the progress and throughput of a DataOps data sprint.

• True
• False

Module 3: Iterate DataOps – Know your data Lesson 1 – Discover

Question 1: You will need someone on your team with detailed knowledge of the business processes you’re going to analyze so selected data elements are appropriate to reaching your objectives.

• True
• False

Question 2: What should you do if you identify gaps or mismatches in the data required for the analysis?

• Rethink how you will do the analysis with different data
• Create the missing data
• Find a new source for the missing or mismatched data
• All of the above  

Question 3: You should trace the linage of data elements to be used for analysis to make sure they come from a trusted source.

• True
• False

Question 4: What is the primary objective of the Discover phase?

• Decide what the analytics team wants to have for lunch
• Identify and locate the specific data elements required to accomplish an analysis
• Uncover the meaning of data column headers and how they relate to the underlying data
• Gain an understanding of the business goals and KPIs of an analysis effort

Question 5: A Data Engineer who thoroughly understands where specific data resides, including the specific databases and files where each identified data element resides, should be involved in Data Discovery process.

• True
• False

Module 3: Iterate DataOps – Know your data Lesson 2 – Classify

Question 1: Classification of each data element will make it easier going forward for users to distinguish the meaning and applicability of the data for their purposes.

• True
• False

Question 2: Which description best defines taxonomy?

• Organizing data elements into meaningful structures
• An IBM network protocol which reduces network latency
• The art of preparing, stuffing, and mounting the skins of animals with lifelike effect

Question 3: A single data element can be placed into an unlimited number of data domains.

• True
• False

Question 4: Which of the following is the objective of classification?

• To bring out points of similarity and dissimilarity among various groups
• To present data in a simple, logical and understandable form
• To condense the mass of data
• All of the above  

Question 5: You should design workflows which are specific to the classification tool you are using.

• True
• False

Module 4: Iterate DataOps – Trust your data Lesson 1 – Manage Qualities & Entities

Question 1: Data quality is data accuracy.

• True
• False

Question 2: All data across the enterprise should have the same data quality.

• True
• False

Question 3:A data quality framework consists of which of the following 4 phases:

• Profile
• Define
• Remediate
• Monitor
• Assess
• Deploy 

Question 4: When assessing data quality, you only need the data set containing the data, metadata is optional.

• True
• False

Module 4: Iterate DataOps – Trust your data Lesson 2 – Manage Policies

Question 1: How does data classification affect defining policies?

• Inheritance, retention and probabilities
• Protection, reporting and inheritance
• Protection, accessibility and retention
• Retention, deletion and storage

Question 2: What impact does a highly sensitive classification have on a policy definition?

• Require data anonymization, de-identification, and masking
• Limit access to the data and/or require data masking
• Limit access to the data and make it unprintable
• No impact

Question 3: What are the most common state, country or regional regulations affecting personal information?

• SIN, SSN and BAN
• FDIC, BCBS and SOX
• CCPA, GDPR and LGPD
• PCI, PII and PHI

Question 4: Once policies have been defined affecting the data, rules must be enforced to act.

• True
• False

Module 5: Iterate DataOps – Use your data  Lesson 1 – Self Service

Question 1: Self Service of data is only possible when any data movement and transformation required to join multiple data assets have been performed.

• True
• False

Question 2: Self Service can use the following governance artefacts to refine a search in a catalog. (Choose all that apply)

• Data Protection Rules
• Business Terms
• Tags

Question 3: A data consumer should not be able to access data that has been identified as sensitive, where there is not a business need to do so.

• True
• False

Question 4: Which of the following statements about Self Service are ?

• Data consumers typically do not know how to manipulate the data
• Data Protection rules prevent a data consumer from inadvertently seeing data that is sensitive
• Creating multiple catalogs can partition data assets by their content and anticipated audience
• A data consumer needs to know SQL to join multiple data assets

Question 5: Data Consumers provide valuable input to data scientists by clarifying the combination of data assets and how they need to be transformed, prior to data movement being designed and implemented.

• True
• False

Module 5: Iterate DataOps – Use your data  Lesson 2 – Manage Movement & Integration

Question 1: You should define the use case at the outset of a Data Movement and Integration project to support a “Build It and They Will Come” strategy.

• True
• False

Question 2: Which of the following does not represent a data integration pattern:

• Data virtualization
• Data replication
• Data lineage
• Message-oriented movement
• Bulk/batch

Question 3: Which of the following is not a Data Movement and Integration Job Design consideration?

• Design for reusability
• Deployment models (e.g. Containers, Kubernetes Orchestration, OpenShift)
• Design for parallel processing
• Everything should be programmed in Python
• Design for job portability (build once and run anywhere)

Question 4: Hand coding generally provides a 10X productivity gain over commercial data integration software tooling.

• True
• False

Question 5: Which of the following is not an example of a message queuing system?

• Kafka
• VSAM
• Microsoft Azure Queues
• GCP PubSub
• AWS Simple Queue Service
• MQ

Module 5: Iterate DataOps – Use your data  Lesson 3 – Improve/Complete

Question 1: DataOps is a completely new methodology and it doesn’t learn anything from agile and devOps.

• True
• False

Question 2: Data consumers can first start to provide feedback to the current data sprint in the stakeholder review meeting.

• True
• False

Question 3: Which of the following assets or artifacts could be found in catalog?

• Code
• Business terms
• Data rules
• Source data
• Data lineage

Question 4: All issues need to be remediated before moving on to the next data sprint.

• True
• False

Question 5: Completing a data sprint involves publishing governed artifacts and data assets to a production environment.

• True
• False

Module 6: Improve DataOps  Review and Refine DataOps

Question 1: DataOps is a fixed process which should not be changed once defined.

• True
• False

Question 2: Improvements to the DataOps process could involve changes to

• Technology used in DataOps
• DataOps team roles and responsibilities
• Processes for ETL
• All of the above  

Question 3: Reviewing the Data classification phase involves reviewing how accurate the data mappings to the business terms are.

• True
• False

Question 4: Reviewing the Establish Baseline Process should include reviewing how effective the processes are for establishing a baseline for –

• External Regulatory requirements
• Organization maturity and Readiness
• Governance and Oversight
• All of the above

Question 5: KPIs are key in determining the effectiveness of all parts of the DataOps process.

• True
• False

DataOps Methodology Final Exam Answers

Question 1: What is a data strategy?

• An architecture and actionable roadmap along with an action plan
• A competitive publication to show that our organization is modern
• A plan to move all legacy data systems to the cloud

Question 2: Which of the following statements about Data Strategy are ?

• Whatever the type of data, it should only include internally produced data
• All types of data – both structured and unstructured need to be considered
• Volumes of data have increased hugely, but are now starting to stabilize
• Only business executives should be consulted in putting together a strategy

Question 3: Which of the following roles are active team members of any DataOps team?

• Chief Technology Officer
• Chief Data Officer
• Data Engineer
• Database Administrator
• Data Steward
• Data Architect
• Data Scientist

Question 4: Creating and maintaining business terms is a major responsibility of which following role?

• Data Engineer
• Data Quality Analyst
• Data Steward
• Data Scientist

Question 5: Business Priority should be the primary focus when deciding what the DataOps team should do.

• True
• False

Question 6: What is a data backlog?

• A bottleneck in the data pipeline
• A list of all data sources
• A prioritized set of requirements expressed as data tasks
• A plan to move all data into a catalog

Question 7: A Data Task should be prioritized by considering:

• The cost of providing the data
• The career advancement possibilities of solving business challenges
• The impact to sales from implementing the data pipeline
• All of the above

Question 8: KPIs are used to determine the progress and throughput of a DataOps data sprint.

• True
• False

Question 9: What are key components of DataOps toolchain?

• Continuous Deployment
• Communication
• Source Control
• All of above

Question 10: Who is responsible for creating DataOps toolchain? (Choose all that apply)

• Data Scientist
• Administrator
• DBA
• Data Engineer

Question 11: What is the primary objective of the Discover phase?

• Decide what the analytics team wants to have for lunch.
• Identify and locate the specific data elements required to accomplish an analysis
• Uncover the meaning of data column headers and how they relate to the underlying data.
• Gain an understanding of the business goals and KPIs of an analysis effort.

Question 12: Which description best defines taxonomy?

• Organizing data elements into meaningful structures.
• An IBM network protocol which reduces network latency.
• The art of preparing, stuffing, and mounting the skins of animals with lifelike effect.

Question 13: Which of the following is the objective of classification?

• To bring out points of similarity and dissimilarity among various groups.
• To present data in a simple, logical and understandable form.
• To condense the mass of data.
• All of the above

Question 14: A data quality framework consists of which of the following 4 phases:

• Profile
• Define
• Remediate
• Monitor
• Assess
• Deploy

Question 15: How does data classification affect defining policies?

• Inheritance, retention and probabilities
• Protection, reporting and inheritance
• Protection, accessibility and retention
• Retention, deletion and storage

Question 16: What impact does a highly sensitive classification have on a policy definition?

• Require data anonymization, de-identification, and masking
• Limit access to the data and/or require data masking
• Limit access to the data and make it unprintable
• No impact

Question 17: Self Service can use the following governance artefacts to refine a search in a catalog. (Choose all that apply)

• Data Protection Rules
• Business Terms
• Tags

Question 18: Which of the following statements about Self Service are ?

• A data consumer needs to know SQL to join multiple data assets
• Data Protection rules prevent a data consumer from inadvertently seeing data that is sensitive
• Creating multiple catalogs can partition data assets by their content and anticipated audience
• Data consumers typically do not know how to manipulate the data

Question 19: Which of the following does not represent a data integration pattern:

• Data virtualization
• Data replication
• Data lineage
• Message-oriented movement
• Bulk/batch

Question 20: Which of the following is not a Data Movement and Integration Job Design consideration?

• Design for reusability
• Deployment models (e.g. containers, Kubernetes orchestration, OpenShift)
• Design for parallel processing
• Everything should be programmed in Python
• Design for job portability (build once and run anywhere)

Question 21: Data consumers can first start to provide feedback to the current data sprint in the stakeholder review meeting.

• True
• False

Question 22: Which of the following could be found in catalog?

• Code
• Business terms
• Data rules
• Source data
• Data lineage

Question 23: All issues need to be remediated before moving on to the next data sprint.

• True
• False

Question 24: Improvements to the DataOps process could involve changes to

• Technology used in DataOps
• DataOps team roles and responsibilities
• Processes for ETL
• All of the above

Question 25: Reviewing the Establish Baseline Process should include reviewing how effective are the processes for establishing a baseline for –

• External Regulatory requirements
• Organization maturity and Readiness
• Governance and Oversight
• All of the above

Conclusion

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