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DataOps is defined by Gartner as “a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and consumers across an organization. Much like DevOps, DataOps is not a rigid dogma, but a principles-based practice influencing how data can be provided and updated to meet the need of the organization’s data consumers.
” The DataOps Methodology is designed to enable an organization to utilize a repeatable process to build and deploy analytics and data pipelines. By following data governance and model management practices they can deliver high-quality enterprise data to enable AI. Successful implementation of this methodology allows an organization to know, trust and use data to drive value.
In the DataOps Methodology course you will learn about best practices for defining a repeatable and business-oriented framework to provide delivery of trusted data. This course is part of the Data Engineering Specialization which provides learners with the foundational skills required to be a Data Engineer.
Module 1: Establish DataOps – Prepare for operation
Lesson 2 – Establish Data Strategy
Question: 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.
Question: What is a data strategy?
Question: Implementing a data strategy should always result in cost savings in the year the plan is realized.
Question: Which of the following statements about Data Strategy are correct?
Question: Data Governance is a key part of executing a data strategy.
Lesson 3 – Establish Team
Question: A DataOps team consists of members mostly from IT departments.
Question: Which of the following roles are active team members of any DataOps team?
Question: Creating and maintain business terms is a major responsibility of which following role?
Question: Only Chief Data Officer can update the KPIs for a data sprint.
Question: DataOps relies heavily on the use of automation, so that communication among team members is not necessary.
Module 2: Establish DataOps – Optimize for operation
Lesson 1 – Establish Toolchain
Question: DataOps toolchain helps you deliver quality data slowly.
Question: DataOps Toolchain and DevOps are the same thing.
Question: DataOps Toolchain can work without DataOps API(s).
Question: What are the key components of DataOps Toolchain?
Question: Who is responsible for creating DataOps Toolchain? (Choose all that apply)
Lesson 2 – Establish Baseline
Question: Data Management is the same as Information Governance.
Question: What is the most costly result from an external influence to an organization?
Question: Reference data is defined as data used as a permissible value within a data field.
Lesson 3 – Establish Business Priorities
Question: Business Priority should be the primary focus when deciding what the DataOps team should do.
Question: What is a data backlog?
Question: A prioritized data backlog will reduce the time taken to start the next DataOps iteration.
Question: A Data Task should be prioritized by considering:
Question: KPIs are used to determine the progress and throughput of a DataOps data sprint.
Module 3: Iterate DataOps – Know your data
Lesson 1 – Discover
Question: 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.
Question: What should you do if you identify gaps or mismatches in the data required for the analysis?
Question: You should trace the linage of data elements to be used for analysis to make sure they come from a trusted source.
Question: What is the primary objective of the Discover phase?
Question: 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.
Lesson 2 – Classify
Question: 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.
Question: Which description best defines taxonomy?
Question: A single data element can be placed into an unlimited number of data domains.
Question: Which of the following is the objective of classification?
Question: You should design workflows which are specific to the classification tool you are using.
Module 4: Iterate DataOps – Trust your data
Lesson 1 – Manage Qualities & Entities
Question: Data quality is data accuracy.
Question: All data across the enterprise should have the same data quality.
Question: A data quality framework consists of which of the following 4 phases:
Question: When assessing data quality, you only need the data set containing the data, metadata is optional.
Lesson 2 – Manage Policies
Question: How does data classification affect defining policies?
Question: What impact does a highly sensitive classification have on a policy definition?
Question: What are the most common state, country or regional regulations affecting personal information?
Question: Once policies have been defined affecting the data, rules must be enforced to act.
Module 5: Iterate DataOps – Use your data
Lesson 1 – Self Service
Question: Self Service of data is only possible when any data movement and transformation required to join multiple data assets have been performed.
Question: Self Service can use the following governance artefacts to refine a search in a catalog. (Choose all that apply)
Question: 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.
Question: Which of the following statements about Self Service are correct?
Question: 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.
Lesson 2 – Manage Movement & Integration
Question: 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.
Question: Which of the following does not represent a data integration pattern:
Question: Which of the following is not a Data Movement and Integration Job Design consideration?
Question: Hand coding generally provides a 10X productivity gain over commercial data integration software tooling.
Question: Which of the following is not an example of a message queuing system?
Lesson 3 – Improve/Complete
Question: DataOps is a completely new methodology and it doesn’t learn anything from agile and devOps.
Question: Data consumers can first start to provide feedback to the current data sprint in the stakeholder review meeting.
Question: Which of the following assets or artifacts could be found in catalog?
Question: All issues need to be remediated before moving on to the next data sprint.
Question: Completing a data sprint involves publishing governed artifacts and data assets to a production environment.
Module 6: Improve DataOps
Question: DataOps is a fixed process which should not be changed once defined.
Question: Improvements to the DataOps process could involve changes to
Question: Reviewing the Data classification phase involves reviewing how accurate the data mappings to the business terms are.
Question: Reviewing the Establish Baseline Process should include reviewing how effective the processes are for establishing a baseline for –
Question: KPIs are key in determining the effectiveness of all parts of the DataOps process.
Final Exam
Question: What is a data strategy?
Question: Which of the following statements about Data Strategy are correct?
Question: Which of the following roles are active team members of any DataOps team?
Question: Creating and maintaining business terms is a major responsibility of which following role?
Question: Business Priority should be the primary focus when deciding what the DataOps team should do.
Question: What is a data backlog?
Question: A Data Task should be prioritized by considering:
Question: KPIs are used to determine the progress and throughput of a DataOps data sprint.
Question: What are key components of DataOps toolchain?
Question: Who is responsible for creating DataOps toolchain? (Choose all that apply)
Question: What is the primary objective of the Discover phase?
Question: Which description best defines taxonomy?
Question: Which of the following is the objective of classification?
Question: A data quality framework consists of which of the following 4 phases:
Question: How does data classification affect defining policies?
Question: What impact does a highly sensitive classification have on a policy definition?
Question: Self Service can use the following governance artefacts to refine a search in a catalog. (Choose all that apply)
Question: Which of the following statements about Self Service are correct?
Question: Which of the following does not represent a data integration pattern:
Question: Which of the following is not a Data Movement and Integration Job Design consideration?
Question: Data consumers can first start to provide feedback to the current data sprint in the stakeholder review meeting.
Question: Which of the following could be found in catalog?
Question: All issues need to be remediated before moving on to the next data sprint.
Question: Improvements to the DataOps process could involve changes to
Question: Reviewing the Establish Baseline Process should include reviewing how effective are the processes for establishing a baseline for –
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