Difference betweenDevOps and DataOps — Learn free

Self-check

Questions 1–10 of 10

1. DevOps focuses on development by software developers, quality and operations. What does DataOps focus on?
Question 1A. Mobile application performanceB. Server provisioning and version controlC. Source and target integrations, data transformation by data engineers, data quality and securityD. User interface designE. Network security only
2. While DevOps ensures there is no hindrance to a high-quality development cycle, what does DataOps ensure end users receive?
Question 2A. Faster application loginsB. More frequent software releasesC. Cheaper cloud storageD. Automated server patchesE. High-quality, trusted, ready-to-use data and actionable KPIs
3. DevOps aligns IT, operations and business team members to SPEED UP the process after every sprint. What does DataOps align roles and responsibilities for?
Question 3A. Faster collaborative work across teamsB. Reducing the number of sprintsC. Eliminating business involvementD. Replacing data engineers with developersE. Longer release cycles
4. DevOps automates server management, version control, configuration, testing and release management. Which activities does DataOps make sure are automated?
Question 4A. Code compilation and lintingB. User acceptance testing onlyC. Payroll and invoicingD. Data acquisition, integration, metadata management, self-service, data governance and cross-cloud operationE. Hardware procurement
5. DevOps works with stakeholders for real-time feedback after every sprint. How is DataOps' optimisation with stakeholders characterised?
Question 5A. Feedback-oriented optimisationB. Result-oriented optimisation, drawing regular insights from new data flowing inC. Cost-oriented optimisationD. Schedule-oriented optimisationE. Tool-oriented optimisation
6. DevOps goes for regular implementations for quick recovery from failures in agile mode. What does DataOps aim to fix quickly through regular implementations?
Question 6A. Server outagesB. Code merge conflictsC. User interface bugsD. Data quality issues and minimum metadata discoveryE. Network latency
7. In the DevOps workflow of builds, codes, unit test, performance, SIT, UAT, PROD deployment and business value, which step comes immediately after UAT?
Question 7A. PROD deploymentB. Performance testingC. SITD. Unit testE. Business value
8. Which sequence describes the DataOps workflow?
Question 8A. Codes, unit test, SIT, UAT, business valueB. Provision, configure, deploy, monitorC. Collect, label, train, serveD. Plan, build, release, runE. Data pipelining, transformations, data look and feel, business value
9. Which of the following is a DataOps concern rather than a DevOps concern?
Question 9A. Version controlB. Metadata managementC. Server managementD. Release managementE. Configuration automation
10. What is the final outcome that both the DevOps and DataOps workflows lead to?
Question 10A. PROD deploymentB. Data transformationC. Business valueD. Unit testingE. Data pipelining