Devops提升数据全价值链的交付能力

1、Devops提升数据全价值链的交付能力技术创新，变革未来目录2020Software vs. Data and DevOps vs.DataOpsValue Delivery: from Data to ProductDataOps+ for Experiment SystemGeorge F. Colony (CEO Forrester Research)“In the future, ALL companies will be SOFTWARE companies”DevOps is Reshaping Software Engineering2020Development + Opera

2、tionsThe 3rd revolutionary movement in Software Engineering“DevOps is a set of practices intended to reduce the time between committing a change to a system and the change being placed into normal production, while ensuring high quality.”DevOps is the first productive force in contemporary software

3、industry2020“In the future, ALL companies will be DATA companies”What is DataOps?DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics. -WikipediaDataOps is an agile approach to designing, implementi

4、ng and maintaining a distributed data architecture that will support a wide range of open source tools and frameworks in production. The goal of DataOps is to create business value from big data. -DataOps is the practice of operationalising data management and integration to rapidly meet new busines

5、s demands for data, and to deliver continuously with confidence, in a world of fragmented data and ceaseless change. -DataOps is the hub for collecting and distributing data, with a mandate to provide controlled access to systems of record for customer and marketing performance data, while protectin

6、g privacy, usage restrictions and data integrity. -DataOps is the orchestration of people, processes, and technology to deliver trusted, business-ready data to data citizens, operations, applications and artificial intelligence (AI) fast. -2020From DevOps to DataOps2020DevOps is the offspring of agi

7、le software development, which is short of data development. DataOps is inspired by DevOps, which centered around the strategic use of data, as opposed to shipping software.DataOps is the derivative and development of DevOps in the data era. Supplements include new toolData Middle Platform, new role

8、sData Scientist and Data Engineer.DataOps is NOT just DevOps for Data!DevOps vs. DataOps2020DataOpsFocusDataTransformationIT to Business User and DevelopmentBenefitBusiness-ready (trusted, high quality) data available for use fastAutomation pointsMetadata managementData curationSelf-service interact

9、ionData governance and multi-cloud data integrationMaster data managementDevOpsFocusApplication and Software DevelopmentTransformationIT to DevelopmentBenefitFaster production and deploymentAutomation pointsConfiguring networks and environmentsTestingRelease managementProvisioning and configuration

10、of machines and serversPerformance monitoringVersion controlContents2020Software vs. Data and DevOps vs.DataOpsValue Delivery: from Data to ProductDataOps+ for Experiment SystemValue ChainA value chain refers to the activities that take place within a company in order to deliver a valuable product t

11、o market.“A value chain is the full range of activities including design, production, marketing and distribution businesses conduct to bring a product or service f rom conception to delivery. ”2020What missing for a complete value chain?2020DataOps OfferingsNever Used2020RarelyOftenSometimesFeature

12、Usage in IT SystemsAlwaysHow does DataOps helpEvidence BasedInnovationAutomationCollectionAd Hoc Use2020Data Driven OrganisationExperiment SystemContinuous DeploymentContinuous IntegrationAgile DevelopmentTraditional DevelopmentResponse Speed to Change2020Contents2020Software vs. Data and DevOps vs.

13、DataOpsValue Delivery: from Data to ProductDataOps+ for Experiment SystemOperationsDevelopmentBusiness Strategy & PlanningImprovements & InnovationBig DataArtificial IntelligenceFinTechBlockchain赋能 DevOps DevOps+Conti赋nu能ous SE2020What is DevOps+?Validated Learning for Complete Value Chain“ to learn

14、 how to build a sustainable business. This learning can be validated scientifically by running frequent experiments that allow entrepreneurs to test each element of their vision.”“Validated learning is the process of demonstrating empirically that a team has discovered valuable truths2020aboutastart

15、upspresentandfuturebusinessprospects.”“It is more concrete, more accurate, and faster than market forecasting or classical business planning.”Trend of Release Frequency2020ProductR&D OrganisationFeature Setfeature backlogGap Analysisdeploy featureswhats next featureprioritised featuresexpected behav

16、ioractual feature behavioralternative featureabandon featuresMVFExperiment SystemDataOps2020extended featureMVP (minimal viable feature)is a small portion (e.g., 10% to 20%) of the feature functionality but assessed to provide the most value to the customer or the company and consequently will affec

17、t the actual system and customer behavior the mostinstrumentation to the code to allow for collection of the data concerning the aspects of system and customer behavior when defining the expected behaviorGap Analysissufficient data concerning the actual behavior collected to draw statistically relev

18、ant conclusions, the team can assess the gap between expected and actual behaviorthe delta between the reference and the actual behavior can be assessed to determine if an actual change is attributed to the feature slice just addedthe team develop hypotheses concerning the gap, either to continue /

19、extend the functionality, or to remove / abandon feature with an alternativeassessing the limited value provided to the customers, the system and the company developing the feature versus the cost of having the feature present in the systemExperiment System2020Customer Feedback Techniques2020Wrap Up2020DevOps and DataOps share a very similar principleDataOps for rapid delivery of data value (only)DevOps+ extends and go beyond DevOps (not limited