AI & Big Data/Analytics
AI & Big Data/AnalyticsIndia: Talent Demand-Supply Analysis & IdentifyingUnique Job RolesJune 2018
KEY TRENDS1Trends and impact of AI and BD&A across Industries Impact of Startups on AI and BD&A ecosystemDEMAND SUPPLY ANALYSIS2Methodology for estimating Demand and Supply Global Demand for AI and BD&A Supply for AI andBD&A talent from IndiaAGENDAUNIQUE JOB ROLES3Methodology to identify unique roles List of Unique jobroles along with a description & technical skills Demandand Supply per job role4APPENDIX
Key TrendsAI & Big Data/Analytics (BDA) has the propensity to enable multiple use cases LOWHIGHIMPACT SCOREResearch is spread across various industry value chains. Industries such asEnterprise Software, Consumer Electronics and Automotive are focusing more onR&D whereas Retail and BFSI industry verticals are focusing more on customerjourney.PredictiveVehicleMaintenance The Healthcare market for AI is expanding at a 40% growth rate andexpected to reach 6 Bn by 2020. Global Clinical Data Analytics InHealthcare market is expected to reach 14 Billion USD by 2022 growing ata CAGR of 33% from 2017 Software-driven approach for drug discovery has increased accuracy,decreased cost and made R&D timelines shorter. In BFSI, a large number of companies (Mastercard, Sift Science etc.) areexploring Fraud detection solutions leveraging AI & BDA. Automated Trading has become widespread. As a result a lot of companiesare mushrooming to master the intricacies of stock tradingAutonomouscarsAssistedDrivingNote - *Impact score is the function of industry digital penetration, data access and availability for application of AISource : DRAUP Analysis as well as primary inputs from interviews with digital stakeholders and DRAUP’s existing customers33
Key Trends and thus, has a high potential to penetrate across industriesAI penetration in different industriesPenetration of AI across industries Sectors with recent andhigh impact AI/BDApenetrationEnterprise SoftwareSectors with mature AIpenetrationConsumer ElectronicsBFSISemiconductorThe retail industry (both online andoffline) has seen major AIinnovations such as store foot printoptimization, personal shoppingassistant and personalization,omnichannel shopping. BFSI, Healthcare and Automotiveindustries are witnessing amassive increase in the number ofAI applications due to greaterdigitization and access to dataMachine LearningEnabled HardwarePredictive diabetesmanagementAutonomous drivingIDEAL LIFECYCLEGROWTH Microsoft Cortana andIntelligent CloudRecommendationbased on photographsAutomotiveINTRODUCTIONIndustries such as EnterpriseSoftware and ConsumerElectronics have adopted AI-aidedtechnologies for some time andare focusing on implementingadvanced deep learning basedtechnologiesMachine Learningenabled AdvertisingAI based roboadvisory serviceRetailHealthcare MATUREStages of Industry lifecycle Note : Y – Axis depicts Intensity of AI applications incorporated in different industriesSource : DRAUP Analysis as well as primary inputs from interviews with digital stakeholders and DRAUP’s existing customers44
Key TrendsWhile G500 & Tech Giants dominate the Platforms and Infrastructure space, start-ups have amore significant presence in the Applications layerIntensityAPPLICATIONSEnterprise SoftwareSemiconductorsBFSIHealthcareRetailConsumer ElectronicsAutomotivePLATFORMSMACHINE INTELLIGENCEPlatforms – Tech Giants’ PlaygroundNLPCOMPUTER VISIONADASDEEP LEARNINGGESTURE CONTROLInfrastructure – G500 DominationINFRASTRUCTUREHardwareApplications – The Start-up ZoneData PlatformsStart-ups*G500 Companies - Top 500 R&D spendersGAFAM – Google, Amazon, Facebook, Apple, MicrosoftGAFAMG50055
Key TrendsGAFAM and leading start-ups have a significant lead over other top R&D leFuture PCiscoAirbusBoschOracleGAFAMLeveraging ML for network threatproducts – Cognitive ThreatAnalyticsTo release Xeon Phi processorline for AI applications- 400MinvestmentsInvested 5B in building an AIpowered Gigafactory.Intel 1B investment to establish theToyota Research Institute for AIVolkswagenFoxconnSize of the bubble indicates R&D spendAI and BD&A FocusStart-upsGAFAMG5001 : Investment in terms of Talent & Acquisition or Funding raised (for start-up)2 : Focus on Emerging vs. Traditional Technologies. Focus on Ecosystem creation and Platform adoption/maturity 500M investment in a 200member AI R&D lab in SilliconValley66
Key TrendsGlobal Service Providers have a large talent share of Big Data Analytics talent and haveaccelerated investments in building AI platforms / solutionsTCSKEY FOCUSAREASDEPLOYMENT& PLATFORMOVERVIEWSTATEDDOMINANTUSE CASES Reposition to serve ‘Heartof Business’ Technology / AI Advantage Plug and play deploymentrequiring customization andlearning Stand alone platform forcore infrastructure services End to end infra servicessuch as Infra blueprint Self healing Deployment PredictivemaintenanceWipro Broad based (BPM Focus) Plug and play deploymentrequiring customization andlearning Stand alone platformoffering a menu of multiplecognitive services Digital Virtual Assistants Prediction systems Robotics & DronesNote: Above analysis is based on the DRAUP’s proprietary engineering services deals databaseInfosys Broad based (includingengineering, ADM & BPM) Bespoke deploymentHCL Broad based (Infrastructureservices) Bespoke deployment AI capabilities bolt-on toexisting automationarchitecture (IIP, IKP, IAPframework) AI modules bolt-on toexisting automationplatform; collaboration withWatson, S-Now, Dynatrace,Splunk Engineering (aircraft floorbeam development) Detect and correct Infra andApp issues Forecasting as a service Watson power chat agent77
KEY TRENDS1Trends and impact of AI and BD&A across Industries Impact of Startups on AI and BD&A ecosystemDEMAND SUPPLY ANALYSIS2Methodology for estimating Demand and Supply Global Demand for AI and BD&A Supply for AI andBD&A talent from IndiaAGENDAUNIQUE JOB ROLES3Methodology to identify unique roles List of Unique jobroles along with a description & technical skills Demandand Supply per job role4APPENDIX
Methodology for estimating the Demand for AI and Big Data/Analytics talent12Employed TalentEmployed talent with AI and Big Data/Analytics skillsOpen Positions AnalysisOpen Job roles across AI and Big Data ifying skillsassociated with AIand BigData/AnalyticsEstimating talentinstalled acrosscompaniesTagging talent withcompany size,industry, locationIdentifying uniquejob roles across AIand BigData/AnalyticsMining openpositions inAI/BD&A from Jobportals and skillingplatforms for allcompaniesleveraging DRAUPMapping openpositions acrossgeographies,company sizes,IndustriesGlobal analysis includesG500 companiesService providersIndia analysis includesStart-upsGlobal CapabilityCenters (GCCs)Sources - Job portals/ platforms include LinkedIn, Naukri, Monster, Indeed, Kaggle & HackerearthNote - There are 3 size groups: Small (1-200 employees), Mid (201-1,000 employees) and Large ( 1,000 employees)Service providersStart-ups
Demand AnalysisThe demand for AI and Big Data/Analytics talent across G500 companies, Startups andService providers is estimated to be 1.2MY 2018Global Demand12Total Employed AI & BD/A talent pool 1.2 M 650,000India Demand1Total Employed AI & BD/A talent poolY 2018Y 2021 224k 390k 152,000 250,000G500 companies – Installed Talent 265,000GCC companies – Installed Talent 52,000 90,000Global Start-Ups – Installed Talent 270,000Start-Ups – Installed Talent 18,000 40,000Service Providers 120,000Service Providers 82,000 120,000Unmet AI & BD/A talent demand in2018 – Job Openings 515,000*G500 Companies - Top 500 R&D spenders. Note: All values are approximated2Unmet AI & BD/A talent demand in2018 – Job Openings 72,000 142,0001010
India EmployedTalentIn India, Bangalore has a significant lead over other cities in availability of AI and BD&A talentNCR15,300SkillsGCCsIT SPStartupTotalBig killsGCCsIT SPStartupTotalBig Data/Analytics700520017007,600AI15050050700 152,000SkillsGCCsIT SPStartupTotalBig ,800PuneGCCsIT SPStartupTotalBig 100BangaloreSkillsGCCsIT SPStartupTotalBig .100Note : DRAUP Talent module AnalysisAll Values are approximated 250,00020182021CAGR: 18%11,500MumbaiSkillsINDIA EMPLOYED TALENT8,300Others20,500HyderabadSkillsGCCsIT SPStartupTotalBig Data/Analytics60009400200017,400AI20009501503,100 India features amongst the toplocations for AI and BD&A globallyalongside US and China. The talent available in the US willbe expensive to meet the futuredemand for emerging skillsets.Organizations are hence reactingby globalizing their talent pool andengaging with local eco-systems.Top EmployersChennai19,500SkillsGCCsIT SPStartupTotalBig 111
India Un-metDemandIndia has the second largest unmet demand for AI and Big Data/Analytics, driven primarily bylarge service providers, GCCs and the start-up ecosystemNCR9,8004,000OthersSkillsTalentTop SkillsTalentBig Data/ Analytics7,900Big Data/ Analytics3,200AI1,900AI800INDIA UN-MET DEMAND 72,000 142,0002018CAGR: 25%10,400MumbaiTop SkillsTalentBig Data/ Analytics8,300AI2,100 Unmet demand for BD&A roles inIndia stands at 55K, primarilycoming from Indian serviceproviders7,000PuneTop SkillsTalentBig Data/ Analytics5,800AI1,2008,100HyderabadTop SkillsTalentBig Data/ Analytics6,300AI1,80026,500BangaloreTop SkillsTalentBig Data/ Analytics19,100AI7.400Note : DRAUP Talent module AnalysisAll Values are approximated20216,400ChennaiTop SkillsTalentBig Data/ Analytics5,200AI1,200 Demand for AI in India hasincreased over the past fewyears, driven primarily byStartups and Platformdevelopment by ServiceProviders Many MNC are also planning toestablish AI/Big Data/AnalyticsCOEs in India1212
Job OpeningsProjectionAbout 1 Million jobs are expected to be created in AI and Big Data/Analytics roles in 20216,00,000India Job Openings – 2018India Job Openings – 2021Big Data / Analytics – 55.5KArtificial Intelligence – 16.5KBig Data / Analytics – 68KArtificial Intelligence – 74K 510K5,00,000 450K4,00,000 415K Globally, Job Creation for AI and Big DataAnalytics roles will reach 960K in 2021with an average CAGR of 23%Global JobOpenings India is expected to grow at a faster rate( 25%) compared to the rest of the world3,00,0002,00,000 The Job Creation for Big Data/Analyticsroles will grow at a much lower rate ( 7%)compared with AI over the next 3 years1,00,000 100K020182019AI Job OpeningsNote : DRAUP Talent module Analysis20202021BD/A Job Openings1313
Methodology for estimating the Supply for AI and Big Data/Analytics talent in India12Employed TalentEmployed talent with AI and BigData/Analytics d withAI and BigData/AnalyticsEstimatingtalent installedacrosscompaniesTagging talentwith companysize, industry,locationAnalysed CompaniesGCCsIndian StartupsService Providers3Fresh Graduate AnalysisEstimating fresh graduates from Indianuniversities employable in AI and ss tiersand mappingenrolmentsdataStep-3Step-2Identification ofrelevancy ofstreams andlevels for AIand BD&ArolesEstimating theemployabilityratios andvalidating themwith SMEsAnalysis done for 40K UniversitiesSources: University Database: All India Survey of Higher Education (http://aishe.nic.in)National Institute Ranking Framework developed by Ministry of Human Resource Development (https://www.nirfindia.org/)Adjacent SkillsEstimating talent employed acrosscompanies in India which can be upskilledStep-1Identifyingneighbourhoodskills forAI/BD&A,validate themwith SMEsStep-2Mapping talentmined from jobportals/upskillingportals withthese skillsAnalysed CompaniesGCCsIndian StartupsService ProvidersStep-3Estimating thecoverage andvalidating tofinalize thetalent number
Supply AnalysisEmployable talent for AI and Big Data/Analytics present in India is estimated to be around 485KSupply in2021CAGR 285 k13%Indian Talent Supply in 2018 185KTalent Supplyfor AI and Big Data/Analytics from India in1.a20181Fresh Graduates fromUniversities 33KTalent supply graduating from Indian Universities 35 k1.5%2Installed Talent In India 152KTalent supply skilled in AI and Big Data/Analytics 250 k18%3Indian Startups 19KInstalled Talent in Indian Startups 40 k30%GCCs 52KInstalled Talent in GCCs in India 90 k20%Service Providers 81KInstalled Talent in ITeS Service Providers (SPs) 120 k13.5% 300KTalent that can be upskilled to work on AI and Big DataAnalytics 420 k12%Adjacent Talent Pool SupplyNote: While adjacent talent pool is 300K, they need to be trained in AI & BDA to satisfy the demand; All Values mentioned are approximated1515
India UniversityTalent SupplyUniversity Graduates: India produces about 33K employable fresh university talent annuallyTotal Employable University Talent: 33,100By Education LevelBy Education Streams2%4% About 84% of the total employabletalent pool is graduating with B.E andB.Tech. degrees.1%Integrated4%1%Ph.D.4% About 48% of the employable talentpool are graduating with computerscience and IT majorsDiploma1% Under-graduate students constitute73% of the total employable talent7%32%15%Post Graduate18% Post-graduate students constitute 18%of the employable talent for AI & BigData/AnalyticsUnder Graduate73%6%17%Computer Eng.Electronics Eng.Mechanical Eng.Computer ScienceMathsNote : DRAUP Talent module Analysis Ph.D enrolment is expected to grow at7% for the next 3 years; UG & PG isexpected to grow slower at 1% for thenext three years14%Electrical Eng.IT Eng.Computer ApplicationITStatistics Density of employable talent in tier 1 isthe highest Number of employable students in tier2 and tier 3 university are the samesince tier 3 universities witness a muchhigher enrolment1616
University Graduates: Tamil Nadu, NCR, Karnataka, Andhra Pradesh and Uttar Pradesh arethe top 5 hubs for fresh university graduates with AI & Big Data / Analytics skillsIndia UniversityTalent Supply The top 5 states (Tamil Nadu, DelhiNCR, Karnataka, Andhra Pradesh andUttar Pradesh) constitute 62% ofthe total employable talentgraduating from top 100 universities The Maturity of talent is higheracross Uttar Pradesh (39%) andKarnataka (38%), owing to a highernumber of PG/PHD/Integrated talent While Tamil Nadu produces themaximum number of employabletalent, the maturity is comparativelylow owing to a very high percentage(83%) of undergraduate talent. Uttar Pradesh and Karnataka have ahigher percentage of employabletalent graduating with Mathematicsand Statistics degreesNote: Top 100 universities across India considered for analysis1717
Installed Talent: Bangalore, Hyderabad and Chennai have the highest number of installed talentpool across GCCs, IT Service Providers & Start-upsGCCsIT Service ProvidersIndia EmployedTalentStart-upsTotal AI & Big Data / Analytics talent withinGCC firms in India is about 52,300. Big Data /Analytics HC: 40,970 AI HC: 11,330Total AI & Big Data / Analytics talent within ITservice providers in India is about 81,650. BigData / Analytics HC: 73,930 AI HC: 7,720Total AI & Big Data / Analytics talent within ITservice providers in India is about 18,190. BigData / Analytics HC: 16,470 AI HC: 1,720Over 45% of the AI & Big Data/Analytics talentacross GCCs is located in Bangalore.After Bangalore, Chennai is the 2nd biggest hubfor Big Data & Analytics for SPs.India constitutes about 10% of the global Big Data /Analytics talent and 4% of the global AI talentNCR and Hyderabad are the next toplocations, each employing 15% of the total AI& Big Data/Analytics talent pool.Within India, Bangalore commands about 75% ofthe Indian AI talent working across Start-ups,followed by Mumbai at 15%Among the start-ups, Big Data/Analytics talent ismore widely dispersed as it is a relatively matureskill compared to AI.Note : DRAUP Engineering module and Start-up module analysis1818
India has a pool of 300K engineers that can be upskilled to become AI and Big Data/AnalyticsprofessionalsIndia AdjacentTalentIT Service providers and GCCs have built digital capabilities that require talent adept with software development, databases and analyticsskills. Such talent has the required complementary skills and could be trained for AI & Big Data/Analytics requirementsIT Service ProvidersGCCs 170,000 to 190,000 110,000 to 130,000Trainable EmployeesTrainable Employees(Total Headcount in India: 1.5 million)(Total Headcount in India: 810,000)Top EmployersNote : DRAUP Engineering moduleTop Employers1919
FTE costs across global locations (in USD)The average FTE for talent (AI & Big Data /Analytics) in the Silicon Valley Bay Areacosts about 50% more than that of talent 0001,05,600Key Insights98,0001,41,3001,02,0001,31,1001,16,700With FTE cost for AI & Big Data / Analytics talent less than half of the FTE cost across globalhubs, India has huge potential to supply to the growing global demandCompensationAnalysisGlobally, Machine Learning talent costsaround 15-25% more than BigData/Analytics talentFor both AI and Big Data/Analytics, talent inIndia costs only around a third of the talentin Bay AreaAI2020
Demand & Supply Analysis 2018 300kKey InsightsIndia faces a talent gap of about 40,000 AI &Big Data / Analytics talent.The talent gap can be addressed by crossskilling adjacent talent throughcollaborations between corporations anduniversities and government initiatives. 40k 72kConsistent cross skilling of adjacent talentwould enable India to position itself as a AIand Big Data / Analytics hub that caters onlyto India demand but also to global demand 33KIndiaUnmet DemandEmployableGraduatesNote : DRAUP’s proprietary talent module analysisIndiaTalent GapAdjacentTalentAdvantages of hiring talent in India include higher quality at scale, lower cost compared to other globallocations and robust ecosystem comprising of Startups, Service Providers and GlobalCapability Centres (GCC).2121
KEY TRENDS1Trends and impact of AI and BD&A across Industries Impact of Startups on AI and BD&A ecosystemDEMAND SUPPLY ANALYSIS2Methodology for estimating Demand and Supply Global Demand for AI and BD&A Supply for AI andBD&A talent from IndiaAGENDAUNIQUE JOB ROLES3Methodology to identify unique roles List of Unique jobroles along with a description & technical skills Demandand Supply per job role4APPENDIX
BCG Analysis14 unique roles were determined across AI & BDA as part of the BCG analysis done in 20176 Big Data / Analytics roles12 Artificial Intelligence rolesBusiness AnalystBusiness AnalystAI Research Scientist – Image &VideoSolutions ArchitectSolutions ArchitectHardware Integration EngineerData IntegratorData ArchitectSoftware Engineer, Applications,Platforms, AIData ArchitectData ScientistSoftware Engineer, TestingData AnalystAI Research ScientistDevOps EngineerData ScientistAI Research Scientist - NLPInformation Security AnalystNote : DRAUP’s proprietary talent module was used to analyse jobs by job roles and skill type2323
MethodologyMethodology to determine unique job rolesPhase-1Phase-2Phase-3Phase-4Harvesting relevant job descriptionsExtracting technical & conceptualskillsClustering extracted skills to identify ExtractingjobdescriptionsFiltering jobdescriptionsCreatingtitle libraryClassifyingJDs basedon the titlelibrary,using arandomforestalgorithmUsingexisting skilllibrary tofine-tunespaCymodelUsingspaCy toextract listof technicalandconceptualskillsCleaning listof skills tiesbetweeneach skillusing aword2vecmodelDevelopingclusters ofskillscommonlyfoundtogetherusing kmeansclusteringOptimizing,tagging andvalidatingskill clustersIdentifyingunique jobrolesIdentifyingindustrySMEsQC and validation checkpoints1UsingspaCy tolocaterelevantsection(s)within JDManual QC on outputEach of the methodology phases have been detailed much further in the subsequent sectionsNote: Draup MethodologyManual QC on outputOutreachConductingprimaryinterviewsto 2424
MethodologyDeveloping a JD corpus for analysisStep No.Steps InvolvedHarvesting FunnelStep-1: JD ExtractionStep-2: Language Filtering Total number of job descriptions extracted(Sources: Indeed, LinkedIn & Glassdoor)28 million Job descriptions filtered on the basis of language Only JDs typed in English were filtered out from the total set15 millionTitles unique to datascienceStep-3: Title Library CreationTITLELIBRARY22Core Data ScienceTitles(Data Scientist, DataEngineer, Data Architect,Applied Scientist, ADASEngineer, etc.)Manual QC to testexhaustiveness oftitle libraryStep-4: JD Corpus Creation 600,000Title library developed using data extracted from LinkedIn, Naukri and IndeedTitles similar to datascience Adjacent /Intersecting Titles(Business Analyst, DataAnalyst, Financial Analyst,Risk Analyst, MarketingAnalyst, etc.)Titles that may createnoise-Negative Titles(Data Entry Operator,Data Center Technician,EHRS, Clinical Scientist,etc.) Relevant job descriptions filtered using a random forest algorithm that classified jobdescriptions on the basis of the title corpus2525
DeterminingUnique Roles18 unique roles were discovered in AI and Big Data/AnalyticsCaptureData and AnalyticsProcess 1OrganizeIdentify syntaxand semanticsIntegrateCollectIdentify datasourcesPrepareEnable accessto data sourcesIntegrateAggregate datainto data lakesLeverageAnalyseDevelop modelsto analyse dataDeployVisualizeCreatevisualizationsDecideMake decisionsusing dataDevelopDevelop datadriven appsAuxiliary Roles **SolutionArchitectChief Data OfficerAnalyst –Data MgmtHadoop AdministratorData WarehouseEngineerData StewardAnalyst – BI *VisualizationSpecialistData ScientistBreakdown ofRoles by Process 2Applied Data Scientist – SpeechApplied Data Scientist – VisionData ArchitectSoftwareEngineer gineerInfrastructureEngineerTest EngineerProductManager* Business intelligence analysts can be part of varied functions, e.g. ops, finance, marketing, or project planningAnalyst –InformationSecurity** Auxiliary roles include those which may not form part of the data science function, but are essential to productize data platforms or autonomous systems26Source: 1 H. Gilbert Miller, Peter Mork, “From Data to Decisions”, IT Professional, vol 15, no.1, pp. 57-59, Jan-Feb 2013, 2 Indeed, Naukri, LinkedIn, StackExchange, GitHub2626
Zinnov AnalysisZinnov Analysis for AI & Big Data / Analytics rolesRoles have been segregated in categories and 5 additional roles have been added. 1 role has been redefined, 2 roles have been merged7 Big Data / Analytics roles3 Artificial Intelligence rolesAnalyst – Data QualityManagementData ScientistAnalyst – BusinessIntelligenceApplied Data Scientist VisionInfrastructure EngineerData Warehouse EngineerApplied Data Scientist –SpeechProduct ManagerBig Data / HadoopAdministratorData Architect[DevOps EngineerRenamed]7 Auxiliary roles[AI ResearchScientist mergedwith Data Scientist]Solutions ArchitectSoftware Engineer –Autonomous SystemsLeadership roleSystems Integration Engineer– Autonomous SystemsChief Data OfficerTest EngineerData Steward[Hardware EngineerRedefined]Visualization SpecialistInformation Security - AnalystNew role addedRedefined roleMerged role with BCG analysis2727
List of unique job roles and definitions – Big Data / Analytics RolesUnique RoleDescriptionDemandTechnical or Conceptual Skills201820214,90010,0002003,000Data ArchitectDesigns andimplementing thetechnical architectureapache, azure, distribute systems, flume, google cloud, gradle,integrations, java j2ee,VisualizationSpecialistDevelopsvisualizations andanimationstableau, d3js, alteryx, python, rstudioAnalyst - DataQualityManagementMaintains and manages thequality of the databasedatabase architecture, relational databases, data cleaning, datamanipulation, tableau, power bi, excel49,00052,000Big Data / HadoopAdministratorSupports the hadoopinfrastructure and ensuresavailabilityhadoop, flume, YARN, mongodb, dynamodb, mapreduce, devops,hbase, hdfs, AWS3,2008,000Data WarehouseEngineerCreates data pipelines to moveand transform datahbase, amazon web service, kafka, spark, cassandra, dynamodb, flume,gradle, graph, hadoop, jmeter, json21,30041,000Analyst - BusinessIntelligenceAnalyzes data (usually structured)and generates descriptive insightsalteryx, cognos, dashboards, data interpretation, data manipulation,oracle sql, postgresql,107,400110,0005003,500Implements and enforcesdatabase architecture, relational databases, data quality, exceldata policies, processes,procedure, andstandards.Note : DRAUP’s proprietary talent module was used to analyse jobs by job roles and skill typeData Steward2828
List of unique job roles and definitionsLeadership RoleUnique RoleDescriptionChief Data OfficerResponsible forenterprise levelgovernance andutilization of data as anassetTechnical or Conceptual SkillsDemand--Artificial Intelligence RolesUnique RoleDescriptionDemandTechnical or Conceptual SkillsData ScientistAnalyzes and interpretsdata (both structured andunstructured) andgenerates prescriptiveand predictive insightsClassification, clustering, decision trees, dimensionality reduction, logisticregression, SVM, natural language process, predictive analytics,Applied DataScientist - VisionDevelops algorithms forvision-based applicationssuch as image or objectrecognition applications.OpenCV, Tensorflow, Pandas, 3D Modelling, Adaptive Thresholding, Caffe,Convolutional Neural NetworkApplied DataScientist – SpeechDevelops algorithms forconversational interfacessuch as chatbotsDialogflow, API.ai, Wit.ai, Microsoft Bot Framework, Bayes Rule, BidirectionalRNN, Chomsky HierarchyNote : DRAUP’s proprietary talent module was used to analyse jobs by job roles and skill type2018202136,500129,00080025,000 50010,0002929
List of unique job roles and definitions – AuxiliaryUnique RoleDescriptionTechnical or Conceptual SkillsSolutions ArchitectResponsible for architecture anddesign implementations for dataplatforms and autonomous systemsSOA, Redshift, EC2, EMR, Shell Scripting, Security Design, Athena, Glue, Elastic SearchInfrastructureEngineerEngineers and maintains large scaleenvironments specifically for solvinglarge scale data science and AIproblemsAWS, Azure, GPU hardware, Docker, Kubernetes, server systems, networking, securityinfrastructureProduct ManagerIdentifies customer and marketrequirements, and develops theproduct roadmapProduct Roadmap, Wireframe, Bootstrap, Distributed Systems, Tableau, Data modellingSoftware Engineer AutonomousSystemsDevelops the software backend forautonomous systemsKalman filtering, Python, C, C , Linux, Matlab, probabilistic filtering, pose estimation, LIDARprocessingAutonomousSystems IntegrationEngineerIntegrates hardware and softwareelements of autonomous systems,ensuring safetyDFMEA, HARA, FTA, kalman filtering, pose estimation, inertial measurement, system design,hardware designTest EngineerTests data platforms andautonomous systemsSelenium, JUnit, regression testing, load testing, black box testing, sanity testing, smoke testingIdentifies potential threats andanti virus, bluecoat, digital forensics, firewall management, fisma, gsec, incident responsevulnerabilities, and developing solutionsto interveneNote : DRAUP’s proprietary talent module was used to analyse jobs by job roles and skill typeAnalyst Information Security3030
KEY TRENDS1Trends and impact of AI and BD&A across Industries Impact of Startups on AI and BD&A ecosystemDEMAND SUPPLY ANALYSIS2Methodology for estimating Demand and Supply Global Demand for AI and BD&A Supply for AI andBD&A talent from IndiaAGENDAUNIQUE JOB ROLES3Methodology to identify unique roles List of Unique jobroles along with a description & technical skills Demandand Supply per job role4APPENDIX
Methodology for estimation of global talent across organizationTOTAL TALENTDEMAND[A] INSTALLEDTALENT POOL[B] OPEN POSITIONSANALYSISStep 1: Skill AnalysisOverall EmployableTalent Pool GloballyTalent pool withAI/DS skillsInstalled inGlobalOrganizationsList of skills associatedwith AI/DS obtained fromprimary interviews andinternal Zinnov researchAll AI/DS employees andtheir companies Globallyobtained by mining jobplatforms [1]Step 2: Company AnalysisAll companies extractedare tagged with size,location[2] and industryverticalCoverage ratiosestimated for sizegroups[3] and industryverticals[4] based onprimary interviewsCoverage ratios applied oneach company to estimateAI/DS talent supply percompanyStep 3: Estimation of Talent Pool[A] INSTALLED TALENT POOLInstalled Talent Pool Sum of talent Installed inall companies[1] Job platforms include LinkedIn, Naukri, Monster and Indeed[2] Location includes both the city and the corresponding hotbeds across globe[3] There are 3 size groups: Small (1-200 employees), Mid (201-1,000 employees) and Large ( 1,000 employees)[4] List of industry verticals include ITeS, ER&D and SPD3333
Methodology for estimation of Open positions globallyTOTAL TALENTDEMANDMining OpenPositions forCompanies GloballyDemand GrowthRate EstimationProjectingFuture Demand[A] INSTALLEDTALENT POOL[B] OPEN POSITIONSANALYSISList of skills associatedwith AI/DS obtained fromprimary interviews andinternal Zinnov researchGlobal AI/DS openpositions in the past 3years obtained by miningjob platforms [1]Quarterly growth for
India has the second largest unmet demand for AI and Big Data/Analytics, driven primarily by large service providers, GCCs and the start-up ecosystem NCR Others Hyderabad Pune Mumbai Bangalore Chennai Top Skills Talent Big Data/ Analytics 5,800 AI 1,200 Top Skills Talent Big Data/ Analytics 19,100 AI 7.400 Top Skills Talent Big Data/ Analytics .
tdwi.org 5 Introduction 1 See the TDWI Best Practices Report Next Generation Data Warehouse Platforms (Q4 2009), available on tdwi.org. Introduction to Big Data Analytics Big data analytics is where advanced analytic techniques operate on big data sets. Hence, big data analytics is really about two things—big data and analytics—plus how the two have teamed up to
big data analytics" To discuss the in-depth analysis of hardware and software platforms for big data analytics The study only focused on the hardware and software platform for big data analytics. The review is centered on the impact of parameters such as scalability, data sizes, resources availability on big data analytics. However, the
Q) Define Big Data Analytics. What are the various types of analytics? Big Data Analytics is the process of examining big data to uncover patterns, unearth trends, and find unknown correlations and other useful information to make faster and better decisions. Few Top Analytics tools are: MS Excel, SAS, IBM SPSS Modeler, R analytics,
example, Netflix uses Big Data Analytics to prescribe favourite song/movie based on customer‟s interests, behaviour, day and time analysis. 3. Python For Big Data Analytics 3.1 . Advantages. of . Python for Big Data Analytics Python. is. the most popular language amongst Data Scientists for Data Analytics not only because of its ease in
The Rise of Big Data Options 25 Beyond Hadoop 27 With Choice Come Decisions 28 ftoc 23 October 2012; 12:36:54 v. . Gauging Success 35 Chapter 5 Big Data Sources.37 Hunting for Data 38 Setting the Goal 39 Big Data Sources Growing 40 Diving Deeper into Big Data Sources 42 A Wealth of Public Information 43 Getting Started with Big Data .
Retail. Big data use cases 4-8. Healthcare . Big data use cases 9-12. Oil and gas. Big data use cases 13-15. Telecommunications . Big data use cases 16-18. Financial services. Big data use cases 19-22. 3 Top Big Data Analytics use cases. Manufacturing Manufacturing. The digital revolution has transformed the manufacturing industry. Manufacturers
The process of analyzing big data to extract useful information and insights is usually referred to as big data analytics or big data valu e chain [6], which is considered as one of the key enabling technologies of smart cities [7, 8, 9]. However, big data complexities comprise non-trivial challenges for the processes of big data analytics [3].
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