Thanks to innovative techniques, our Data Fabric differentiates itself by:auniquedataintegrationpattern:easydataintegrationbyautomateddatablending(withouthavingtoknowschemas upfront).Withthis,theDataFabricexcelsincomplexinfrastructures(blendsdatafromacrosshundredsandeven thousands of data sources fully automated!)creating high-quality data from any source (also unstructurered data)automatedstreamingofhigh-qualitydatasetsthatmatchesyourquery,toyourownapplications&platforms(data modelling)enrichingdatawith(external)referencesources,normalisingdataandtheabilitytowritebacktoyourdatasources. This makes data curation & normalisation of your data sources (e.g. MDM & ERP systems) possiblesupportforanydataprotectionregulationandpoliciesincombinationwithanonymisationandpseudonymisationof 115differentPII’sthatareautomaticallyidentified.Eachcountrycanapplyitsowndataprotectionpolicies.TheData Fabriccanbesetupinsuchawaythatdatawillnotcrossbordersandthatspecifictypesofdataarenotbeing blendeddata insights and automation of data management tasks and much more“Dataintegration(49%)anddatapreparation(37%)areamongthetopthreetechnologiesthatorganizations would like to automate by 2020.”Ehtisham Zaidi, Eric Thoo, Guido De Simoni, Mark Beyer - Gartner -TheDataFabriccanautomatenearlyeverything;theDataFabricis100%focussedonstreamliningeverypartofthedata process by i.a.:Reinforcement LearningSimple Annotation and LabellingGraph-based Data Stewarding
Crawling data fully automated from internal and external data resources
The Data Fabric is a data integration platform (iPaaS) capable of delivering Data as a Service (DaaS).The Data Fabric includes over 220 out-of-the-box integrations (connectors). Crawlerscollectfullyautomatedallcontentfromstructureddata,unstructureddataandimage-onlyfilesfromanyinternal source(includinglegacysystems).Datafromexternalsourcescanbecollectedaswell(e.g.dataenrichment/records completion). Afterapplyinginnovativetechniquestothedatacollected,high-qualitydataisgeneratedandmanyusecases can be dealt with.
Blending and cleansing data: creating high-quality data
“How good is your data quality?”Duringthedatacrawlingprocess,thecollecteddatagetscleansedfullyautomated.Byi.a.‘naturallanguageprocessing’, triangulationandfuzzymergingtechniques,datawillbeorganised,de-duplicatedandenriched,datarelationsputin placeanddatawillbeblended.Inaddition,18 data quality metricsandarangeofalgorithmsensuresthathigh-qualitydata is created.Theseautomateddatapreparationstepsarethefirststepsallowingyourorganisationtoturnyourdataintoinformationand thefirststepstodatacurationandnormalisation.TheDataFabriciscapabletowritebacktoover350sources.After verificationbyadatastewardordataengineer,datacurationanddatanormalisationatyourdatasources(e.g.MDM& ERP systems) can be applied.
July 25, 2019: Gartner states in their “Hype Cycle Report for Enterprise Information Management” the following:"DataandanalyticsleaderssuchasdataarchitectsshouldconsiderDaaS-stylearchitectureasone optiontoexpandandcomplementtheexistingdatamanagementstrategyandinfrastructure.…DaaS canserveasameansofaddressingthegrowingvarietyofdata,andthisissometimesrepresentedaspartof a new value statement for building this type of infrastructure.”September11,2019:Gartnerconcludesin“ModernDataandAnalyticsRequirementsDemandaConvergenceofData Management Capabilities” the following:“Duetochangingrequirements,moderndataandanalyticsusecasesneedaportfolioofcapabilitiesthat cannotbefulfilledbyexisting,stand-aloneproducts.Dataandanalyticsleadersmustinvestinnewdata management solutions that leverage aggregated and integrated capabilities.”TheDataFabricdeliversDaaS:high-qualitydatafromtheDataFabriccanbe streamedviapushandpulltechniquesto DataWarehouses,PowerBI,Google BigQueryoranytoolthatneedscleansed anddeduplicateddata.TheDataFabric canofferextrafunctionalitiesfor platformssuchasAzure,Hadoopand IBMdatalake.TheDataFabricalso features“Keep Me In The loop”,unified viewandmore.TheDataFabricfitsin anyinfrastructurewhilemaking processesmoreefficientandsavingtime and money.
Data insight and data management
Whilecrawlingforcontent,theDataFabricalsoincludestheaccessrights,metadataandlogfiles.Thisenablesyouto apply(automated)datamanagementtaskswhilegainingdatainsights.Thismakesgovernance,riskmanagementand compliance support possible in several areas, including:Automatic classification of documents via machine learning techniquesMonitoring ‘data leaks’ for example given, documents categorised as sensitiveAcquiringinsightsregardingpersonallyidentifiableinformation.Reportscanbegeneratedandinformation providedaboutthedatalocationswithouthavingtoinvolveanyotherdepartment.Datacanbeanonymisedor pseudonymised fully automated when data is streamed for analysis (BI, data science, etc.).Fullyautomatedapplicationofdataretentionpolicies.‘Datalifecyclemanagement’(DLM)canbefullyautomatedor applied after an approval loop by data owners.
Data becomes information
Throughdataintegration,thecleansing,blendingandenrichmentsofdata,thedashboardsandalerts,thedataanalysis andBIpossibilities,theunique'unifiedview',theabilitytoaddexternaldatasources,therealtimeprocessingofinformation thatbecomesimmediatelyavailableforknowledgeworkers,managementordatascientists,beingabletofindaneedleina haystack, acquiring data insight and more, data will be converted into information.BecausetheDataFabriccanestablishrelationshipsbetweendataandisstrongin‘datalineage’,notonlyapplicationsin theareaofunstructureddataareonthehorizon,butalsoonstructureddata.Establishingrelationsbetweenrecordsand analysingthemispossible,examplegivenforERPsystems.Thisallowstherealisationofunprecedentedinsights.By processingexternaldatasources,manyotherapplicationsarealsopossibleincluding‘knowyourcustomer’(KYC)anda 360-degree view of employees and organisations.TheDataFabricisofgreatvalueforboardofdirectorsandmanagement,marketing,HRM,recruitment,data scientists & analysts, IT and knowledge workers amongst other people and departments.IfyouwouldliketoobtainmoreinformationaboutourDataFabricorifyouhaveanyquestionsaboutthemanyotheruse cases the Data Fabric has to offer you, please feel free to contact us!
The Data Fabric summarised
1.The Data Fabric creates a unique, solid, flexible and scalable data foundation that fits in any (complex) infrastructure2.Innovative techniques ensure the creation of high-quality data without having to know how data (records) could blend3.(High quality) data sets matching a defined query, can be streamed to other applications and platforms (push and pull)4.Writingbacktooriginalsources(withinterventionofadatasteward,dataengineerordataprotectionofficer)is supported5.Bycombiningtheintegratedfunctionalitieslikedatalineage,metadatacollectionandcreation,datacatalog,streaming &writebackcapabilities,machinelearningcapabilities,automatedfrauddetectionandmore,manydatarelateduse cases can be dealt with and solved.As such, the Data Fabric can be called a Smart Data Fabric!WiththeDataFabric,youcangetinsightsandcontroloveryourdataandinformationoutofyourvaluabledata,without changing your way of working and while reusing the infrastructure you already have invested in.TheDataFabricincreasesefficiencyinmultiplewaysandwillsaveyoulotsoftimeandmoney.Withthis,theDataFabric has a high ROI. We are happy to make this visible for your organisation by mapping several value metrics.There is much more to tell about the Data Fabric’s possibilities and its innovative techniques. Feel free to contact us.+91 74 066 24 888 datafabric@s10group.com
Data Integration
Data Management
Data Preparation
Data Governance
Data Cleaning
Data Catalog
Data Lineage
Data Training
Data Intelligence
Data Mart
Data Access
Data Workflow
Data quality is analysed by 18 data quality metrics. By adjusting the levels, data quality can be improved to the preferred levels
Dataset from query “Customer Data” is automatically streamed for predictive analysis
Over 220 out-of-the-box integrations have been developped
What is the Smart Data Fabric and how does it work?
Data AccuracyData ValidityData CompletenessData RelevanceData UniformityData StewardshipData ConsistencyData AccountabilityData Connectivity
1.2.3.4.5.6.7.8.9.
Data ReliabilityData QualityData TimelinessData IntegrityData ConformityData FlexibilityData Staleness Data AvailabilityData Usability
10.11.12.13.14.15.16.17.18.
18 data quality metrics
Blending and deduplication of data(simple example)
Datacanbeprovidedondemandtoauser. Qualitydataisrealisedinacentralplaceby cleansingandenrichingdata.Thisqualitydata canbeofferedtodifferentsystems,applications orusers,irrespectiveoftheirlocation.DaaS solutions provide advantages like:Noextensiveknowledgeoftheunderlying data is requiredCost-effectivenessData quality is improved
On-premiseDatabasesEnterprise systemsCustom apps
Use cases…
The Smart Data Fabric’s pillars
Data Fabric’s differentiation by innovation
Thankstoinnovativetechniques,ourDataFabricdifferentiates itself by:auniquedataintegrationpattern:easydataintegration byautomateddatablending(withouthavingtoknow schemasupfront).Withthis,theDataFabricexcelsin complexinfrastructures(blendsdatafromacross hundredsandeventhousandsofdatasourcesfully automated!)creatinghigh-qualitydatafromanysource(also unstructurered data)automatedstreamingofhigh-qualitydatasetsthat matchesyourquery,toyourownapplications&platforms (data modelling)enrichingdatawith(external)referencesources, normalisingdataandtheabilitytowritebacktoyourdata sources.Thismakesdatacuration&normalisationof your data sources (e.g. MDM & ERP systems) possiblesupportforanydataprotectionregulationandpoliciesin combinationwithanonymisationandpseudonymisation of115differentPII’sthatareautomaticallyidentified. Eachcountrycanapplyitsowndataprotectionpolicies. TheDataFabriccanbesetupinsuchawaythatdatawill notcrossbordersandthatspecifictypesofdataarenot being blendeddatainsightsandautomationofdatamanagementtasks and much more“Dataintegration(49%)anddatapreparation (37%)areamongthetopthreetechnologiesthat organizations would like to automate by 2020.”Ehtisham Zaidi, Eric Thoo, Guido De Simoni, Mark Beyer - Gartner -TheDataFabriccanautomatenearlyeverything;theData Fabricis100%focussedonstreamliningeverypartofthedata process by i.a.:Reinforcement LearningSimple Annotation and LabellingGraph-based Data Stewarding
Crawling data fully automated from internal and
external data resources
TheDataFabricisadataintegrationplatform(iPaaS)capable of delivering Data as a Service (DaaS).TheDataFabricincludesover220out-of-the-boxintegrations (connectors). Crawlerscollectfullyautomatedallcontentfromstructured data,unstructureddataandimage-onlyfilesfromanyinternal source(includinglegacysystems).Datafromexternalsources canbecollectedaswell(e.g.dataenrichment/records completion).Afterapplyinginnovativetechniquestothedata collected,high-qualitydataisgeneratedandmanyusecases can be dealt with.
Blending and cleansing data: creating high-quality
data
“How good is your data quality?”Duringthedatacrawlingprocess,thecollecteddatagets cleansedfullyautomated.Byi.a.‘naturallanguage processing’,triangulationandfuzzymergingtechniques,data willbeorganised,de-duplicatedandenriched,data relationsputinplaceanddatawillbeblended.Inaddition,18 data quality metricsandarangeofalgorithmsensuresthat high-quality data is created.Theseautomateddatapreparationstepsarethefirststeps allowingyourorganisationtoturnyourdataintoinformation andthefirststepstodatacurationandnormalisation.The DataFabriciscapabletowritebacktoover350sources. After verificationbyadatastewardordataengineer,datacuration anddatanormalisationatyourdatasources(e.g.MDM&ERP systems) can be applied.
July25,2019:Gartnerstatesintheir“HypeCycleReportfor Enterprise Information Management” the following:"Dataandanalyticsleaderssuchasdata architectsshouldconsiderDaaS-style architectureasoneoptiontoexpandand complementtheexistingdatamanagement strategyandinfrastructure.…DaaScan serveasameansofaddressingthegrowing varietyofdata,andthisissometimes representedaspartofanewvaluestatementfor building this type of infrastructure.”September11,2019:Gartnerconcludesin“ModernDataand AnalyticsRequirementsDemandaConvergenceofData Management Capabilities” the following:“Duetochangingrequirements,moderndata andanalyticsusecasesneedaportfolioof capabilitiesthatcannotbefulfilledbyexisting, stand-aloneproducts.Dataandanalytics leadersmustinvestinnewdatamanagement solutionsthatleverageaggregatedand integrated capabilities.”TheDataFabricdeliversDaaS:high-qualitydatafromthe DataFabriccanbestreamedviapushandpulltechniquesto DataWarehouses,PowerBI,GoogleBigQueryoranytoolthat needscleansedanddeduplicateddata.TheDataFabriccan offerextrafunctionalitiesforplatformssuchasAzure,Hadoop andIBMdatalake.TheDataFabricalsofeatures“Keep Me In The loop”,unifiedviewandmore.TheDataFabricfitsinany infrastructurewhilemakingprocessesmoreefficientand saving time and money.
Data insight and data management
Whilecrawlingforcontent,theDataFabricalsoincludesthe accessrights,metadataandlogfiles.Thisenablesyouto apply(automated)datamanagementtaskswhilegainingdata insights.Thismakesgovernance,riskmanagementand compliance support possible in several areas, including:Automaticclassificationofdocumentsviamachine learning techniquesMonitoring‘dataleaks’forexamplegiven,documents categorised as sensitiveAcquiringinsightsregardingpersonallyidentifiable information.Reportscanbegeneratedandinformation providedaboutthedatalocationswithouthavingto involveanyotherdepartment.Datacanbeanonymised orpseudonymisedfullyautomatedwhendatais streamed for analysis (BI, data science, etc.).Fullyautomatedapplicationofdataretentionpolicies. ‘Datalifecyclemanagement’(DLM)canbefully automatedorappliedafteranapprovalloopbydata owners.
Data becomes information
Throughdataintegration,thecleansing,blendingand enrichmentsofdata,thedashboardsandalerts,thedata analysisandBIpossibilities,theunique'unifiedview',the abilitytoaddexternaldatasources,therealtimeprocessingof informationthatbecomesimmediatelyavailableforknowledge workers,managementordatascientists,beingabletofinda needleinahaystack,acquiringdatainsightandmore,data will be converted into information.BecausetheDataFabriccanestablishrelationshipsbetween dataandisstrongin‘datalineage’,notonlyapplicationsinthe areaofunstructureddataareonthehorizon,butalsoon structureddata.Establishingrelationsbetweenrecordsand analysingthemispossible,examplegivenforERPsystems. Thisallowstherealisationofunprecedentedinsights.By processingexternaldatasources,manyotherapplicationsare alsopossibleincluding‘knowyourcustomer’(KYC)anda360-degree view of employees and organisations.TheDataFabricisofgreatvalueforboardofdirectorsand management,marketing,HRM,recruitment,data scientists&analysts,ITandknowledgeworkersamongst other people and departments.IfyouwouldliketoobtainmoreinformationaboutourData Fabricorifyouhaveanyquestionsaboutthemanyotheruse casestheDataFabrichastoofferyou,pleasefeelfreeto contact us!
The Data Fabric summarised
1.TheDataFabriccreatesaunique,solid,flexibleand scalabledatafoundationthatfitsinany(complex) infrastructure2.Innovativetechniquesensurethecreationofhigh-quality datawithouthavingtoknowhowdata(records)could blend3.(Highquality)datasetsmatchingadefinedquery,canbe streamedtootherapplicationsandplatforms(pushand pull)4.Writingbacktooriginalsources(withinterventionofadata steward,dataengineerordataprotectionofficer)is supported5.Bycombiningtheintegratedfunctionalitieslikedata lineage,metadatacollectionandcreation,datacatalog, streaming&writebackcapabilities,machinelearning capabilities,automatedfrauddetectionandmore,many data related use cases can be dealt with and solved.As such, the Data Fabric can be called a Smart Data Fabric!WiththeDataFabric,youcangetinsightsandcontrolover yourdataandinformationoutofyourvaluabledata,without changingyourwayofworkingandwhilereusingthe infrastructure you already have invested in.TheDataFabricincreasesefficiencyinmultiplewaysandwill saveyoulotsoftimeandmoney.Withthis,theDataFabric hasahighROI.Wearehappytomakethisvisibleforyour organisation by mapping several value metrics.ThereismuchmoretotellabouttheDataFabric’spossibilities and its innovative techniques. Feel free to contact us.+91 74 066 24 888 datafabric@s10group.com
Over 220 out-of-the-box integrations have been developped
Data quality is analysed by 18 data quality metrics. By adjusting the levels, data quality can be improved to the preferred levels
Dataset from query “Customer Data” is automatically streamed for predictive analysis
Data Integration
Data Management
Data Preparation
Data Governance
Data Cleaning
Data Catalog
Data Lineage
Data Training
Data Intelligence
Data Mart
Data Access
Data Workflow
All about data and innovation
Create high-quality data Streamline the process of making data ready to use Become Data Drivenwith the Data Fabric!
1. Collecting data & data curation/normalisation2.Organisingdataanddatagovernance,processingnewdata and requests3. Streaming of defined quality data to applications/platforms4. Data management and internal use cases
Automateddata integration
+91 74 066 24 888
Dataunificationwith the Data Fabric…
Curious about the use cases of our customers or how we can support your own use cases?Please get in touch!
Data AccuracyData ValidityData CompletenessData RelevanceData UniformityData StewardshipData ConsistencyData AccountabilityData Connectivity
1.2.3.4.5.6.7.8.9.
Data ReliabilityData QualityData TimelinessData IntegrityData ConformityData FlexibilityData Staleness Data AvailabilityData Usability
10.11.12.13.14.15.16.17.18.
18 data quality metrics
Datacanbeprovidedondemandtoauser. Qualitydataisrealisedinacentralplaceby cleansingandenrichingdata.Thisqualitydata canbeofferedtodifferentsystems,applications orusers,irrespectiveoftheirlocation.DaaS solutions provide advantages like:Noextensiveknowledgeoftheunderlying data is requiredCost-effectivenessData quality is improved