BI, Analytics and Big DataA Modern-Day PerspectiveBy: Elad Israeli, Co-Founder, SiSensehttp://www.sisense.com
WWW.SISENSE.COMBusiness Intelligence (Analytics)A set of theories,methodologies,processes,architectures, andtechnologies thattransform raw datainto meaningful anduseful information forbusiness purposes.
WWW.SISENSE.COMThis is a Dashboard (= several queries)
WWW.SISENSE.COM…and BI/Analytics is:The ability to create a new report, dashboard or justget a new analytic question answered in real-time, orat least in-time.
WWW.SISENSE.COMWhat is Big Data?A collection of data sets so large and complexthat it becomes difficult to process using on-hand database management tools or traditionaldata processing applicationsDue to its technical nature, the same challengesarise in Analytics at much lower volumes thanwhat is traditionally considered Big Data.
WWW.SISENSE.COM..so Big Data Analytics is:The same as ‘Small Data’ Analytics, only with theadded challenges (and potential) of large datasets(~50M records or 50GB size, or more)Challenges, such as:• Data storage and management• De-centralized/multi-server architectures• Performance bottlenecks, poor responsiveness• Increasing hardware requirements
WWW.SISENSE.COMApproaches to The Challenge1. Project-Specific:– The development of a specific dashboard/report– An isolated initiative, with no forward-lookingimplications from the prospect’s perspective2. Solution-Oriented:– The development of a specific dashboard/report,with future ones (known or unknown) in mind
WWW.SISENSE.COME.K.G: Solution-Oriented vs. Project- SpecificTimeNew Report New ReportBI/Analytics (Solution-Oriented)TimeNew Report New Report New ReportReport/Dashboard Project (Project-Specific)
WWW.SISENSE.COMBI/Analytics E.K.GTimeNew Report New ReportThe rate at which new reports are introduced into critical processes shouldincrease over-time, due to:• Completed integration, customization & adaptation• Time for training to sink in• Adoption (more users generating reports)New Report = Answer To New Question = New Insight
WWW.SISENSE.COMHow Raw Data Becomes InsightConnect ToSourceLoad &StoreClean &StandardizeGrantAccessDefineQueriesFormatThe ReportShare theReportRespond toFeedbackETL / Data ManagementBI/Analytics/Visualization
WWW.SISENSE.COMData Warehouse• Clean and accurate datarecognized as the onlyreal business ‘truth’• A central repository ofdata which is created byintegrating data fromone or more disparatesources• Stores current as well ashistorical data
WWW.SISENSE.COMExisting Data LandscapesOwner:ITOwner:IT or BusinessDW• The data is in its detailed form (raw data)• The data is located in multiple places• The data may be dirty (i.e. entry-errors)• The data is accessible to whoever ownsthe application/database• The data is not centralizedWith an existing Data Warehouse Without an existing Data Warehouse• The data is in its detailed form (raw data)• The data clean (was already processed)• The data is usually only directly accessible to IT• The data is centralized (single version)Operational DBApplication DBFilesOperational DBApplication DBFilesETLData Martsor OLAP Cubes (optional)
WWW.SISENSE.COMTraditional BI/Analytics ArchitecturesEnd-Users (Business) End-Users (Business)DetailedDirtyUnstructuredCentralized / Data Warehouse Non-Centralized / No DWSummarizedDe-centralizedCleanStructuredDetailedDirtyUnstructuredDetailedDirtyUnstructuredDWData Martsor OLAPCubesOwner:ITOwner:IT or Business
WWW.SISENSE.COMTraditional Architectures - ComparisonCentralized / DW Non-Centralized / No DWApproach Solution-oriented Project-specificData Quality & Accuracy Higher LowerScalability Higher LowerSingle Version of the Truth Yes NoInitial Investment Higher LowerLevel of Detail Summarized GranularOwner IT IT or Business (optional)Implementation Time Longer ShorterTechnical Complexity Higher LowerAdvantage / Disadvantage
WWW.SISENSE.COMModern-Day BI/Analytics - Focus• Self-Service– Empower business users of varying skill-levels– Keep IT in control, without becoming a bottleneck• Agility– Fast turnaround for new requirements• Scalability– Handle large, or rapidly growing volumes of data– Handle fast, unpredictable usage patterns and adoption
WWW.SISENSE.COMModern BI/Analytics – How?• Full-Coverage Solution– Provide all functionality required, from datamanagement, ETL and end-user analytics• Utilize modern technology– Columnar databases– In-Chip analytics technology– Support for 21st century chip-sets
WWW.SISENSE.COMArchitecture: With a Data WarehouseEnd-Users (Business)DetailedCentralizedCleanStructuredDetailedDirtyUnstructuredDWOwner:ITEnd-Users (Business)SummarizedDe-centralizedCleanStructuredDWMartsor OLAPCubesOwner:ITModern TraditionalElastiCube
WWW.SISENSE.COMModern vs. Traditional (DW)Centralized / DW SiSense ArchitectureApproach Solution-oriented Solution-orientedData Quality & Accuracy High HighScalability High HighSingle Version of the Truth Yes YesInitial Investment Higher LowerLevel of Detail Summarized GranularOwner IT IT or Business (optional)Implementation Time Longer ShorterTechnical Complexity Higher LowerAdvantage / Disadvantage
WWW.SISENSE.COMArchitecture: Without a Data WarehouseEnd-Users (Business)DetailedCentralizedCleanStructuredDetailedDirtyUnstructuredElastiCubeOwner:IT or BusinessEnd-Users (Business)Owner:IT or BusinessDetailedNon-CentralizedDirtyUnstructuredDetailedDirtyUnstructuredModern Traditional
WWW.SISENSE.COMModern vs. Traditional (No DW)Non-Centralized / No DW Modern ArchitectureApproach Project-oriented Solution-orientedData Quality & Accuracy Lower HigherScalability Lower HigherSingle Version of the Truth No YesInitial Investment Lower LowerLevel of Detail Granular GranularOwner IT or Business (optional) IT or Business (optional)Implementation Time Short ShortTechnical Complexity Lower LowerAdvantage / Disadvantage
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