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Text hereCloud Data WarehouseModernization on AzureBigTitleData PricingHereandWorkshopPackaging OverviewDaniel HeinCloud Ecosystem Solution ArchitectMatt RogersPartner Alliances Manager

Agenda1.00 – Lunch served1.30 – Welcome and Workshop overview1.40 – EDC Demo1.50 – EDC Lab2.30 – Break2.40 – IICS Demo2.50 – IICS Lab4.00 – Close2 Informatica. Proprietary and Confidential.

What are the barriers to Azure adoption?Connectivity How do I get my data to Azure? Where should I land it in Azure?Locating the right data What data should I put in Azure? What data can I put in Azure?Azure Experiment vs Azure Strategy Writing custom code is easy for a starter project, but how will I scale on Azure?Patchwork of vendors/services Which vendors should I work with on Azure to build a complete cloud data management strategy? How will I ensure all the pieces work together well?3 Informatica. Proprietary and Confidential.

Putting you on the fast lane to Azure4100 10x17Data sourcesFaster to locatethe right dataMicrosoft productintegrations Informatica. Proprietary and Confidential.

A Leader in Five Gartner Magic QuadrantsMagic Quadrantfor Master DataManagement SolutionsMagic Quadrantfor Enterprise IntegrationPlatform as a ServiceMagic Quadrantfor DataIntegration ToolsMagic Quadrantfor MetadataManagement SolutionsMagic Quadrantfor DataQuality ToolsOct 2017Apr 2018Aug 2017Oct 2017Bill O'Kane, et al.,30 October 2017Keith Guttridge, et al.,18 April 2018Aug 2017Mark A. Beyer , et al.,3 August 2017Guido De Simoni, et al.,10 August 2017Mei Yang Selvage, et al.,24 October 2017These graphics were published by Gartner, Inc. as part of larger research documents and should be evaluated in the context of the entire document. The Gartner documents areavailable upon request from Informatica. Gartner does not endorse any vendor, product or service depicted in its research pub lications, and does not advise technology users toselect only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinion s of Gartner's research organization and should not beconstrued as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, inclu ding any warranties of merchantability or fitness for aparticular purpose.

Top 10 of Fortune 100Lead with Informatica

85 of Fortune 100Lead with Informatica

Our Approach to Driving Customer SuccessThink BIGStartSmallScale Fast8 Informatica. Proprietary and Confidential.

CLOUDREAL TIME/STREAMINGBIG DATATRADITIONALSolutionsENTERPRISEDATA LAKEENTERPRISE RENCE360SECURE@SOURCEDATAINTEGRATIONiPaaSBIG DATAMANAGEMENTDATAQUALITYMASTER DATAMANAGEMENTENTERPRISEDATA CATALOGDATASECURITYProductsIntelligentData PlatformMONITOR AND MANAGEDATA ENGINECONNECTIVITY

Informatica products for AzureAzure SQL DWCosmosDBInformaticaData QualityMaster DataManagementAzure BlobSQL Server 2016Supported Azure ConnectorsAzure Data LakeStore (ADLS)DocumentDBHD InsightDynamics365(CRM, AX, GP,NAV)Azure SQL DBPower CenterInformaticaIntelligentCloud ServicesBig DataManagementEnterprise DataCatalogAxonSecure@Source* Check PAM for specific product supportInformaticaIntelligentStreamsSupported on:Available on:Power CenterInformaticaIntelligent CloudServicesPaaSPAYG and BYOL10 Informatica. Proprietary and Confidential.Enterprise DataCatalogInformatica DataQualityBig DataManagement

Azure “On-Ramp”Jumpstartingthe Cloud DataWarehousing Journey11 Informatica. Proprietary and Confidential.

Informatica is the “On-ramp”to Azure SQL DWSolution Components Connectivity to all on-premises datawarehouse vendorsAzure SQL DW Intelligent cataloging to make it easyto locate data to be moved to thecloudSecure Agent Best-in-class data integrationcapabilities Rapidly identify dependencies todevelop a rock solid migration strategyAvailable via the Azure Marketplace12 Informatica. Proprietary and Confidential.Intelligent CloudServices (IICS)Enterprise DataCatalog (EDC)On-PremisesEDW

EnterpriseData Catalog

Understand your data landscapewith machine learning-based,data asset discovery and visibilityClassify yourdata14Know moreabout your data Informatica. Proprietary and Confidential.Share your dataknowledge

How can a data catalog help?15Self-service Discoveryfor AnalyticsData GovernanceIT Impact AnalysisFind and locate data assetsquickly and make sense of thedata in business contextGet inventory of your dataassets and make it availablefor businessGet a clear, complete of pictureof data environment Informatica. Proprietary and Confidential.

Enterprise Data Catalog for EveryoneEDCData StewardData ArchitectData ConsumerHow can I managemetadata for keyenterprise dataassets?How can IT enablebusiness todiscov er dataassets with v erifieddata quality andtraceability?How can I search,explore, understandand trust datarequired for myanalysis?How do I managethe data lifecycle?16 Informatica. Proprietary and Confidential.Technical DataAnalystHow can Iunderstand howdata mov esthrough myapplicationportfolio to mydata warehousesfor analytics?ETL DeveloperHow can I make theextract, transform,and load data flowfor my datawarehousing projectsv isible to others?

Enterprise Information CatalogComprehensive Discovery and Visibilityto all data assets Easily find and discover trusted data Explore 360-degree data relationships End-to-End data lineage &impact analysis Integrated Business Glossary Crowd-sourced enrichmentand auto-tagging of data assets Automatic Classification fordata domains Machine-learning-baseddata similarity recommendations(CLAIRE)17 Informatica. Proprietary and Confidential.

Entity RecognitionOrderAmountDateProductPrIDProduct ateZipAI-driven, machine learning based techniques to identify, cluster and match similar columns and provide Informatica. Proprietary and Confidential.recommendations for similar data sets

Enterprise Data CatalogEnhanced Column SimilarityUnsupervised clustering of similarcolumns based on names, lineage, valuesand patternsEnhanced Smart Domain Discoverybased on new column similarity clusters.19 Informatica. Proprietary and Confidential.

Enterprise Data CatalogOpen Metadata APINo metadata lock-in; anymetadata can be ingested andaccessed from EICProgrammatic curation of dataassets to deal with metadata atscaleAnalytics on Metadata RepositoryIntegrate with third partyapplications search, lineage andasset relationship services20 Informatica. Proprietary and Confidential.Access metadata knowledgegraphs with Open Metadata API

Enterprise Data CatalogEDC Plugin for TableauIdentify, understand metadataassociated with a TableauReportComplete, governed and trustedview of data assetsTableau plugin connects to anexisting EIC deployment21 Informatica. Proprietary and Confidential.

Enterprise Data CatalogInformatica Axon IntegrationDetermine the technical lineageof specific data and surface thisin a business relevant contextBusinessGlossaries fromInformatica AxonImport business glossary andclassifications from Informatica Axon.This is a two-way integration with easynavigation to associated technical andbusiness assets.22 Informatica. Proprietary and Confidential.Links to EIC fromAxon

InformaticaBig DataPowerCenter DQ MDM BDM MM BG ILM AxonInformatica Cloud DIHCloudera Hortonworks MapR AWSEMR Azure HD InsightIBM DataStage Microsoft SSISOracle Data Integrator TalendFiles and File SystemsCSV XML JSON AvroParquet Excel PDF PPT DOCZip Files SharePoint OneDrive ADLSAzure Blob AWS S3 HDFSMapRFS LocalDatabasesENTERPRISEUnifiedMetadataOracle DB2 SQL Server SybaseTeradata Netezza MySQLGreenplum Azure SQL DB/DWSAP HANA AWS RedshiftGoogle BigQuery JDBCCloud PlatformsBusiness IntelligenceAWS Azure GoogleTableau IBM Cognos SAP BusinessObjects MicroStrategy OBIEE QlikViewApplicationsSAP Salesforce Oracle23Other ETL Informatica. Proprietary and Confidential.

Enterprise Data CatalogHands on Lab Workshop

Lesson 1: Data DiscoveryDuration: 10 minutesIn this lesson you will learn how to search for relevant data assets using Searchand Dynamic Faceting capabilities in the Catalog. You will also learn to exploreassociated Data Profiling statistics to determine the quality of the assets.Objectives Find Data Assets Explore Data Profiling Statistics25 Informatica. Proprietary and Confidential.

Lesson 2: Data Domain CurationDuration: 10 minutesIn this lesson, you will learn about data domain assets in Enterprise Data Catalog.Objectives Review Data Domain26 Informatica. Proprietary and Confidential.

Lesson 3: Lineage and Impact AnalysisDuration: 10 minutesIn this lesson, you will learn how to use the new drill down lineage views in theCatalog to visualize data provenance. You will also learn how to use the detailedimpact analysis reports in the catalog to understand impact due to change in dataassets or ETL flows.Objectives Understand Drill Down Lineage Views in the Catalog Perform Impact Analysis on Data Assets Understand Relationships27 Informatica. Proprietary and Confidential.

Lesson 4: Data ClassificationDuration: 10 minutesIn this lesson, you will learn how the Catalog automatically classifies data basedon known domains. You will also learn how you can annotate datasets to furtherclassify data assets along multiple dimensions.Objectives Work with Semantic-Search Understand Crowd-sourced curation28 Informatica. Proprietary and Confidential.

Coffee/Tea Break10 minutes

Intelligent Cloud ServicesHands on Lab Workshop 30 Informatica. Proprietary and Confidential.

Informatica Intelligent Cloud Services tion,transformation andorchestration forpowering datawarehouses andanalytic workloadsAPI-first integrationthat orchestrates,governs andmanages data andapplication services31 Informatica. Proprietary and Confidential.APIManagementIntegrationHubB2BGain visibilityand control ofintegrationand data APIsAutomateintegration atmixed latenciesand eliminatepoint-to-pointintegrationsAutomatesecure dataexchangeacross partnernetworks

Informatica Intelligent Cloud Services ArchitectureYour Corporate NetworkIntelligentCloud ServicesCloud AgentAgent GroupSecure AgentfirewallCloud ApplicationsNo staging requiredData transmission is secureAgent Groups for High Availability32 Informatica. Proprietary and Confidential.Multiple security certificationsCloud Hosted Agent

Lesson 1: Mass IngestionDuration: 15 minutesIn this lesson you will learn how to mass ingest files from remote servers to acloud storageObjectives Create mass ingestion Task to read data from the Flat file and load into AzureBlob. In this lab, will learn how to move Flat files from Linux machine or Ftpserver to Azure blob storage.33 Informatica. Proprietary and Confidential.

Lesson 2: Data SynchronisationDuration: 20 minutesIn this lesson, you will learn how to easily synchronize data from on-premisesdatabase to a cloud data warehouse.Objectives Create Synchronization Task to read data from the Flat file and load into AzureSQL DW.34 Informatica. Proprietary and Confidential.

Lesson 3: Working with semi-structured dataDuration: 20 minutesIn this lesson, you will learn how to load a JSON file to a cloud data warehouseusing Informatica’s Intelligent Cloud Services.Objectives Understand how to handle semi-unstructured data Data Transformations deep dive35 Informatica. Proprietary and Confidential.

Lesson 4: Common Data Warehouse PatternsDuration: 30 minutesIn this lesson, you will learn how build commonly known data warehouse patternsusing cloud data integrationObjectives Create a slowly changing dimension mapping that reads data from Oracle sourceand load into Azure SQL DW.36 Informatica. Proprietary and Confidential.

Lesson 5: Task OrchestrationDuration: 30 minutesIn this lesson, you will learn how to control the execution sequence using taskflow.Objectives Create Taskflow to execute previously created Mapping and Synchronizationtasks.37 Informatica. Proprietary and Confidential.

Q&A

Lunch

Thank You

A Leader in Five Gartner Magic Quadrants Magic Quadrant for Data Integration Tools Aug 2017 Mark A. Beyer , et al., 3 August 2017 Magic Quadrant for Metadata