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Title HereBig Data Pricing and Packaging Overview

Cloud Data Warehouse Modernization on Azure Workshop

Daniel HeinCloud Ecosystem Solution Architect

Matt RogersPartner Alliances Manager

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Agenda1.00 – Lunch served

1.30 – Welcome and Workshop overview

1.40 – EDC Demo

1.50 – EDC Lab

2.30 – Break

2.40 – IICS Demo

2.50 – IICS Lab

4.00 – Close

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What are the barriers to Azure adoption?

• How do I get my data to Azure?• Where should I land it in Azure?

Connectivity

• What data should I put in Azure?• What data can I put in Azure?

Locating the right data

• Writing custom code is easy for a starter project, but how will I scale on Azure?

Azure Experiment vs Azure Strategy

• 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?

Patchwork of vendors/services

4 © Informatica. Proprietary and Confidential.

Putting you on the fast lane to Azure

100+Data sources

10xFaster to locate

the right data

17Microsoft product

integrations

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

Management Solutions

Aug 2017

Guido De Simoni, et al.,

10 August 2017

Magic Quadrant

for Data

Quality Tools

Oct 2017

Mei Yang Selvage, et al.,

24 October 2017

Magic Quadrant

for Enterprise Integration

Platform as a Service

Apr 2018

Keith Guttridge, et al.,

18 April 2018

Magic Quadrant

for Master Data

Management Solutions

Oct 2017

Bill O'Kane, et al.,

30 October 2017

These 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 are

available 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 to

select 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 be

construed 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 a

particular purpose.

Lead with Informatica

Top 10 of Fortune 100

Lead with Informatica

85 of Fortune 100

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Think BIGStart Small

Scale Fast

Our Approach to Driving Customer Success

MONITOR AND MANAGE

DATA ENGINE

CONNECTIVITY

DATAQUALITY

ENTERPRISEDATA CATALOG

DATASECURITY

Products

Solutions

MASTER DATAMANAGEMENT

Intelligent

Data Platform

CLOUDREAL TIME/

STREAMINGBIG DATA TRADITIONAL

DATAINTEGRATION

iPaaS

PRODUCT 360

ENTERPRISE DATA GOVERNANCE

SECURE@SOURCESUPPLIER 360

REFERENCE 360

ENTERPRISE DATA LAKE

CUSTOMER 360

BIG DATA MANAGEMENT

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Informatica products for Azure

Power CenterInformatica

Intelligent Cloud Services

Big Data

Management

Enterprise Data

Catalog

Informatica

Intelligent Cloud

Services

Informatica

Data Quality

Enterprise Data

CatalogPower Center

Master Data

Management

Big Data

ManagementInformatica Data

Quality

Supported on:

Available on:

Supported Azure ConnectorsAzure Blob

Azure Data Lake

Store (ADLS)DocumentDBAzure SQL DW

SQL Server 2016 HD Insight

Dynamics365

(CRM, AX, GP,

NAV)

CosmosDB* Check PAM for specific product support

Axon Secure@Source

Informatica

Intelligent Streams

PaaS PAYG and BYOL

Azure SQL DB

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Azure “On-Ramp”

Jumpstarting

the Cloud Data

Warehousing Journey

Informatica is the “On-ramp”to Azure SQL DW

• Connectivity to all on-premises data warehouse vendors

• Intelligent cataloging to make it easy to locate data to be moved to the cloud

• Best-in-class data integration capabilities

• Rapidly identify dependencies to develop a rock solid migration strategy

Solution Components

Secure Agent

Enterprise Data

Catalog (EDC)

Intelligent Cloud

Services (IICS)

Azure SQL DW

On-Premises

EDWAvailable via the Azure Marketplace

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EnterpriseData Catalog

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Understand your data landscape with machine learning-based,data asset discovery and visibility

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Classify your

data

Know more

about your dataShare your data

knowledge

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How can a data catalog help?

Self-service Discovery

for Analytics

Find and locate data assets

quickly and make sense of the

data in business context

Data Governance

Get inventory of your data

assets and make it available

for business

IT Impact Analysis

Get a clear, complete of picture

of data environment

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Enterprise Data Catalog for Everyone

How can IT enable

business to discover data assets with verified

data quality and traceability?

Data Architect

How can I search,

explore, understand and trust data required for my

analysis?

Data ConsumerData Steward

How can I manage

metadata for key enterprise data assets?

How do I manage the data lifecycle?

How can I make the

extract, transform, and load data flow for my data

warehousing projects v isible to others?

ETL DeveloperTechnical Data

Analyst

How can I

understand how data moves through my

application portfolio to my

data warehouses for analytics?

EDC

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• Easily find and discover trusted data

• Explore 360-degree data relationships

• End-to-End data lineage &

impact analysis

• Integrated Business Glossary

• Crowd-sourced enrichment

and auto-tagging of data assets

• Automatic Classification for

data domains

• Machine-learning-based data similarity recommendations

(CLAIRE)

Comprehensive Discovery and Visibility

to all data assets

Enterprise Information Catalog

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Entity Recognition

Street City State Zip

Address

First

Name

Last

Name

Customer

PrID Product Name

Product

DateAmount

Order

AI-driven, machine learning based techniques to identify, cluster and match similar columns and provide

recommendations for similar data sets

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Enterprise Data CatalogEnhanced Column Similarity

Unsupervised clustering of similar columns based on names, lineage, values and patterns

Enhanced Smart Domain Discovery based on new column similarity clusters.

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Enterprise Data CatalogOpen Metadata API

No metadata lock-in; any

metadata can be ingested and

accessed from EIC

Programmatic curation of data

assets to deal with metadata at

scale

Integrate with third party

applications search, lineage and

asset relationship services

Analytics on Metadata Repository

Access metadata knowledge

graphs with Open Metadata API

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Enterprise Data CatalogEDC Plugin for Tableau

Identify, understand metadata

associated with a Tableau

Report

Complete, governed and trusted

view of data assets

Tableau plugin connects to an

existing EIC deployment

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Enterprise Data CatalogInformatica Axon Integration

Determine the technical lineage

of specific data and surface this

in a business relevant context

Import business glossary and

classifications from Informatica Axon.

This is a two-way integration with easy

navigation to associated technical and

business assets.

Business

Glossaries from Informatica Axon

Links to EIC from

Axon

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Cloudera | Hortonworks | MapR | AWS

EMR | Azure HD Insight

Big Data

PowerCenter | DQ | MDM | BDM |

MM | BG | ILM | Axon

Informatica Cloud | DIH

Informatica

IBM DataStage | Microsoft SSIS

Oracle Data Integrator | Talend

Other ETL

CSV | XML | JSON | Avro

Parquet | Excel | PDF | PPT | DOC

Zip Files | SharePoint | OneDrive | ADLS

Azure Blob | AWS S3 | HDFS

MapRFS | Local

Files and File Systems

Oracle | DB2 | SQL Server | Sybase

Teradata | Netezza | MySQL

Greenplum | Azure SQL DB/DW

SAP HANA | AWS Redshift

Google BigQuery | JDBC

Databases

AWS | Azure | Google

Cloud Platforms

SAP | Salesforce | Oracle

Applications

Tableau | IBM Cognos |

SAP | BusinessObjects |

MicroStrategy OBIEE | QlikView

Business Intelligence

Unified Metadata

ENTERPRISE

`

Enterprise Data Catalog

Hands on Lab Workshop

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Duration: 10 minutes

In this lesson you will learn how to search for relevant data assets using Search and Dynamic Faceting capabilities in the Catalog. You will also learn to explore associated Data Profiling statistics to determine the quality of the assets.

Objectives

• Find Data Assets

• Explore Data Profiling Statistics

Lesson 1: Data Discovery

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Duration: 10 minutes

In this lesson, you will learn about data domain assets in Enterprise Data Catalog.

Objectives

• Review Data Domain

Lesson 2: Data Domain Curation

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Lesson 3: Lineage and Impact Analysis

Duration: 10 minutes

In this lesson, you will learn how to use the new drill down lineage views in the Catalog to visualize data provenance. You will also learn how to use the detailed impact analysis reports in the catalog to understand impact due to change in data assets or ETL flows.

Objectives

• Understand Drill Down Lineage Views in the Catalog

• Perform Impact Analysis on Data Assets

• Understand Relationships

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Duration: 10 minutes

In this lesson, you will learn how the Catalog automatically classifies data based on known domains. You will also learn how you can annotate datasets to further classify data assets along multiple dimensions.

Objectives

• Work with Semantic-Search

• Understand Crowd-sourced curation

Lesson 4: Data Classification

Coffee/Tea Break10 minutes

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`

Intelligent Cloud Services

Hands on Lab Workshop

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Informatica Intelligent Cloud Services (IICS)

Data

IntegrationApplication

IntegrationB2B

Integration

Hub

API

Management

Integration,

transformation and orchestration for powering data

warehouses and analytic workloads

API-first integration

that orchestrates, governs and

manages data and

application services

Automate

secure data exchange

across partner

networks

Automate

integration at mixed latencies and eliminate

point-to-point integrations

Gain visibility

and control of integration

and data APIs

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Informatica Intelligent Cloud Services Architecture

Your Corporate Network

Cloud Applications

No staging required Data transmission is secure Multiple security certifications

Cloud Hosted AgentAgent Groups for High Availability

Agent GroupCloud Agent

Secure Agent

f irewall

Intelligent

Cloud Services

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Duration: 15 minutes

In this lesson you will learn how to mass ingest files from remote servers to a cloud storage

Objectives

• Create mass ingestion Task to read data from the Flat file and load into Azure Blob. In this lab, will learn how to move Flat files from Linux machine or Ftp server to Azure blob storage.

Lesson 1: Mass Ingestion

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Duration: 20 minutes

In this lesson, you will learn how to easily synchronize data from on-premises database to a cloud data warehouse.

Objectives

• Create Synchronization Task to read data from the Flat file and load into Azure SQL DW.

Lesson 2: Data Synchronisation

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Lesson 3: Working with semi-structured data

Duration: 20 minutes

In this lesson, you will learn how to load a JSON file to a cloud data warehouse using Informatica’s Intelligent Cloud Services.

Objectives

• Understand how to handle semi-unstructured data

• Data Transformations deep dive

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Duration: 30 minutes

In this lesson, you will learn how build commonly known data warehouse patterns using cloud data integration

Objectives

• Create a slowly changing dimension mapping that reads data from Oracle source and load into Azure SQL DW.

Lesson 4: Common Data Warehouse Patterns

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Duration: 30 minutes

In this lesson, you will learn how to control the execution sequence using taskflow.

Objectives

• Create Taskflow to execute previously created Mapping and Synchronization tasks.

Lesson 5: Task Orchestration

Q & A

Lunch

Thank You