SlideShare a Scribd company logo
1 of 31
Download to read offline
1
Managing Heterogeneous Data Stacks With Informatica and
MongoDB Atlas
Seth Payne
Sr. Product Manager, MongoDB
Sumon Saha
Director of Product Management, Informatica
susaha@informatica.comseth.payne@mongodb.com
Best way to
work with data
Freedom to
run anywhere
Intelligently put data
where you need it
Intelligent Operational Data Platform
Data Source
Integration
Data
APIs
Data Loading
and
Streaming
Legacy
Systems
Offloading
Data
Analytics
Data
Governance
Massive volumes & large variety
Applications
Files
Images,
Audio & Video
Sensors
Tabular Databases
MongoDB &
Other Non Tabular
Data Warehouse &
Data Lake
Many structures and sources
Integration Challenges
Data Access
API
Change
Data
Capture
(CDC)
Extract
Transform
Load
(ETL)
MongoDB Cluster
Document Data Model
Distributed Systems
Architecture
Cloud | On-Premises
Operational Apps and
Systems of Record
Producers
Operational Data Layer
Consumers
Mainframe Systems
CRM
ERP
Order Management
Supply Chain Mgmt
Data Lake
Marketing Automation
Website
Social Media
Reference Data
Third-Party APIs
Etc.
Batch Load
API CallsBatch File
Exports
Real-Time
Data Changes
Delta Load
MongoDB Change Streams
Write Back to Producer Systems (Optional)
MongoDB
Native Drivers
Consuming Operational
Apps and Services
Internal apps, customer-facing
services, and APIs for
third-party consumption – across
any channel
Business Intelligence (BI)
and Advanced Analytics
Visualization and reporting,
data analysis, artificial
intelligence, machine learning
and more
Human Capital Mgmt
MongoDB Connectors
MongoDB Connectors
of enterprise workloads
will be in the cloud by
2020
83%
Cloud is the Key Enabler of the New Digital Era
Source: Forbes, Logic Monitor Cloud Adoption
of large organizations
will enable their non-IT
personnel to perform
integration tasks by 2023*
65%
Democratization Empowers New Integration Personas
*Gartner, Predicts 2019: Democratization of IT Requires Different Strategies for Integration, Keith Guttridge, et al, 21 January 2019
of integration platforms will
leverage machine learning to
automate integration between
application APIs by 2020, thus
reducing the need for skilled
integration specialists*
75%
AI/ML Automates Integration
*Gartner, Predicts 2019: Democratization of IT Requires Different Strategies for Integration, Keith Guttridge, et al, 21 January 2019
SaaS, IaaS and PaaS Adoption Accelerating Rapidly
*CAGR 2017-2022 (%)
*Source: Gartner, Forecast Analysis: Public Cloud Services, Worldwide, 4Q18 Update, Colleen Graham, et al 8 Feb 2019
17%
Replace
Software as a Service
SaaS
Re-host
Infrastructure as a Service
IaaS
26.4% 20.2%
Re-platform
Platform as a Service
PaaS
Gartner estimates the following growth
of enterprises are looking
at a multi-cloud strategy;
with an average of 5
clouds
81%
Multi-Cloud and Hybrid is the Current Reality
Source: Rightscale 2018 state of Cloud Report
ML based
Integration
Re-platform
Replace
Rehost
New Data
New
Users
Hybrid
More
Workloads
Data Challenges Rise in a Multi-Cloud Hybrid World
Integrating business
processes that
span clouds
Data management
challenges amplify
with multiple clouds
Locked in by a
single best-of-breed
cloud provider
Challenges
Cloud
DW
Cloud
Application
Integration
Cloud B2B
Integration
Cloud
Data Lake
Cloud API
Mgmt.
Cloud
Migration
AWS RedshiftAmazon Aurora
Our Vision
ANY Integration Pattern ANY User ANY Data
Enterprise Unified Metadata Intelligence
Unified Modular Hybrid Secure Trusted iPaaS
Supporting Any Integration and Any Data
Management Pattern
Log data
Machine
& IOT
EDI order
requests
Website & Mobile
Edge Data
Streaming
Edge Data
Streaming
Big Data
Streaming
Queue
B2B
API order
requests
Place
an Order
API Gateway
Providers
On-Prem
ERP System
Data
Warehouses
Integration
Hub
Databases
Data
Integration
Data & Application
Integration
Application
Integration
API
API
API
API
Supporting Any Integration and Any Data
Management Pattern
Log data
Log data
EDI order
requests
Website
Edge Data
Streaming
Edge Data
Streaming
Big Data
Streaming
Queue
B2B
API order
requests
Place
an Order
API Gateway
Providers
On-Prem
ERP System
Data
Warehouses
Integration
Hub
Databases
Data
Integration
Data & Application
Integration
Application
Integration
API
API
API
API
Table stakes
Cloud Data
Integration
Cloud Application
Integration
Cloud API
Management
Connectivity
+
New and unique patterns
Cloud
B2B
Cloud
Integration Hub
Cloud
MDM
Cloud
Data Security
Cloud Data
Quality
Cloud Data
Preparation
Data Ingestion/
Data Lakes
Cloud
Streaming/IoT
Cloud Data
Catalog
Cloud Data
Governance
Connect Your Enterprise to Everything
Connecting 100,000 applications, databases, and other endpoints
Informatica MDM Services and
MongoDB Atlas
IICS MDM Services
Deliver a complete and trusted view of all enterprise customer data
Remove duplicate, inaccurate,
incomplete customer data
Customer data integration for a
complete view of across all data
sources and apps
Link trusted customer profiles
and explore relationships
Customer
360
IICS MDM - Architecture
Data Integration Modernization
Cloud Data Integration Modernization Blueprint
Supporting Any Modern Analytics
ENTERPRISE DATA CATALOG
DATA QUALITY & GOVERNANCE
DATA PROTECTION
Elastic Compute
API & Application Integration
Cloud Data Integration
Replication & Mass Ingestion
File & Streaming Ingestion Cloud Data Integration
Cloud
SaaS
LogsMachine
Data
Connected
Devices
Edge
DatabasesApplication
Servers
Mainframe
On-Premises
Cloud
Object Store
Cloud Data
Lake
Cloud Data
Warehouses
Machine
Learning
Visualization
Business
Intelligence
Data Integration Services
Use Cases: Data ingestion, migration, synchronization, replication
Synchronize SaaS and
On-premises Data
• Periodically sync SaaS and
on-premises applications to
Cloud DB/DW
• Cloud Data stores are used
for operational and analytic
purposes.
• Sync needs are both real
time as well as batch
Replicate Bulk Data to
Cloud
• Replicate on-premises data
to DB/DW on Cloud
• Cost savings and High
Availability
• Build using easy-to-use
wizards
Data Ingestion to
Databases and
Applications
• Bulk ingestion of data
sources
• Involves reuse of common
integration patterns like
Slowly Changing Dimensions,
error handling, etc.
• Migrate existing on-premises
DB/DW to cloud DB/DW
Application Integration and API Management Services
Use Cases: Real-time, API, and process integration needs
• Integrate API-based
applications in real time via
APIs and messaging
• Supplement bulk data
integration of data sets with
real-time data processing
• Integrate with MOM brokers
and ESB
Real-time Data Integration
• Create composite service and
data APIs exposed as REST,
SOAP, or OData services
• Expose managed APIs to
partners, customers, and
internal consumers
• Obtain visibility and control of
the use of APIs
API Creation and
Management
• Automate application and
business processes
• Provide interactive access to
data to users and applications
via API-enabled services and
data sources
• Provide users with automated
and guided workflows
Process Automation
Demonstration of
IICS Data Catalog & Data
Integration Services
w/ MongoDB integration
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 publications, and does not
advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions 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, including
any warranties of merchantability or fitness for a particular purpose.
A Leader in Five Gartner Magic Quadrants
Magic Quadrant
for Master Data
Management
Solutions
Michael Moran, et al.,
12 December 2018
Magic Quadrant
for Data
Integration Tools
Mark A. Beyer , et al.,
19 July 2018
Magic Quadrant
for Metadata
Management
Solutions
Guido De Simoni, et al.,
09 August 2018
Magic Quadrant
for Data Quality
Tools
Melody Chien, et al.,
27 March 2019
Magic Quadrant
for Enterprise
Integration Platform
as a Service
Eric Thoo, et al.,
23 April 2019
July 2018Aug 2018
March 2019 Dec 2018Apr 2019
8T+
Transactions
per month
>300%
Growth of
API volume
7M+
Integrations/day
200%+ growth YoY
110+
OEMs
220+
Native Connectors
>50%
Annual revenue
growth
Volumes of data
2x
Every 6 months
Informatica Intelligent Cloud Services
• Connecting 100,000 applications, databases, and other endpoints
Informatica and MongoDB —
Better Together
• Complete—End to End Solution
Enterprise Cloud Data Management including
Data Integration, Quality, Governance and Master
Data Management
Streaming
Application Integration and API Management Solution
Support across hybrid and multi-cloud
• Speed—Time to Insights/Productivity
Automation and self-service
200+ codeless connectors
Metadata-driven development
• Fast—High Performance
Optimized, scalable, native integration
Questions?
Please visit us at the Drivers and Connectors Booth!
MongoDB World 2019: Managing a Heterogeneous Data Stack with Informatica and MongoDB Atlas

More Related Content

What's hot

Building Data Lake on AWS | AWS Floor28
Building Data Lake on AWS | AWS Floor28Building Data Lake on AWS | AWS Floor28
Building Data Lake on AWS | AWS Floor28Amazon Web Services
 
Enterprise 360 - Graphs at the Center of a Data Fabric
Enterprise 360 - Graphs at the Center of a Data FabricEnterprise 360 - Graphs at the Center of a Data Fabric
Enterprise 360 - Graphs at the Center of a Data FabricPrecisely
 
How to Take Advantage of an Enterprise Data Warehouse in the Cloud
How to Take Advantage of an Enterprise Data Warehouse in the CloudHow to Take Advantage of an Enterprise Data Warehouse in the Cloud
How to Take Advantage of an Enterprise Data Warehouse in the CloudDenodo
 
Redefining Data Analytics Through Search
Redefining Data Analytics Through SearchRedefining Data Analytics Through Search
Redefining Data Analytics Through SearchConnexica
 
4th Industrial Revolution
4th Industrial Revolution4th Industrial Revolution
4th Industrial RevolutionRolando Rangel
 
Making the most of your Snowflake Investment
Making the most of your Snowflake InvestmentMaking the most of your Snowflake Investment
Making the most of your Snowflake InvestmentPaul Van Siclen
 
Hybrid Data Architecture: Integrating Hadoop with a Data Warehouse
Hybrid Data Architecture: Integrating Hadoop with a Data WarehouseHybrid Data Architecture: Integrating Hadoop with a Data Warehouse
Hybrid Data Architecture: Integrating Hadoop with a Data WarehouseDataWorks Summit
 
From ingest to insights with AWS
From ingest to insights with AWSFrom ingest to insights with AWS
From ingest to insights with AWSPaul Van Siclen
 
Company Profile - NPC with TIBCO Spotfire solution
Company Profile - NPC with TIBCO Spotfire solution  Company Profile - NPC with TIBCO Spotfire solution
Company Profile - NPC with TIBCO Spotfire solution Sirinporn Setworaya
 
Build Data Lakes and Analytics on AWS: Patterns & Best Practices - BDA305 - A...
Build Data Lakes and Analytics on AWS: Patterns & Best Practices - BDA305 - A...Build Data Lakes and Analytics on AWS: Patterns & Best Practices - BDA305 - A...
Build Data Lakes and Analytics on AWS: Patterns & Best Practices - BDA305 - A...Amazon Web Services
 
Moving to the Cloud: Modernizing Data Architecture in Healthcare
Moving to the Cloud: Modernizing Data Architecture in HealthcareMoving to the Cloud: Modernizing Data Architecture in Healthcare
Moving to the Cloud: Modernizing Data Architecture in HealthcarePerficient, Inc.
 
Non-Relational Revolution: Database Week SF
Non-Relational Revolution: Database Week SFNon-Relational Revolution: Database Week SF
Non-Relational Revolution: Database Week SFAmazon Web Services
 
Big Data Management: What's New, What's Different, and What You Need To Know
Big Data Management: What's New, What's Different, and What You Need To KnowBig Data Management: What's New, What's Different, and What You Need To Know
Big Data Management: What's New, What's Different, and What You Need To KnowSnapLogic
 
Spark Summit Keynote by Seshu Adunuthula
Spark Summit Keynote by Seshu AdunuthulaSpark Summit Keynote by Seshu Adunuthula
Spark Summit Keynote by Seshu AdunuthulaSpark Summit
 
Adapting to the exponential development of technology
Adapting to the exponential development of technologyAdapting to the exponential development of technology
Adapting to the exponential development of technologyDataWorks Summit
 

What's hot (20)

Building Data Lake on AWS | AWS Floor28
Building Data Lake on AWS | AWS Floor28Building Data Lake on AWS | AWS Floor28
Building Data Lake on AWS | AWS Floor28
 
Bring Your Data Model Alive with Automation - Data Modeling Zone Europe 2018
Bring Your Data Model Alive with Automation - Data Modeling Zone Europe 2018 Bring Your Data Model Alive with Automation - Data Modeling Zone Europe 2018
Bring Your Data Model Alive with Automation - Data Modeling Zone Europe 2018
 
Enterprise 360 - Graphs at the Center of a Data Fabric
Enterprise 360 - Graphs at the Center of a Data FabricEnterprise 360 - Graphs at the Center of a Data Fabric
Enterprise 360 - Graphs at the Center of a Data Fabric
 
How to Take Advantage of an Enterprise Data Warehouse in the Cloud
How to Take Advantage of an Enterprise Data Warehouse in the CloudHow to Take Advantage of an Enterprise Data Warehouse in the Cloud
How to Take Advantage of an Enterprise Data Warehouse in the Cloud
 
Redefining Data Analytics Through Search
Redefining Data Analytics Through SearchRedefining Data Analytics Through Search
Redefining Data Analytics Through Search
 
4th Industrial Revolution
4th Industrial Revolution4th Industrial Revolution
4th Industrial Revolution
 
Making the most of your Snowflake Investment
Making the most of your Snowflake InvestmentMaking the most of your Snowflake Investment
Making the most of your Snowflake Investment
 
Hybrid Data Architecture: Integrating Hadoop with a Data Warehouse
Hybrid Data Architecture: Integrating Hadoop with a Data WarehouseHybrid Data Architecture: Integrating Hadoop with a Data Warehouse
Hybrid Data Architecture: Integrating Hadoop with a Data Warehouse
 
Non-Relational Revolution
Non-Relational RevolutionNon-Relational Revolution
Non-Relational Revolution
 
From ingest to insights with AWS
From ingest to insights with AWSFrom ingest to insights with AWS
From ingest to insights with AWS
 
451 Research Impact Report
451 Research Impact Report451 Research Impact Report
451 Research Impact Report
 
Future of data
Future of dataFuture of data
Future of data
 
Company Profile - NPC with TIBCO Spotfire solution
Company Profile - NPC with TIBCO Spotfire solution  Company Profile - NPC with TIBCO Spotfire solution
Company Profile - NPC with TIBCO Spotfire solution
 
Build Data Lakes and Analytics on AWS: Patterns & Best Practices - BDA305 - A...
Build Data Lakes and Analytics on AWS: Patterns & Best Practices - BDA305 - A...Build Data Lakes and Analytics on AWS: Patterns & Best Practices - BDA305 - A...
Build Data Lakes and Analytics on AWS: Patterns & Best Practices - BDA305 - A...
 
Hybrid Cloud Strategy for Big Data and Analytics
Hybrid Cloud Strategy for Big Data and Analytics Hybrid Cloud Strategy for Big Data and Analytics
Hybrid Cloud Strategy for Big Data and Analytics
 
Moving to the Cloud: Modernizing Data Architecture in Healthcare
Moving to the Cloud: Modernizing Data Architecture in HealthcareMoving to the Cloud: Modernizing Data Architecture in Healthcare
Moving to the Cloud: Modernizing Data Architecture in Healthcare
 
Non-Relational Revolution: Database Week SF
Non-Relational Revolution: Database Week SFNon-Relational Revolution: Database Week SF
Non-Relational Revolution: Database Week SF
 
Big Data Management: What's New, What's Different, and What You Need To Know
Big Data Management: What's New, What's Different, and What You Need To KnowBig Data Management: What's New, What's Different, and What You Need To Know
Big Data Management: What's New, What's Different, and What You Need To Know
 
Spark Summit Keynote by Seshu Adunuthula
Spark Summit Keynote by Seshu AdunuthulaSpark Summit Keynote by Seshu Adunuthula
Spark Summit Keynote by Seshu Adunuthula
 
Adapting to the exponential development of technology
Adapting to the exponential development of technologyAdapting to the exponential development of technology
Adapting to the exponential development of technology
 

Similar to MongoDB World 2019: Managing a Heterogeneous Data Stack with Informatica and MongoDB Atlas

8.17.11 big data and hadoop with informatica slideshare
8.17.11 big data and hadoop with informatica slideshare8.17.11 big data and hadoop with informatica slideshare
8.17.11 big data and hadoop with informatica slideshareJulianna DeLua
 
SendGrid Improves Email Delivery with Hybrid Data Warehousing
SendGrid Improves Email Delivery with Hybrid Data WarehousingSendGrid Improves Email Delivery with Hybrid Data Warehousing
SendGrid Improves Email Delivery with Hybrid Data WarehousingAmazon Web Services
 
20181212 AWS NL - Informatica Cloud Overview
20181212 AWS NL - Informatica Cloud Overview20181212 AWS NL - Informatica Cloud Overview
20181212 AWS NL - Informatica Cloud OverviewGreg Rakers
 
Cloud Ready Data: Speeding Your Journey to the Cloud
Cloud Ready Data: Speeding Your Journey to the CloudCloud Ready Data: Speeding Your Journey to the Cloud
Cloud Ready Data: Speeding Your Journey to the CloudDLT Solutions
 
AWS Summit Singapore - Accelerate Digital Transformation through AI-powered C...
AWS Summit Singapore - Accelerate Digital Transformation through AI-powered C...AWS Summit Singapore - Accelerate Digital Transformation through AI-powered C...
AWS Summit Singapore - Accelerate Digital Transformation through AI-powered C...Amazon Web Services
 
IICS_Capabilities.pptx
IICS_Capabilities.pptxIICS_Capabilities.pptx
IICS_Capabilities.pptxNandan Kumar
 
Accelerate Digital Transformation Through AI-powered Cloud Analytics Moderniz...
Accelerate Digital Transformation Through AI-powered Cloud Analytics Moderniz...Accelerate Digital Transformation Through AI-powered Cloud Analytics Moderniz...
Accelerate Digital Transformation Through AI-powered Cloud Analytics Moderniz...Amazon Web Services
 
Big data an elephant business opportunities
Big data an elephant   business opportunitiesBig data an elephant   business opportunities
Big data an elephant business opportunitiesBigdata Meetup Kochi
 
The Double win business transformation and in-year ROI and TCO reduction
The Double win business transformation and in-year ROI and TCO reductionThe Double win business transformation and in-year ROI and TCO reduction
The Double win business transformation and in-year ROI and TCO reductionMongoDB
 
Cloud computing adoption in sap technologies
Cloud computing adoption in sap technologiesCloud computing adoption in sap technologies
Cloud computing adoption in sap technologiessveldanda
 
Unleashing the value of metadata with Talend
Unleashing the value of metadata with Talend Unleashing the value of metadata with Talend
Unleashing the value of metadata with Talend Jean-Michel Franco
 
Bringing the Power of Big Data Computation to Salesforce
Bringing the Power of Big Data Computation to SalesforceBringing the Power of Big Data Computation to Salesforce
Bringing the Power of Big Data Computation to SalesforceSalesforce Developers
 
Partena 2010.02.10
Partena 2010.02.10Partena 2010.02.10
Partena 2010.02.10lucdelanglez
 
Data Integration for Both Self-Service Analytics and IT Users
Data Integration for Both Self-Service Analytics and IT Users Data Integration for Both Self-Service Analytics and IT Users
Data Integration for Both Self-Service Analytics and IT Users Senturus
 
Information Virtualization: Query Federation on Data Lakes
Information Virtualization: Query Federation on Data LakesInformation Virtualization: Query Federation on Data Lakes
Information Virtualization: Query Federation on Data LakesDataWorks Summit
 
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...Denodo
 
Enabling Next Gen Analytics with Azure Data Lake and StreamSets
Enabling Next Gen Analytics with Azure Data Lake and StreamSetsEnabling Next Gen Analytics with Azure Data Lake and StreamSets
Enabling Next Gen Analytics with Azure Data Lake and StreamSetsStreamsets Inc.
 
Data and Application Modernization in the Age of the Cloud
Data and Application Modernization in the Age of the CloudData and Application Modernization in the Age of the Cloud
Data and Application Modernization in the Age of the Cloudredmondpulver
 
DataOps: Control-M's role in data pipeline orchestration
DataOps: Control-M's role in data pipeline orchestrationDataOps: Control-M's role in data pipeline orchestration
DataOps: Control-M's role in data pipeline orchestrationpzjnjr6rsg
 

Similar to MongoDB World 2019: Managing a Heterogeneous Data Stack with Informatica and MongoDB Atlas (20)

8.17.11 big data and hadoop with informatica slideshare
8.17.11 big data and hadoop with informatica slideshare8.17.11 big data and hadoop with informatica slideshare
8.17.11 big data and hadoop with informatica slideshare
 
SendGrid Improves Email Delivery with Hybrid Data Warehousing
SendGrid Improves Email Delivery with Hybrid Data WarehousingSendGrid Improves Email Delivery with Hybrid Data Warehousing
SendGrid Improves Email Delivery with Hybrid Data Warehousing
 
20181212 AWS NL - Informatica Cloud Overview
20181212 AWS NL - Informatica Cloud Overview20181212 AWS NL - Informatica Cloud Overview
20181212 AWS NL - Informatica Cloud Overview
 
Cloud Ready Data: Speeding Your Journey to the Cloud
Cloud Ready Data: Speeding Your Journey to the CloudCloud Ready Data: Speeding Your Journey to the Cloud
Cloud Ready Data: Speeding Your Journey to the Cloud
 
AWS Summit Singapore - Accelerate Digital Transformation through AI-powered C...
AWS Summit Singapore - Accelerate Digital Transformation through AI-powered C...AWS Summit Singapore - Accelerate Digital Transformation through AI-powered C...
AWS Summit Singapore - Accelerate Digital Transformation through AI-powered C...
 
IICS_Capabilities.pptx
IICS_Capabilities.pptxIICS_Capabilities.pptx
IICS_Capabilities.pptx
 
Accelerate Digital Transformation Through AI-powered Cloud Analytics Moderniz...
Accelerate Digital Transformation Through AI-powered Cloud Analytics Moderniz...Accelerate Digital Transformation Through AI-powered Cloud Analytics Moderniz...
Accelerate Digital Transformation Through AI-powered Cloud Analytics Moderniz...
 
Big data an elephant business opportunities
Big data an elephant   business opportunitiesBig data an elephant   business opportunities
Big data an elephant business opportunities
 
The Double win business transformation and in-year ROI and TCO reduction
The Double win business transformation and in-year ROI and TCO reductionThe Double win business transformation and in-year ROI and TCO reduction
The Double win business transformation and in-year ROI and TCO reduction
 
Cloud computing adoption in sap technologies
Cloud computing adoption in sap technologiesCloud computing adoption in sap technologies
Cloud computing adoption in sap technologies
 
Unleashing the value of metadata with Talend
Unleashing the value of metadata with Talend Unleashing the value of metadata with Talend
Unleashing the value of metadata with Talend
 
Bringing the Power of Big Data Computation to Salesforce
Bringing the Power of Big Data Computation to SalesforceBringing the Power of Big Data Computation to Salesforce
Bringing the Power of Big Data Computation to Salesforce
 
Partena 2010.02.10
Partena 2010.02.10Partena 2010.02.10
Partena 2010.02.10
 
Data Integration for Both Self-Service Analytics and IT Users
Data Integration for Both Self-Service Analytics and IT Users Data Integration for Both Self-Service Analytics and IT Users
Data Integration for Both Self-Service Analytics and IT Users
 
Information Virtualization: Query Federation on Data Lakes
Information Virtualization: Query Federation on Data LakesInformation Virtualization: Query Federation on Data Lakes
Information Virtualization: Query Federation on Data Lakes
 
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...
 
Enabling Next Gen Analytics with Azure Data Lake and StreamSets
Enabling Next Gen Analytics with Azure Data Lake and StreamSetsEnabling Next Gen Analytics with Azure Data Lake and StreamSets
Enabling Next Gen Analytics with Azure Data Lake and StreamSets
 
Data and Application Modernization in the Age of the Cloud
Data and Application Modernization in the Age of the CloudData and Application Modernization in the Age of the Cloud
Data and Application Modernization in the Age of the Cloud
 
DataOps: Control-M's role in data pipeline orchestration
DataOps: Control-M's role in data pipeline orchestrationDataOps: Control-M's role in data pipeline orchestration
DataOps: Control-M's role in data pipeline orchestration
 
IBM Cloud pak for data brochure
IBM Cloud pak for data   brochureIBM Cloud pak for data   brochure
IBM Cloud pak for data brochure
 

More from MongoDB

MongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB
 
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB
 
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB
 
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB
 
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB
 
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB
 
MongoDB SoCal 2020: MongoDB Atlas Jump Start
 MongoDB SoCal 2020: MongoDB Atlas Jump Start MongoDB SoCal 2020: MongoDB Atlas Jump Start
MongoDB SoCal 2020: MongoDB Atlas Jump StartMongoDB
 
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB
 
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB
 
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...MongoDB
 
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB
 
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB
 
MongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB
 
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB
 
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB
 
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB
 
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB
 
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB
 
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB
 
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB
 

More from MongoDB (20)

MongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB SoCal 2020: Migrate Anything* to MongoDB AtlasMongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
MongoDB SoCal 2020: Migrate Anything* to MongoDB Atlas
 
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
MongoDB SoCal 2020: Go on a Data Safari with MongoDB Charts!
 
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
MongoDB SoCal 2020: Using MongoDB Services in Kubernetes: Any Platform, Devel...
 
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDBMongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
MongoDB SoCal 2020: A Complete Methodology of Data Modeling for MongoDB
 
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
MongoDB SoCal 2020: From Pharmacist to Analyst: Leveraging MongoDB for Real-T...
 
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series DataMongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
MongoDB SoCal 2020: Best Practices for Working with IoT and Time-series Data
 
MongoDB SoCal 2020: MongoDB Atlas Jump Start
 MongoDB SoCal 2020: MongoDB Atlas Jump Start MongoDB SoCal 2020: MongoDB Atlas Jump Start
MongoDB SoCal 2020: MongoDB Atlas Jump Start
 
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
MongoDB .local San Francisco 2020: Powering the new age data demands [Infosys]
 
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
MongoDB .local San Francisco 2020: Using Client Side Encryption in MongoDB 4.2
 
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
MongoDB .local San Francisco 2020: Using MongoDB Services in Kubernetes: any ...
 
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
MongoDB .local San Francisco 2020: Go on a Data Safari with MongoDB Charts!
 
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your MindsetMongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
MongoDB .local San Francisco 2020: From SQL to NoSQL -- Changing Your Mindset
 
MongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB .local San Francisco 2020: MongoDB Atlas JumpstartMongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
MongoDB .local San Francisco 2020: MongoDB Atlas Jumpstart
 
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
MongoDB .local San Francisco 2020: Tips and Tricks++ for Querying and Indexin...
 
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
MongoDB .local San Francisco 2020: Aggregation Pipeline Power++
 
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
MongoDB .local San Francisco 2020: A Complete Methodology of Data Modeling fo...
 
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep DiveMongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
MongoDB .local San Francisco 2020: MongoDB Atlas Data Lake Technical Deep Dive
 
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & GolangMongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
MongoDB .local San Francisco 2020: Developing Alexa Skills with MongoDB & Golang
 
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
MongoDB .local Paris 2020: Realm : l'ingrédient secret pour de meilleures app...
 
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
MongoDB .local Paris 2020: Upply @MongoDB : Upply : Quand le Machine Learning...
 

Recently uploaded

Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...shyamraj55
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsAndrey Dotsenko
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
Bluetooth Controlled Car with Arduino.pdf
Bluetooth Controlled Car with Arduino.pdfBluetooth Controlled Car with Arduino.pdf
Bluetooth Controlled Car with Arduino.pdfngoud9212
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxnull - The Open Security Community
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsSnow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsHyundai Motor Group
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Wonjun Hwang
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 

Recently uploaded (20)

Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
Bluetooth Controlled Car with Arduino.pdf
Bluetooth Controlled Car with Arduino.pdfBluetooth Controlled Car with Arduino.pdf
Bluetooth Controlled Car with Arduino.pdf
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
Vulnerability_Management_GRC_by Sohang Sengupta.pptx
Vulnerability_Management_GRC_by Sohang Sengupta.pptxVulnerability_Management_GRC_by Sohang Sengupta.pptx
Vulnerability_Management_GRC_by Sohang Sengupta.pptx
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food Manufacturing
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsSnow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 

MongoDB World 2019: Managing a Heterogeneous Data Stack with Informatica and MongoDB Atlas

  • 1. 1 Managing Heterogeneous Data Stacks With Informatica and MongoDB Atlas Seth Payne Sr. Product Manager, MongoDB Sumon Saha Director of Product Management, Informatica susaha@informatica.comseth.payne@mongodb.com
  • 2. Best way to work with data Freedom to run anywhere Intelligently put data where you need it Intelligent Operational Data Platform
  • 4. Massive volumes & large variety Applications Files Images, Audio & Video Sensors Tabular Databases MongoDB & Other Non Tabular Data Warehouse & Data Lake Many structures and sources Integration Challenges
  • 5. Data Access API Change Data Capture (CDC) Extract Transform Load (ETL) MongoDB Cluster Document Data Model Distributed Systems Architecture Cloud | On-Premises Operational Apps and Systems of Record Producers Operational Data Layer Consumers Mainframe Systems CRM ERP Order Management Supply Chain Mgmt Data Lake Marketing Automation Website Social Media Reference Data Third-Party APIs Etc. Batch Load API CallsBatch File Exports Real-Time Data Changes Delta Load MongoDB Change Streams Write Back to Producer Systems (Optional) MongoDB Native Drivers Consuming Operational Apps and Services Internal apps, customer-facing services, and APIs for third-party consumption – across any channel Business Intelligence (BI) and Advanced Analytics Visualization and reporting, data analysis, artificial intelligence, machine learning and more Human Capital Mgmt MongoDB Connectors
  • 7.
  • 8. of enterprise workloads will be in the cloud by 2020 83% Cloud is the Key Enabler of the New Digital Era Source: Forbes, Logic Monitor Cloud Adoption
  • 9. of large organizations will enable their non-IT personnel to perform integration tasks by 2023* 65% Democratization Empowers New Integration Personas *Gartner, Predicts 2019: Democratization of IT Requires Different Strategies for Integration, Keith Guttridge, et al, 21 January 2019
  • 10. of integration platforms will leverage machine learning to automate integration between application APIs by 2020, thus reducing the need for skilled integration specialists* 75% AI/ML Automates Integration *Gartner, Predicts 2019: Democratization of IT Requires Different Strategies for Integration, Keith Guttridge, et al, 21 January 2019
  • 11. SaaS, IaaS and PaaS Adoption Accelerating Rapidly *CAGR 2017-2022 (%) *Source: Gartner, Forecast Analysis: Public Cloud Services, Worldwide, 4Q18 Update, Colleen Graham, et al 8 Feb 2019 17% Replace Software as a Service SaaS Re-host Infrastructure as a Service IaaS 26.4% 20.2% Re-platform Platform as a Service PaaS Gartner estimates the following growth
  • 12. of enterprises are looking at a multi-cloud strategy; with an average of 5 clouds 81% Multi-Cloud and Hybrid is the Current Reality Source: Rightscale 2018 state of Cloud Report
  • 14. Data Challenges Rise in a Multi-Cloud Hybrid World Integrating business processes that span clouds Data management challenges amplify with multiple clouds Locked in by a single best-of-breed cloud provider Challenges Cloud DW Cloud Application Integration Cloud B2B Integration Cloud Data Lake Cloud API Mgmt. Cloud Migration AWS RedshiftAmazon Aurora
  • 15. Our Vision ANY Integration Pattern ANY User ANY Data Enterprise Unified Metadata Intelligence Unified Modular Hybrid Secure Trusted iPaaS
  • 16. Supporting Any Integration and Any Data Management Pattern Log data Machine & IOT EDI order requests Website & Mobile Edge Data Streaming Edge Data Streaming Big Data Streaming Queue B2B API order requests Place an Order API Gateway Providers On-Prem ERP System Data Warehouses Integration Hub Databases Data Integration Data & Application Integration Application Integration API API API API
  • 17. Supporting Any Integration and Any Data Management Pattern Log data Log data EDI order requests Website Edge Data Streaming Edge Data Streaming Big Data Streaming Queue B2B API order requests Place an Order API Gateway Providers On-Prem ERP System Data Warehouses Integration Hub Databases Data Integration Data & Application Integration Application Integration API API API API Table stakes Cloud Data Integration Cloud Application Integration Cloud API Management Connectivity + New and unique patterns Cloud B2B Cloud Integration Hub Cloud MDM Cloud Data Security Cloud Data Quality Cloud Data Preparation Data Ingestion/ Data Lakes Cloud Streaming/IoT Cloud Data Catalog Cloud Data Governance
  • 18. Connect Your Enterprise to Everything Connecting 100,000 applications, databases, and other endpoints
  • 19. Informatica MDM Services and MongoDB Atlas
  • 20. IICS MDM Services Deliver a complete and trusted view of all enterprise customer data Remove duplicate, inaccurate, incomplete customer data Customer data integration for a complete view of across all data sources and apps Link trusted customer profiles and explore relationships Customer 360
  • 21. IICS MDM - Architecture
  • 23. Cloud Data Integration Modernization Blueprint Supporting Any Modern Analytics ENTERPRISE DATA CATALOG DATA QUALITY & GOVERNANCE DATA PROTECTION Elastic Compute API & Application Integration Cloud Data Integration Replication & Mass Ingestion File & Streaming Ingestion Cloud Data Integration Cloud SaaS LogsMachine Data Connected Devices Edge DatabasesApplication Servers Mainframe On-Premises Cloud Object Store Cloud Data Lake Cloud Data Warehouses Machine Learning Visualization Business Intelligence
  • 24. Data Integration Services Use Cases: Data ingestion, migration, synchronization, replication Synchronize SaaS and On-premises Data • Periodically sync SaaS and on-premises applications to Cloud DB/DW • Cloud Data stores are used for operational and analytic purposes. • Sync needs are both real time as well as batch Replicate Bulk Data to Cloud • Replicate on-premises data to DB/DW on Cloud • Cost savings and High Availability • Build using easy-to-use wizards Data Ingestion to Databases and Applications • Bulk ingestion of data sources • Involves reuse of common integration patterns like Slowly Changing Dimensions, error handling, etc. • Migrate existing on-premises DB/DW to cloud DB/DW
  • 25. Application Integration and API Management Services Use Cases: Real-time, API, and process integration needs • Integrate API-based applications in real time via APIs and messaging • Supplement bulk data integration of data sets with real-time data processing • Integrate with MOM brokers and ESB Real-time Data Integration • Create composite service and data APIs exposed as REST, SOAP, or OData services • Expose managed APIs to partners, customers, and internal consumers • Obtain visibility and control of the use of APIs API Creation and Management • Automate application and business processes • Provide interactive access to data to users and applications via API-enabled services and data sources • Provide users with automated and guided workflows Process Automation
  • 26. Demonstration of IICS Data Catalog & Data Integration Services w/ MongoDB integration
  • 27. 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 publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions 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, including any warranties of merchantability or fitness for a particular purpose. A Leader in Five Gartner Magic Quadrants Magic Quadrant for Master Data Management Solutions Michael Moran, et al., 12 December 2018 Magic Quadrant for Data Integration Tools Mark A. Beyer , et al., 19 July 2018 Magic Quadrant for Metadata Management Solutions Guido De Simoni, et al., 09 August 2018 Magic Quadrant for Data Quality Tools Melody Chien, et al., 27 March 2019 Magic Quadrant for Enterprise Integration Platform as a Service Eric Thoo, et al., 23 April 2019 July 2018Aug 2018 March 2019 Dec 2018Apr 2019
  • 28. 8T+ Transactions per month >300% Growth of API volume 7M+ Integrations/day 200%+ growth YoY 110+ OEMs 220+ Native Connectors >50% Annual revenue growth Volumes of data 2x Every 6 months Informatica Intelligent Cloud Services • Connecting 100,000 applications, databases, and other endpoints
  • 29. Informatica and MongoDB — Better Together • Complete—End to End Solution Enterprise Cloud Data Management including Data Integration, Quality, Governance and Master Data Management Streaming Application Integration and API Management Solution Support across hybrid and multi-cloud • Speed—Time to Insights/Productivity Automation and self-service 200+ codeless connectors Metadata-driven development • Fast—High Performance Optimized, scalable, native integration
  • 30. Questions? Please visit us at the Drivers and Connectors Booth!