Soumettre la recherche
Mettre en ligne
CWIN17 India / Insights platform architecture v1 0 virtual - subhadeep dutta
•
Télécharger en tant que PPTX, PDF
•
1 j'aime
•
818 vues
Capgemini
Suivre
Cloud architecture & Platforms
Lire moins
Lire la suite
Présentations et discours publics
Signaler
Partager
Signaler
Partager
1 sur 24
Télécharger maintenant
Recommandé
Top Trends in Building Data Lakes for Machine Learning and AI
Top Trends in Building Data Lakes for Machine Learning and AI
Holden Ackerman
Best Practices for Building a Data Lake with Amazon S3 - August 2016 Monthly ...
Best Practices for Building a Data Lake with Amazon S3 - August 2016 Monthly ...
Amazon Web Services
Architecting an Open Data Lake for the Enterprise
Architecting an Open Data Lake for the Enterprise
Amazon Web Services
Big Data in Azure
Big Data in Azure
DataWorks Summit/Hadoop Summit
How to Architect a Serverless Cloud Data Lake for Enhanced Data Analytics
How to Architect a Serverless Cloud Data Lake for Enhanced Data Analytics
Informatica
Big Data & Data Lakes Building Blocks
Big Data & Data Lakes Building Blocks
Amazon Web Services
Filling the Data Lake
Filling the Data Lake
DataWorks Summit/Hadoop Summit
Modern Data Architecture for a Data Lake with Informatica and Hortonworks Dat...
Modern Data Architecture for a Data Lake with Informatica and Hortonworks Dat...
Hortonworks
Recommandé
Top Trends in Building Data Lakes for Machine Learning and AI
Top Trends in Building Data Lakes for Machine Learning and AI
Holden Ackerman
Best Practices for Building a Data Lake with Amazon S3 - August 2016 Monthly ...
Best Practices for Building a Data Lake with Amazon S3 - August 2016 Monthly ...
Amazon Web Services
Architecting an Open Data Lake for the Enterprise
Architecting an Open Data Lake for the Enterprise
Amazon Web Services
Big Data in Azure
Big Data in Azure
DataWorks Summit/Hadoop Summit
How to Architect a Serverless Cloud Data Lake for Enhanced Data Analytics
How to Architect a Serverless Cloud Data Lake for Enhanced Data Analytics
Informatica
Big Data & Data Lakes Building Blocks
Big Data & Data Lakes Building Blocks
Amazon Web Services
Filling the Data Lake
Filling the Data Lake
DataWorks Summit/Hadoop Summit
Modern Data Architecture for a Data Lake with Informatica and Hortonworks Dat...
Modern Data Architecture for a Data Lake with Informatica and Hortonworks Dat...
Hortonworks
Big Data 2.0: ETL & Analytics: Implementing a next generation platform
Big Data 2.0: ETL & Analytics: Implementing a next generation platform
Caserta
Scaling Data Science on Big Data
Scaling Data Science on Big Data
DataWorks Summit
Module 1 - CP Datalake on AWS
Module 1 - CP Datalake on AWS
Lam Le
Securing your Big Data Environments in the Cloud
Securing your Big Data Environments in the Cloud
DataWorks Summit
Hadoop Journey at Walgreens
Hadoop Journey at Walgreens
DataWorks Summit
Artur Fejklowicz - “Data Lake architecture” AI&BigDataDay 2017
Artur Fejklowicz - “Data Lake architecture” AI&BigDataDay 2017
Lviv Startup Club
Microsoft Azure Big Data Analytics
Microsoft Azure Big Data Analytics
Mark Kromer
A Reference Architecture for ETL 2.0
A Reference Architecture for ETL 2.0
DataWorks Summit
Empowering you with Democratized Data Access, Data Science and Machine Learning
Empowering you with Democratized Data Access, Data Science and Machine Learning
DataWorks Summit
Data-In-Motion Unleashed
Data-In-Motion Unleashed
DataWorks Summit
McGraw-Hill Optimizes Analytics Workloads with Databricks
McGraw-Hill Optimizes Analytics Workloads with Databricks
Amazon Web Services
Big data architectures and the data lake
Big data architectures and the data lake
James Serra
Solving Big Data Problems using Hortonworks
Solving Big Data Problems using Hortonworks
DataWorks Summit/Hadoop Summit
Module 3 - QuickSight Overview
Module 3 - QuickSight Overview
Lam Le
Data Quality in the Data Hub with RedPointGlobal
Data Quality in the Data Hub with RedPointGlobal
Caserta
How Apache Hadoop is Revolutionizing Business Intelligence and Data Analytics...
How Apache Hadoop is Revolutionizing Business Intelligence and Data Analytics...
Amr Awadallah
2017 OpenWorld Keynote for Data Integration
2017 OpenWorld Keynote for Data Integration
Jeffrey T. Pollock
Big Data on Azure Tutorial
Big Data on Azure Tutorial
rustd
Enterprise large scale graph analytics and computing base on distribute graph...
Enterprise large scale graph analytics and computing base on distribute graph...
DataWorks Summit
Real-time Data Pipelines with SAP and Apache Kafka
Real-time Data Pipelines with SAP and Apache Kafka
Carole Gunst
Cloud Security Alliance's GRC Stack Overview
Cloud Security Alliance's GRC Stack Overview
Valdez Ladd MBA, CISSP, CISA,
Secure Configuration and Automation Overview
Secure Configuration and Automation Overview
Amazon Web Services
Contenu connexe
Tendances
Big Data 2.0: ETL & Analytics: Implementing a next generation platform
Big Data 2.0: ETL & Analytics: Implementing a next generation platform
Caserta
Scaling Data Science on Big Data
Scaling Data Science on Big Data
DataWorks Summit
Module 1 - CP Datalake on AWS
Module 1 - CP Datalake on AWS
Lam Le
Securing your Big Data Environments in the Cloud
Securing your Big Data Environments in the Cloud
DataWorks Summit
Hadoop Journey at Walgreens
Hadoop Journey at Walgreens
DataWorks Summit
Artur Fejklowicz - “Data Lake architecture” AI&BigDataDay 2017
Artur Fejklowicz - “Data Lake architecture” AI&BigDataDay 2017
Lviv Startup Club
Microsoft Azure Big Data Analytics
Microsoft Azure Big Data Analytics
Mark Kromer
A Reference Architecture for ETL 2.0
A Reference Architecture for ETL 2.0
DataWorks Summit
Empowering you with Democratized Data Access, Data Science and Machine Learning
Empowering you with Democratized Data Access, Data Science and Machine Learning
DataWorks Summit
Data-In-Motion Unleashed
Data-In-Motion Unleashed
DataWorks Summit
McGraw-Hill Optimizes Analytics Workloads with Databricks
McGraw-Hill Optimizes Analytics Workloads with Databricks
Amazon Web Services
Big data architectures and the data lake
Big data architectures and the data lake
James Serra
Solving Big Data Problems using Hortonworks
Solving Big Data Problems using Hortonworks
DataWorks Summit/Hadoop Summit
Module 3 - QuickSight Overview
Module 3 - QuickSight Overview
Lam Le
Data Quality in the Data Hub with RedPointGlobal
Data Quality in the Data Hub with RedPointGlobal
Caserta
How Apache Hadoop is Revolutionizing Business Intelligence and Data Analytics...
How Apache Hadoop is Revolutionizing Business Intelligence and Data Analytics...
Amr Awadallah
2017 OpenWorld Keynote for Data Integration
2017 OpenWorld Keynote for Data Integration
Jeffrey T. Pollock
Big Data on Azure Tutorial
Big Data on Azure Tutorial
rustd
Enterprise large scale graph analytics and computing base on distribute graph...
Enterprise large scale graph analytics and computing base on distribute graph...
DataWorks Summit
Real-time Data Pipelines with SAP and Apache Kafka
Real-time Data Pipelines with SAP and Apache Kafka
Carole Gunst
Tendances
(20)
Big Data 2.0: ETL & Analytics: Implementing a next generation platform
Big Data 2.0: ETL & Analytics: Implementing a next generation platform
Scaling Data Science on Big Data
Scaling Data Science on Big Data
Module 1 - CP Datalake on AWS
Module 1 - CP Datalake on AWS
Securing your Big Data Environments in the Cloud
Securing your Big Data Environments in the Cloud
Hadoop Journey at Walgreens
Hadoop Journey at Walgreens
Artur Fejklowicz - “Data Lake architecture” AI&BigDataDay 2017
Artur Fejklowicz - “Data Lake architecture” AI&BigDataDay 2017
Microsoft Azure Big Data Analytics
Microsoft Azure Big Data Analytics
A Reference Architecture for ETL 2.0
A Reference Architecture for ETL 2.0
Empowering you with Democratized Data Access, Data Science and Machine Learning
Empowering you with Democratized Data Access, Data Science and Machine Learning
Data-In-Motion Unleashed
Data-In-Motion Unleashed
McGraw-Hill Optimizes Analytics Workloads with Databricks
McGraw-Hill Optimizes Analytics Workloads with Databricks
Big data architectures and the data lake
Big data architectures and the data lake
Solving Big Data Problems using Hortonworks
Solving Big Data Problems using Hortonworks
Module 3 - QuickSight Overview
Module 3 - QuickSight Overview
Data Quality in the Data Hub with RedPointGlobal
Data Quality in the Data Hub with RedPointGlobal
How Apache Hadoop is Revolutionizing Business Intelligence and Data Analytics...
How Apache Hadoop is Revolutionizing Business Intelligence and Data Analytics...
2017 OpenWorld Keynote for Data Integration
2017 OpenWorld Keynote for Data Integration
Big Data on Azure Tutorial
Big Data on Azure Tutorial
Enterprise large scale graph analytics and computing base on distribute graph...
Enterprise large scale graph analytics and computing base on distribute graph...
Real-time Data Pipelines with SAP and Apache Kafka
Real-time Data Pipelines with SAP and Apache Kafka
Similaire à CWIN17 India / Insights platform architecture v1 0 virtual - subhadeep dutta
Cloud Security Alliance's GRC Stack Overview
Cloud Security Alliance's GRC Stack Overview
Valdez Ladd MBA, CISSP, CISA,
Secure Configuration and Automation Overview
Secure Configuration and Automation Overview
Amazon Web Services
Infrastructure Security: Your Minimum Security Baseline
Infrastructure Security: Your Minimum Security Baseline
Amazon Web Services
How Redlock Automates Security on AWS
How Redlock Automates Security on AWS
Amazon Web Services
HLC302_Adopting Microservices in Healthcare Building a Compliant DevOps Pipel...
HLC302_Adopting Microservices in Healthcare Building a Compliant DevOps Pipel...
Amazon Web Services
Examining Technical Best Practices for Veritas and AWS Using a Detailed Refer...
Examining Technical Best Practices for Veritas and AWS Using a Detailed Refer...
Veritas Technologies LLC
AWS - Security & Compliance
AWS - Security & Compliance
Amazon Web Services LATAM
Hybridní cloud s F5 v prostředí kontejnerů
Hybridní cloud s F5 v prostředí kontejnerů
MarketingArrowECS_CZ
Seven Criteria for Building an AWS Global Transit Network
Seven Criteria for Building an AWS Global Transit Network
Khash Nakhostin
Cloud Conversations: Giving Business Transformation a Voice_AWSPSSummit_Singa...
Cloud Conversations: Giving Business Transformation a Voice_AWSPSSummit_Singa...
Amazon Web Services
Hybrid Infrastructure Integration
Hybrid Infrastructure Integration
Amazon Web Services
AWS Security Best Practices and Design Patterns
AWS Security Best Practices and Design Patterns
Amazon Web Services
Hybrid Infrastructure Integration
Hybrid Infrastructure Integration
Amazon Web Services
Cloud Security 2014 AASNET
Cloud Security 2014 AASNET
Farrukh Shahzad
CloudPassage Best Practices for Automatic Security Scaling
CloudPassage Best Practices for Automatic Security Scaling
Amazon Web Services
Hybrid Infrastructure Integration
Hybrid Infrastructure Integration
Amazon Web Services
Toward Full Stack Security
Toward Full Stack Security
Amazon Web Services
AWS Core Services Overview, Immersion Day Huntsville 2019
AWS Core Services Overview, Immersion Day Huntsville 2019
Amazon Web Services
Hybrid Identity Management and Security for Large Enterprises (ENT307-R2) - A...
Hybrid Identity Management and Security for Large Enterprises (ENT307-R2) - A...
Amazon Web Services
(HLS401) Architecting for HIPAA Compliance on AWS | AWS re:Invent 2014
(HLS401) Architecting for HIPAA Compliance on AWS | AWS re:Invent 2014
Amazon Web Services
Similaire à CWIN17 India / Insights platform architecture v1 0 virtual - subhadeep dutta
(20)
Cloud Security Alliance's GRC Stack Overview
Cloud Security Alliance's GRC Stack Overview
Secure Configuration and Automation Overview
Secure Configuration and Automation Overview
Infrastructure Security: Your Minimum Security Baseline
Infrastructure Security: Your Minimum Security Baseline
How Redlock Automates Security on AWS
How Redlock Automates Security on AWS
HLC302_Adopting Microservices in Healthcare Building a Compliant DevOps Pipel...
HLC302_Adopting Microservices in Healthcare Building a Compliant DevOps Pipel...
Examining Technical Best Practices for Veritas and AWS Using a Detailed Refer...
Examining Technical Best Practices for Veritas and AWS Using a Detailed Refer...
AWS - Security & Compliance
AWS - Security & Compliance
Hybridní cloud s F5 v prostředí kontejnerů
Hybridní cloud s F5 v prostředí kontejnerů
Seven Criteria for Building an AWS Global Transit Network
Seven Criteria for Building an AWS Global Transit Network
Cloud Conversations: Giving Business Transformation a Voice_AWSPSSummit_Singa...
Cloud Conversations: Giving Business Transformation a Voice_AWSPSSummit_Singa...
Hybrid Infrastructure Integration
Hybrid Infrastructure Integration
AWS Security Best Practices and Design Patterns
AWS Security Best Practices and Design Patterns
Hybrid Infrastructure Integration
Hybrid Infrastructure Integration
Cloud Security 2014 AASNET
Cloud Security 2014 AASNET
CloudPassage Best Practices for Automatic Security Scaling
CloudPassage Best Practices for Automatic Security Scaling
Hybrid Infrastructure Integration
Hybrid Infrastructure Integration
Toward Full Stack Security
Toward Full Stack Security
AWS Core Services Overview, Immersion Day Huntsville 2019
AWS Core Services Overview, Immersion Day Huntsville 2019
Hybrid Identity Management and Security for Large Enterprises (ENT307-R2) - A...
Hybrid Identity Management and Security for Large Enterprises (ENT307-R2) - A...
(HLS401) Architecting for HIPAA Compliance on AWS | AWS re:Invent 2014
(HLS401) Architecting for HIPAA Compliance on AWS | AWS re:Invent 2014
Plus de Capgemini
Top Healthcare Trends 2022
Top Healthcare Trends 2022
Capgemini
Top P&C Insurance Trends 2022
Top P&C Insurance Trends 2022
Capgemini
Commercial Banking Trends book 2022
Commercial Banking Trends book 2022
Capgemini
Top Trends in Payments 2022
Top Trends in Payments 2022
Capgemini
Top Trends in Wealth Management 2022
Top Trends in Wealth Management 2022
Capgemini
Retail Banking Trends book 2022
Retail Banking Trends book 2022
Capgemini
Top Life Insurance Trends 2022
Top Life Insurance Trends 2022
Capgemini
キャップジェミニ、あなたの『RISE WITH SAP』のパートナーです
キャップジェミニ、あなたの『RISE WITH SAP』のパートナーです
Capgemini
Property & Casualty Insurance Top Trends 2021
Property & Casualty Insurance Top Trends 2021
Capgemini
Life Insurance Top Trends 2021
Life Insurance Top Trends 2021
Capgemini
Top Trends in Commercial Banking: 2021
Top Trends in Commercial Banking: 2021
Capgemini
Top Trends in Wealth Management: 2021
Top Trends in Wealth Management: 2021
Capgemini
Top Trends in Payments: 2021
Top Trends in Payments: 2021
Capgemini
Health Insurance Top Trends 2021
Health Insurance Top Trends 2021
Capgemini
Top Trends in Retail Banking: 2021
Top Trends in Retail Banking: 2021
Capgemini
Capgemini’s Connected Autonomous Planning
Capgemini’s Connected Autonomous Planning
Capgemini
Top Trends in Retail Banking: 2020
Top Trends in Retail Banking: 2020
Capgemini
Top Trends in Life Insurance: 2020
Top Trends in Life Insurance: 2020
Capgemini
Top Trends in Health Insurance: 2020
Top Trends in Health Insurance: 2020
Capgemini
Top Trends in Payments: 2020
Top Trends in Payments: 2020
Capgemini
Plus de Capgemini
(20)
Top Healthcare Trends 2022
Top Healthcare Trends 2022
Top P&C Insurance Trends 2022
Top P&C Insurance Trends 2022
Commercial Banking Trends book 2022
Commercial Banking Trends book 2022
Top Trends in Payments 2022
Top Trends in Payments 2022
Top Trends in Wealth Management 2022
Top Trends in Wealth Management 2022
Retail Banking Trends book 2022
Retail Banking Trends book 2022
Top Life Insurance Trends 2022
Top Life Insurance Trends 2022
キャップジェミニ、あなたの『RISE WITH SAP』のパートナーです
キャップジェミニ、あなたの『RISE WITH SAP』のパートナーです
Property & Casualty Insurance Top Trends 2021
Property & Casualty Insurance Top Trends 2021
Life Insurance Top Trends 2021
Life Insurance Top Trends 2021
Top Trends in Commercial Banking: 2021
Top Trends in Commercial Banking: 2021
Top Trends in Wealth Management: 2021
Top Trends in Wealth Management: 2021
Top Trends in Payments: 2021
Top Trends in Payments: 2021
Health Insurance Top Trends 2021
Health Insurance Top Trends 2021
Top Trends in Retail Banking: 2021
Top Trends in Retail Banking: 2021
Capgemini’s Connected Autonomous Planning
Capgemini’s Connected Autonomous Planning
Top Trends in Retail Banking: 2020
Top Trends in Retail Banking: 2020
Top Trends in Life Insurance: 2020
Top Trends in Life Insurance: 2020
Top Trends in Health Insurance: 2020
Top Trends in Health Insurance: 2020
Top Trends in Payments: 2020
Top Trends in Payments: 2020
Dernier
Aesthetic Colaba Mumbai Cst Call girls 📞 7738631006 Grant road Call Girls ❤️-...
Aesthetic Colaba Mumbai Cst Call girls 📞 7738631006 Grant road Call Girls ❤️-...
Pooja Nehwal
Chiulli_Aurora_Oman_Raffaele_Beowulf.pptx
Chiulli_Aurora_Oman_Raffaele_Beowulf.pptx
raffaeleoman
Report Writing Webinar Training
Report Writing Webinar Training
KylaCullinane
Busty Desi⚡Call Girls in Sector 51 Noida Escorts >༒8448380779 Escort Service-...
Busty Desi⚡Call Girls in Sector 51 Noida Escorts >༒8448380779 Escort Service-...
Delhi Call girls
AWS Data Engineer Associate (DEA-C01) Exam Dumps 2024.pdf
AWS Data Engineer Associate (DEA-C01) Exam Dumps 2024.pdf
SkillCertProExams
BDSM⚡Call Girls in Sector 93 Noida Escorts >༒8448380779 Escort Service
BDSM⚡Call Girls in Sector 93 Noida Escorts >༒8448380779 Escort Service
Delhi Call girls
ICT role in 21st century education and it's challenges.pdf
ICT role in 21st century education and it's challenges.pdf
Islamia university of Rahim Yar khan campus
Uncommon Grace The Autobiography of Isaac Folorunso
Uncommon Grace The Autobiography of Isaac Folorunso
Kayode Fayemi
The workplace ecosystem of the future 24.4.2024 Fabritius_share ii.pdf
The workplace ecosystem of the future 24.4.2024 Fabritius_share ii.pdf
Senaatti-kiinteistöt
Thirunelveli call girls Tamil escorts 7877702510
Thirunelveli call girls Tamil escorts 7877702510
Vipesco
Presentation on Engagement in Book Clubs
Presentation on Engagement in Book Clubs
samaasim06
My Presentation "In Your Hands" by Halle Bailey
My Presentation "In Your Hands" by Halle Bailey
hlharris
Causes of poverty in France presentation.pptx
Causes of poverty in France presentation.pptx
CamilleBoulbin1
SaaStr Workshop Wednesday w/ Lucas Price, Yardstick
SaaStr Workshop Wednesday w/ Lucas Price, Yardstick
saastr
Introduction to Prompt Engineering (Focusing on ChatGPT)
Introduction to Prompt Engineering (Focusing on ChatGPT)
Chameera Dedduwage
If this Giant Must Walk: A Manifesto for a New Nigeria
If this Giant Must Walk: A Manifesto for a New Nigeria
Kayode Fayemi
BDSM⚡Call Girls in Sector 97 Noida Escorts >༒8448380779 Escort Service
BDSM⚡Call Girls in Sector 97 Noida Escorts >༒8448380779 Escort Service
Delhi Call girls
Bring back lost lover in USA, Canada ,Uk ,Australia ,London Lost Love Spell C...
Bring back lost lover in USA, Canada ,Uk ,Australia ,London Lost Love Spell C...
amilabibi1
lONG QUESTION ANSWER PAKISTAN STUDIES10.
lONG QUESTION ANSWER PAKISTAN STUDIES10.
lodhisaajjda
No Advance 8868886958 Chandigarh Call Girls , Indian Call Girls For Full Nigh...
No Advance 8868886958 Chandigarh Call Girls , Indian Call Girls For Full Nigh...
Sheetaleventcompany
Dernier
(20)
Aesthetic Colaba Mumbai Cst Call girls 📞 7738631006 Grant road Call Girls ❤️-...
Aesthetic Colaba Mumbai Cst Call girls 📞 7738631006 Grant road Call Girls ❤️-...
Chiulli_Aurora_Oman_Raffaele_Beowulf.pptx
Chiulli_Aurora_Oman_Raffaele_Beowulf.pptx
Report Writing Webinar Training
Report Writing Webinar Training
Busty Desi⚡Call Girls in Sector 51 Noida Escorts >༒8448380779 Escort Service-...
Busty Desi⚡Call Girls in Sector 51 Noida Escorts >༒8448380779 Escort Service-...
AWS Data Engineer Associate (DEA-C01) Exam Dumps 2024.pdf
AWS Data Engineer Associate (DEA-C01) Exam Dumps 2024.pdf
BDSM⚡Call Girls in Sector 93 Noida Escorts >༒8448380779 Escort Service
BDSM⚡Call Girls in Sector 93 Noida Escorts >༒8448380779 Escort Service
ICT role in 21st century education and it's challenges.pdf
ICT role in 21st century education and it's challenges.pdf
Uncommon Grace The Autobiography of Isaac Folorunso
Uncommon Grace The Autobiography of Isaac Folorunso
The workplace ecosystem of the future 24.4.2024 Fabritius_share ii.pdf
The workplace ecosystem of the future 24.4.2024 Fabritius_share ii.pdf
Thirunelveli call girls Tamil escorts 7877702510
Thirunelveli call girls Tamil escorts 7877702510
Presentation on Engagement in Book Clubs
Presentation on Engagement in Book Clubs
My Presentation "In Your Hands" by Halle Bailey
My Presentation "In Your Hands" by Halle Bailey
Causes of poverty in France presentation.pptx
Causes of poverty in France presentation.pptx
SaaStr Workshop Wednesday w/ Lucas Price, Yardstick
SaaStr Workshop Wednesday w/ Lucas Price, Yardstick
Introduction to Prompt Engineering (Focusing on ChatGPT)
Introduction to Prompt Engineering (Focusing on ChatGPT)
If this Giant Must Walk: A Manifesto for a New Nigeria
If this Giant Must Walk: A Manifesto for a New Nigeria
BDSM⚡Call Girls in Sector 97 Noida Escorts >༒8448380779 Escort Service
BDSM⚡Call Girls in Sector 97 Noida Escorts >༒8448380779 Escort Service
Bring back lost lover in USA, Canada ,Uk ,Australia ,London Lost Love Spell C...
Bring back lost lover in USA, Canada ,Uk ,Australia ,London Lost Love Spell C...
lONG QUESTION ANSWER PAKISTAN STUDIES10.
lONG QUESTION ANSWER PAKISTAN STUDIES10.
No Advance 8868886958 Chandigarh Call Girls , Indian Call Girls For Full Nigh...
No Advance 8868886958 Chandigarh Call Girls , Indian Call Girls For Full Nigh...
CWIN17 India / Insights platform architecture v1 0 virtual - subhadeep dutta
1.
Cloud Architectures &
Platforms CWIN17, September 27th 2017 Presenter : SHUVADEEP DUTTA, Insights Platform, Insights & Data
2.
2Copyright © Capgemini
2017 All Rights Reserved 2Copyright © Capgemini 2017. All Rights Reserved AGENDA Platform Architecture Views Cloud Platform Security Platform Logging Platform DevOps
3.
3Copyright © Capgemini
2017 All Rights Reserved 3Copyright © Capgemini 2017. All Rights Reserved Future Looking Data Lake – Conceptual Architecture
4.
4Copyright © Capgemini
2017 All Rights Reserved 4Copyright © Capgemini 2017. All Rights Reserved Big Data and Analytics Platform Logical Architecture – Cloud & Technology Agnostic View
5.
5Copyright © Capgemini
2017 All Rights Reserved 5Copyright © Capgemini 2017. All Rights Reserved Big Data and Analytics Cloud Platform – MS Azure / AWS Native Services
6.
6Copyright © Capgemini
2017 All Rights Reserved 6Copyright © Capgemini 2017. All Rights Reserved Big Data and Analytics Cloud Platform – Custom Built Stack (Opensource Hortonworks)
7.
7Copyright © Capgemini
2017 All Rights Reserved 7Copyright © Capgemini 2017. All Rights Reserved Cloud Deployment Considerations Data topology, governance & security capabilities need to be evaluated taking into consideration the key considerations to define a target state hybrid cloud platform architecture Focus Area Consideration Data Location Location of data storage in alignment with regional regulatory compliance directives Analytics Use Cases Type of analytical workloads going to be executed on the data repository located at a specific region / country Data Access, Authentication and Authorization Mechanism of data and underlying platform resource access based on specific user role, user location, time of access etc. Network Latency Volume of data transfer over network ensuring appropriate bandwidth and SLAs being met Data Ingestion Type of data ingestion mechanisms used to transfer data from on-premise to cloud and vice-versa Security and Regulatory Compliance Implementation of controls and mechanisms to meet platform security (perimeter, data and application), regional regulatory compliance directives such as PCI, SOX etc. Platform Governance Platform wide metadata management, audit logging, master and reference data management capabilities; considerations for bottom-up / top-down /Hybrid approaches: Data Catalog driven data discovery and knowledge sharing (bottom-up) vs. Data Governance Council (Data Stewardship) driven information asset management and knowledge sharing (Top-down) Platform Infrastructure Considerations for High Availability, Fault Tolerant and Disaster Recovery capabilities Considerations from platform performance and scalability based on specific Big Data Analytics workload use cases Considerations for Platform resource management and orchestration Data and Application Portability Considerations for data and application portability across different platform environments e.g. On-premise, Private, Public cloud
8.
The information contained
in this presentation is proprietary. Copyright © 2016 Capgemini. All rights reserved. Rightshore® is a trademark belonging to Capgemini. www.capgemini.com 8Copyright © Capgemini 2017. All Rights Reserved Capgemini’s DaaS (Data as a Service) Solution Framework Meet all data and analytics management service needs from data ingestion, preparation, discovery, through till data analysis using opensource or commercial tools Leverage client’s current investments and integrate with technology of client choice or extend / customize existing framework capabilities
9.
9Copyright © Capgemini
2017 All Rights Reserved Cloud Platform Security
10.
10Copyright © Capgemini
2017 All Rights Reserved 10Copyright © Capgemini 2017. All Rights Reserved Big Data and Analytics Platform – Cloud Security Framework Physical Asset Security Management Protection for physical assets and locations including networks and data centers Cloud Governance Cloud specific security governance including directory synchronization and geo locational support Information Asset Protection Protection of data at rest or in transit Governance & Compliance Security governance, maintenance of security policy, audit and compliance Threats and Vulnerability Management Management of vulnerabilities and mitigations with Network and endpoint protection Incident Management Management and responding to expected and unexpected events Identity and Access Management Authentication of users and management of identity
11.
11Copyright © Capgemini
2017 All Rights Reserved 11Copyright © Capgemini 2017. All Rights Reserved Cloud Security Capability Framework – Shared Responsibility Model
12.
12Copyright © Capgemini
2017 All Rights Reserved 12Copyright © Capgemini 2017. All Rights Reserved AWS VPC Security Reference Architecture VPC Security Architecture Scenarios Scenario 1 : VPC with a Single Public Subnet only • Instances run in a private, isolated section of the AWS cloud with direct access to the Internet • Network ACLs and security groups can be used to provide strict control over inbound and outbound network traffic to EC2 instances Scenario 2 : VPC with Public and Private Subnets and NAT • In addition to public subnet, a private subnet is added whose instances are not addressable from the Internet • Instances in the private subnet can establish outbound connections to the Internet via the public subnet using Network Address Translation (NAT Gateway or Instance) Scenario 3 : VPC with Public and Private Subnets and hardware VPN access • IPsec VPN connection between Amazon VPC and customer data center, while also providing direct access to the Internet for public subnet instances in Amazon VPC • VPN appliance on customer corporate data center side Scenario 4 : VPC with Private Subnet only and hardware VPN access • Instances run in a private, isolated section of the AWS cloud with a private subnet whose instances are not addressable from the Internet • Private subnet is connected to customer data center via an IPsec VPN tunnel
13.
13Copyright © Capgemini
2017 All Rights Reserved 13Copyright © Capgemini 2017. All Rights Reserved AWS VPC Security Reference Architecture – Security Groups VPC security groups to firewall each EC2 instance Each instance can be in up to 5 security groups Separate security groups for applications and management Security groups are stateful with ingress and egress rules Max. 50 rules per security group VPC Router will allow any subnet to route to another in VPC Network Access Control Lists are used to restrict internal VPC traffic Elastic load balancers are used to distribute traffic between instances Elastic load balancers are also placed in security groups Platform security can scale up and down with solution; instances can be added into security groups during launch time Use NAT instances to provide internet connectivity for Private Subnets; allow backend servers to route to AWS APIs – Ex. storing logs in S3 bucket or using DynamoDB, SES Access AWS API endpoints through the Internet Gateway like S3, SES, DynamoDB, SNS etc.
14.
14Copyright © Capgemini
2017 All Rights Reserved 14Copyright © Capgemini 2017. All Rights Reserved AWS Identity and Access Management Securely control access to AWS services and resources Fine grained control of user permissions, resources and actions Support for RunInstances Multi Factor Authentication – Hardware token or Smartphone Apps Segregation of roles using IAM AWS Account Owner (Master) Network Management Security Management Server Management Storage Management
15.
15Copyright © Capgemini
2017 All Rights Reserved 15Copyright © Capgemini 2017. All Rights Reserved AWS Identity and Access Management Role Based Security
16.
16Copyright © Capgemini
2017 All Rights Reserved 16Copyright © Capgemini 2017. All Rights Reserved AWS Identity and Access Management using Enterprise’ existing Active Directory Flow 1 2 3 4 The enterprise user accesses the identity broker application The identity broker application authenticates the users against the corporate identity store The identity broker application has permissions to access the AWS Security Token Service (STS) to request temporary security credentials Enterprise users get a temporary URL that gives them access to the AWS APIs or the Management Console AWS Identity Federation with Temporary Security Credentials
17.
17Copyright © Capgemini
2017 All Rights Reserved 17Copyright © Capgemini 2017. All Rights Reserved AWS Data Storage Security – Capabilities AWS S3 Capabilities – Access controls at bucket and object level Cryptographic capabilities such as SSL for data in motion, Server/Client side encryption, MD5 checksums AWS Redshift Capabilities – Full disk encryption; CloudHSM to store keys Back-up access logs to S3 for analysis Security groups and VPC for deployment; data loading using SSL from S3 with restricted access to S3 SSL encryption for data accessed over internet AWS RDS Capabilities – Restricted access to RDS instances using Security groups and IAM permissions Data encryption (Data at rest and in motion) Automatic patching for minor updates AWS DynamoDB Capabilities – Fine grained security access to columns and rows using IAM role and access policies AWS EBS Volume Capabilities – Option to use own encryption or commercial solutions Ex. Windows BitLocker or Linux LUKS for encrypted volumes and TrueCrypt for containers; Commercial : Safenet Protect-V, Trend Secure Cloud etc.
18.
18Copyright © Capgemini
2017 All Rights Reserved 18Copyright © Capgemini 2017. All Rights Reserved Securing AWS Applications Process Flow
19.
19Copyright © Capgemini
2017 All Rights Reserved Platform Logging
20.
20Copyright © Capgemini
2017 All Rights Reserved 20Copyright © Capgemini 2017. All Rights Reserved Platform Monitoring – Centralized Troubleshooting, Security, Audit and Monitoring
21.
21Copyright © Capgemini
2017 All Rights Reserved 21Copyright © Capgemini 2017. All Rights Reserved Platform Monitoring – Solution Options Shippers Queue Logstash Elasticsearch Elasticsearch Kibana Log Parsing Indexing & Curation Dashboards & ReportsRedis, RabbirMQ, KafkaSyslog, Rsyslog, Logstash, Fluentd etc. JSONEvents Extract Option 1 – Custom Built using ELK stack (Elasticsearch, Logstash and Kibana) Option 2 – SaaS Solution – Loggly (alternate leading tool : Sumologic) Shippers Syslog, Rsyslog, Logstash, Fluentd, cloud plug-ins etc. Application Framework INGEST PROCESS INDEX Search & Other Services • Cloud-based SaaS for easy central log collection, aggregation, management • Easy set-up • Dynamic parsing - Real-time, JSON support, parsing/tagging, self-documenting • Regular Expressions based • Dashboards, pre-configured and customizable, shareable • Anomaly Detection • Alerts that can be sent to HipChat, Slack, PagerDuty, HTTP endpoints, others • JIRA Software integration, point-and click ticket creation without leaving Loggly
22.
22Copyright © Capgemini
2017 All Rights Reserved Platform DevOps
23.
23Copyright © Capgemini
2017 All Rights Reserved 23Copyright © Capgemini 2017. All Rights Reserved DevOps Reference Architecture for Big Data Analytics Workloads
24.
The information contained
in this presentation is proprietary. Copyright © 2015 Capgemini. All rights reserved. Rightshore® is a trademark belonging to Capgemini. www.capgemini.com About Capgemini With more than 145,000 people in over 40 countries, Capgemini is one of the world's foremost providers of consulting, technology and outsourcing services. The Group reported 2014 global revenues of EUR 10.573 billion. Together with its clients, Capgemini creates and delivers business and technology solutions that fit their needs and drive the results they want. A deeply multicultural organization, Capgemini has developed its own way of working, the Collaborative Business Experience™, and draws on Rightshore®, its worldwide delivery model Learn more about us at www.capgemini.com.
Télécharger maintenant