SlideShare a Scribd company logo
AstraZeneca – Amazon Analytics Cloud Services
Amazon Analytics Cloud Services 
British-Swedish multinational pharmaceutical and biologics company 
Business Context / 
Challenges 
Integration challenges 
• Point to point interfaces 
• Local reporting and data 
gathering to fill the gaps 
• Intensive manual 
reconciliation 
• Local systems to resolve 
integration gaps, incurring 
local costs and support 
effort 
• Little re-use of data for 
multiple purposes 
Pain points 
• Duplicated licences and 
contracts 
• Tying up headcount in 
duplicated tasks 
• Fragmented reporting and 
reconciliation 
• Multiple integration points 
Solution 
HCL provides a comprehensive cloud based 
solution which comprises of the following in addition to 
requirements specified in RFI(detailed solution 
explanation provided in subsequent slides): 
• A robust, proven, secure, public cloud service 
from Amazon Web Services (AWS) with menu 
based pricing 
• A powerful data processing layer which can 
leverage elastic computing 
• Pre-defined set of data connectors and 
adapters that can be leveraged to easily pull data 
having different formats (structured, semi-structured 
and unstructured) from different 
sources 
• A wide variety of technology options to 
implement best of breed technologies for meeting 
AstraZeneca’s requirements 
• APIs that allow easy connection to different 
sets of analytics, visualization and reporting tools 
• A robust Data Quality Framework to ensure 
quality of data being processed for purpose of 
reporting. Availability of pre-defined operational 
dashboards 
• A Next generation platform to enable advanced 
analytics using BigData frameworks 
Potential Benefits 
Universal 
• Commonly understood view of 
sales & marketing information 
Integrated 
• Correlated with other data and 
governed by common master 
data 
On Demand 
• Available when required, 
accessible in the right format, 
timely 
Cost Effective 
• More for less cost and effort 
(IT and business) 
• Delivered through a smart 
technology layer and toolset 
built once, shared many times 
Copyright © 2014 HCL Technologies Limited 2 | www.hcltech.com
HCL’s Understanding of Requirements 
Data Hosting Data Supply Data Processing 
Analysis, Visualizations & 
Reporting 
Others 
Data partitioning Structured & unstructured data Create custom reports Create custom reports UI/ UX 
customization 
Data backup & 
restore 
Delta updates Work on permitted data Access reports across 
devices 
Internationalization 
& localization 
Secure data access Batch updates Collaborate on permitted 
data 
Use existing tools Friendly user 
interface 
Secure data holding Secure upload Task based collaboration Secure work areas Security policies 
Scalable Scalable & flexible Use existing tools Performance SLAs 
Monitoring AZ, Partner & Web data Report management 
Publish reports on the web Secure work areas 
User management 
Traffic management 
Task/workflow management 
Upload management 
Copyright © 2014 HCL Technologies Limited 3 | www.hcltech.com 
3 
@ 
Data 
Supply 
Data 
Processing 
Analytics & 
Visualization 
AZ 
Enterprise 
Data 
Third Party Data 
& Web Data 
Analysts 
Local 
Market Data 
Dashboards 
& Reports 
Publish 
Dashboards 
& Reports 
End 
Users 
Data Hosting 
Dashboards 
& Reports
Solution Architecture 
AZ 
AZ Global Enterprise 
Global Firewall 
Data Landing Zone 
EDW 
Additional 
Enterprise 
Data 
(Source 1) 
Additional 
Enterprise 
Data 
(Source 2) 
AZ Local/Regional Enterprise 
Local Firewall 
Data Landing Zone 
Regional 
Data 
AZ Local/Regional Enterprise 
Local Firewall 
Data Landing Zone 
Regional 
Data 
Data Supply Data Processing Data Hosting 
Monitoring 
AWS 
Monitoring 
Monitoring 
AWS 
Monitoring 
Monitoring 
AWS 
Monitoring 
DWH On Cloud 
AWS Redshift 
DB User based Access Control 
Global Data Region 1 Data Region 2 Data 
Data Processing Zone 
AWS Informatica/ Elastic Map Reduce 
Data Validation Processing Program/Job 
Landing Zone/ Staging Area 
AWS Redshift 
Global Bucket 
(EDW + 
Additional Enterprise Data 
Local/Region 1 
Bucket 
Local/Region 2 
Bucket 
Access Control 
Reporting, Analysis and Visualization 
Single Sign-on-AWS 
Identity and Access 
Management/ Any 
other IAM on AWS 
Analysis Tool 
SAS(on AWS Instance) 
Role Based Access Control 
Analytics Workbench 
Connector(S) 
Reporting, Visualization Tools 
Existing Tools, on premise or 
on AWS 
Role Based Access Control 
Reporting 
Module 
Visualization 
Module 
Connector(S) 
Copyright © 2014 HCL Technologies Limited 4 | www.hcltech.com 
AZ Source Data/Systems Amazon Web Services Consumer

More Related Content

What's hot

Cloud computing
Cloud computingCloud computing
Cloud computing
Mohd Masood
 
Data Center Transformation to Cloud - Mindmap
Data Center Transformation to Cloud - MindmapData Center Transformation to Cloud - Mindmap
Data Center Transformation to Cloud - Mindmap
WAJAHAT IQBAL
 
Solution architecture Amazon web services
Solution architecture Amazon web servicesSolution architecture Amazon web services
Solution architecture Amazon web services
Sandeep Sharma IIMK Smart City,IoT,Bigdata,Cloud,BI,DW
 
InterSystems Data Platform Comparison Chart
InterSystems Data Platform Comparison ChartInterSystems Data Platform Comparison Chart
InterSystems Data Platform Comparison Chart
Todd Winey
 
Data As Service (Team: 5, Project: 17)
Data As Service (Team: 5, Project: 17) Data As Service (Team: 5, Project: 17)
Data As Service (Team: 5, Project: 17)
Pankaj Shipte
 
Introducing Direct Database Access with Snowflake + Intrinio
Introducing Direct Database Access with Snowflake + IntrinioIntroducing Direct Database Access with Snowflake + Intrinio
Introducing Direct Database Access with Snowflake + Intrinio
Intrinio
 
Snowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for EveryoneSnowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for Everyone
Angel Abundez
 
Дмитрий Попович "How to build a data warehouse?"
Дмитрий Попович "How to build a data warehouse?"Дмитрий Попович "How to build a data warehouse?"
Дмитрий Попович "How to build a data warehouse?"
Fwdays
 
CloudCast
CloudCastCloudCast
CloudCast
GeneXus
 
Cloud Computing : Core Features and Three Models
Cloud Computing : Core Features and Three ModelsCloud Computing : Core Features and Three Models
Cloud Computing : Core Features and Three Models
Gobinda Chandra Dey
 
USA Information Security Compliance Market Overview
USA Information Security Compliance Market OverviewUSA Information Security Compliance Market Overview
USA Information Security Compliance Market Overview
Niraj Singhvi
 
Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"
Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"
Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"
Fwdays
 
Process Batch transaction using AzureBlob Integration with Apache Camel
Process Batch transaction using AzureBlob Integration with Apache CamelProcess Batch transaction using AzureBlob Integration with Apache Camel
Process Batch transaction using AzureBlob Integration with Apache Camel
Srikant Mantha
 
Modern business intelligence
Modern business intelligenceModern business intelligence
Modern business intelligence
Michael Stephenson
 
[WSO2Con EU 2017] WHO CARES? A WSO2 Cloud Oriented Reference Architecture for...
[WSO2Con EU 2017] WHO CARES? A WSO2 Cloud Oriented Reference Architecture for...[WSO2Con EU 2017] WHO CARES? A WSO2 Cloud Oriented Reference Architecture for...
[WSO2Con EU 2017] WHO CARES? A WSO2 Cloud Oriented Reference Architecture for...
WSO2
 
Infrastructure as a Service
Infrastructure as a ServiceInfrastructure as a Service
Infrastructure as a Service
SwiftTech Solutions, Inc.
 
Why Business Intelligence Should Consider Agile Modern Data Delivery Platform
Why Business Intelligence Should Consider Agile Modern Data Delivery PlatformWhy Business Intelligence Should Consider Agile Modern Data Delivery Platform
Why Business Intelligence Should Consider Agile Modern Data Delivery Platform
syed_javed
 
Cloud Computing IaaS
Cloud Computing IaaSCloud Computing IaaS
Cloud Computing IaaS
Chris Sparshott
 
Solution Architecture Cassandra
Solution Architecture CassandraSolution Architecture Cassandra
TrueSight Enterprise Edition
TrueSight Enterprise EditionTrueSight Enterprise Edition
TrueSight Enterprise Edition
michaelkmcdowell
 

What's hot (20)

Cloud computing
Cloud computingCloud computing
Cloud computing
 
Data Center Transformation to Cloud - Mindmap
Data Center Transformation to Cloud - MindmapData Center Transformation to Cloud - Mindmap
Data Center Transformation to Cloud - Mindmap
 
Solution architecture Amazon web services
Solution architecture Amazon web servicesSolution architecture Amazon web services
Solution architecture Amazon web services
 
InterSystems Data Platform Comparison Chart
InterSystems Data Platform Comparison ChartInterSystems Data Platform Comparison Chart
InterSystems Data Platform Comparison Chart
 
Data As Service (Team: 5, Project: 17)
Data As Service (Team: 5, Project: 17) Data As Service (Team: 5, Project: 17)
Data As Service (Team: 5, Project: 17)
 
Introducing Direct Database Access with Snowflake + Intrinio
Introducing Direct Database Access with Snowflake + IntrinioIntroducing Direct Database Access with Snowflake + Intrinio
Introducing Direct Database Access with Snowflake + Intrinio
 
Snowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for EveryoneSnowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for Everyone
 
Дмитрий Попович "How to build a data warehouse?"
Дмитрий Попович "How to build a data warehouse?"Дмитрий Попович "How to build a data warehouse?"
Дмитрий Попович "How to build a data warehouse?"
 
CloudCast
CloudCastCloudCast
CloudCast
 
Cloud Computing : Core Features and Three Models
Cloud Computing : Core Features and Three ModelsCloud Computing : Core Features and Three Models
Cloud Computing : Core Features and Three Models
 
USA Information Security Compliance Market Overview
USA Information Security Compliance Market OverviewUSA Information Security Compliance Market Overview
USA Information Security Compliance Market Overview
 
Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"
Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"
Дмитрий Лавриненко "Big & Fast Data for Identity & Telemetry services"
 
Process Batch transaction using AzureBlob Integration with Apache Camel
Process Batch transaction using AzureBlob Integration with Apache CamelProcess Batch transaction using AzureBlob Integration with Apache Camel
Process Batch transaction using AzureBlob Integration with Apache Camel
 
Modern business intelligence
Modern business intelligenceModern business intelligence
Modern business intelligence
 
[WSO2Con EU 2017] WHO CARES? A WSO2 Cloud Oriented Reference Architecture for...
[WSO2Con EU 2017] WHO CARES? A WSO2 Cloud Oriented Reference Architecture for...[WSO2Con EU 2017] WHO CARES? A WSO2 Cloud Oriented Reference Architecture for...
[WSO2Con EU 2017] WHO CARES? A WSO2 Cloud Oriented Reference Architecture for...
 
Infrastructure as a Service
Infrastructure as a ServiceInfrastructure as a Service
Infrastructure as a Service
 
Why Business Intelligence Should Consider Agile Modern Data Delivery Platform
Why Business Intelligence Should Consider Agile Modern Data Delivery PlatformWhy Business Intelligence Should Consider Agile Modern Data Delivery Platform
Why Business Intelligence Should Consider Agile Modern Data Delivery Platform
 
Cloud Computing IaaS
Cloud Computing IaaSCloud Computing IaaS
Cloud Computing IaaS
 
Solution Architecture Cassandra
Solution Architecture CassandraSolution Architecture Cassandra
Solution Architecture Cassandra
 
TrueSight Enterprise Edition
TrueSight Enterprise EditionTrueSight Enterprise Edition
TrueSight Enterprise Edition
 

Viewers also liked

Choosing the Right Data Storage Solution
Choosing the Right Data Storage SolutionChoosing the Right Data Storage Solution
Choosing the Right Data Storage Solution
Amazon Web Services
 
BDT305 Transforming Big Data with Spark and Shark - AWS re: Invent 2012
BDT305 Transforming Big Data with Spark and Shark - AWS re: Invent 2012BDT305 Transforming Big Data with Spark and Shark - AWS re: Invent 2012
BDT305 Transforming Big Data with Spark and Shark - AWS re: Invent 2012
Amazon Web Services
 
Semantic 'Radar' Steers Users to Insights in the Data Lake
Semantic 'Radar' Steers Users to Insights in the Data LakeSemantic 'Radar' Steers Users to Insights in the Data Lake
Semantic 'Radar' Steers Users to Insights in the Data Lake
Cognizant
 
(HLS402) Getting into Your Genes: The Definitive Guide to Using Amazon EMR, A...
(HLS402) Getting into Your Genes: The Definitive Guide to Using Amazon EMR, A...(HLS402) Getting into Your Genes: The Definitive Guide to Using Amazon EMR, A...
(HLS402) Getting into Your Genes: The Definitive Guide to Using Amazon EMR, A...
Amazon Web Services
 
(BDT401) Big Data Orchestra - Harmony within Data Analysis Tools | AWS re:Inv...
(BDT401) Big Data Orchestra - Harmony within Data Analysis Tools | AWS re:Inv...(BDT401) Big Data Orchestra - Harmony within Data Analysis Tools | AWS re:Inv...
(BDT401) Big Data Orchestra - Harmony within Data Analysis Tools | AWS re:Inv...
Amazon Web Services
 
(BDT302) Big Data Beyond Hadoop: Running Mahout, Giraph, and R on Amazon EMR ...
(BDT302) Big Data Beyond Hadoop: Running Mahout, Giraph, and R on Amazon EMR ...(BDT302) Big Data Beyond Hadoop: Running Mahout, Giraph, and R on Amazon EMR ...
(BDT302) Big Data Beyond Hadoop: Running Mahout, Giraph, and R on Amazon EMR ...
Amazon Web Services
 
Maximizing EC2 and Elastic Block Store Disk Performance
Maximizing EC2 and Elastic Block Store Disk PerformanceMaximizing EC2 and Elastic Block Store Disk Performance
Maximizing EC2 and Elastic Block Store Disk Performance
Amazon Web Services
 
(BDT308) Using Amazon Elastic MapReduce as Your Scalable Data Warehouse | AWS...
(BDT308) Using Amazon Elastic MapReduce as Your Scalable Data Warehouse | AWS...(BDT308) Using Amazon Elastic MapReduce as Your Scalable Data Warehouse | AWS...
(BDT308) Using Amazon Elastic MapReduce as Your Scalable Data Warehouse | AWS...
Amazon Web Services
 
(BDT310) Big Data Architectural Patterns and Best Practices on AWS | AWS re:I...
(BDT310) Big Data Architectural Patterns and Best Practices on AWS | AWS re:I...(BDT310) Big Data Architectural Patterns and Best Practices on AWS | AWS re:I...
(BDT310) Big Data Architectural Patterns and Best Practices on AWS | AWS re:I...
Amazon Web Services
 
(SDD414) Amazon Redshift Deep Dive and What's Next | AWS re:Invent 2014
(SDD414) Amazon Redshift Deep Dive and What's Next | AWS re:Invent 2014(SDD414) Amazon Redshift Deep Dive and What's Next | AWS re:Invent 2014
(SDD414) Amazon Redshift Deep Dive and What's Next | AWS re:Invent 2014
Amazon Web Services
 
(SDD415) NEW LAUNCH: Amazon Aurora: Amazon’s New Relational Database Engine |...
(SDD415) NEW LAUNCH: Amazon Aurora: Amazon’s New Relational Database Engine |...(SDD415) NEW LAUNCH: Amazon Aurora: Amazon’s New Relational Database Engine |...
(SDD415) NEW LAUNCH: Amazon Aurora: Amazon’s New Relational Database Engine |...
Amazon Web Services
 

Viewers also liked (11)

Choosing the Right Data Storage Solution
Choosing the Right Data Storage SolutionChoosing the Right Data Storage Solution
Choosing the Right Data Storage Solution
 
BDT305 Transforming Big Data with Spark and Shark - AWS re: Invent 2012
BDT305 Transforming Big Data with Spark and Shark - AWS re: Invent 2012BDT305 Transforming Big Data with Spark and Shark - AWS re: Invent 2012
BDT305 Transforming Big Data with Spark and Shark - AWS re: Invent 2012
 
Semantic 'Radar' Steers Users to Insights in the Data Lake
Semantic 'Radar' Steers Users to Insights in the Data LakeSemantic 'Radar' Steers Users to Insights in the Data Lake
Semantic 'Radar' Steers Users to Insights in the Data Lake
 
(HLS402) Getting into Your Genes: The Definitive Guide to Using Amazon EMR, A...
(HLS402) Getting into Your Genes: The Definitive Guide to Using Amazon EMR, A...(HLS402) Getting into Your Genes: The Definitive Guide to Using Amazon EMR, A...
(HLS402) Getting into Your Genes: The Definitive Guide to Using Amazon EMR, A...
 
(BDT401) Big Data Orchestra - Harmony within Data Analysis Tools | AWS re:Inv...
(BDT401) Big Data Orchestra - Harmony within Data Analysis Tools | AWS re:Inv...(BDT401) Big Data Orchestra - Harmony within Data Analysis Tools | AWS re:Inv...
(BDT401) Big Data Orchestra - Harmony within Data Analysis Tools | AWS re:Inv...
 
(BDT302) Big Data Beyond Hadoop: Running Mahout, Giraph, and R on Amazon EMR ...
(BDT302) Big Data Beyond Hadoop: Running Mahout, Giraph, and R on Amazon EMR ...(BDT302) Big Data Beyond Hadoop: Running Mahout, Giraph, and R on Amazon EMR ...
(BDT302) Big Data Beyond Hadoop: Running Mahout, Giraph, and R on Amazon EMR ...
 
Maximizing EC2 and Elastic Block Store Disk Performance
Maximizing EC2 and Elastic Block Store Disk PerformanceMaximizing EC2 and Elastic Block Store Disk Performance
Maximizing EC2 and Elastic Block Store Disk Performance
 
(BDT308) Using Amazon Elastic MapReduce as Your Scalable Data Warehouse | AWS...
(BDT308) Using Amazon Elastic MapReduce as Your Scalable Data Warehouse | AWS...(BDT308) Using Amazon Elastic MapReduce as Your Scalable Data Warehouse | AWS...
(BDT308) Using Amazon Elastic MapReduce as Your Scalable Data Warehouse | AWS...
 
(BDT310) Big Data Architectural Patterns and Best Practices on AWS | AWS re:I...
(BDT310) Big Data Architectural Patterns and Best Practices on AWS | AWS re:I...(BDT310) Big Data Architectural Patterns and Best Practices on AWS | AWS re:I...
(BDT310) Big Data Architectural Patterns and Best Practices on AWS | AWS re:I...
 
(SDD414) Amazon Redshift Deep Dive and What's Next | AWS re:Invent 2014
(SDD414) Amazon Redshift Deep Dive and What's Next | AWS re:Invent 2014(SDD414) Amazon Redshift Deep Dive and What's Next | AWS re:Invent 2014
(SDD414) Amazon Redshift Deep Dive and What's Next | AWS re:Invent 2014
 
(SDD415) NEW LAUNCH: Amazon Aurora: Amazon’s New Relational Database Engine |...
(SDD415) NEW LAUNCH: Amazon Aurora: Amazon’s New Relational Database Engine |...(SDD415) NEW LAUNCH: Amazon Aurora: Amazon’s New Relational Database Engine |...
(SDD415) NEW LAUNCH: Amazon Aurora: Amazon’s New Relational Database Engine |...
 

Similar to BAS big data_v1 0

KoprowskiT_session1_SDNEvent_WASDforBeginners
KoprowskiT_session1_SDNEvent_WASDforBeginnersKoprowskiT_session1_SDNEvent_WASDforBeginners
KoprowskiT_session1_SDNEvent_WASDforBeginners
Tobias Koprowski
 
Data Driven Advanced Analytics using Denodo Platform on AWS
Data Driven Advanced Analytics using Denodo Platform on AWSData Driven Advanced Analytics using Denodo Platform on AWS
Data Driven Advanced Analytics using Denodo Platform on AWS
Denodo
 
Big Data Expo 2015 - Microsoft Transform you data into intelligent action
Big Data Expo 2015 - Microsoft Transform you data into intelligent actionBig Data Expo 2015 - Microsoft Transform you data into intelligent action
Big Data Expo 2015 - Microsoft Transform you data into intelligent action
BigDataExpo
 
MongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoT
MongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoTMongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoT
MongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoT
MongoDB
 
SMAC - Social, Mobile, Analytics and Cloud - An overview
SMAC - Social, Mobile, Analytics and Cloud - An overview SMAC - Social, Mobile, Analytics and Cloud - An overview
SMAC - Social, Mobile, Analytics and Cloud - An overview
Rajesh Menon
 
Azure Overview Csco
Azure Overview CscoAzure Overview Csco
Azure Overview Csco
rajramab
 
Emerging IT Trends and Innovation Concepts.pptx
Emerging IT Trends and Innovation Concepts.pptxEmerging IT Trends and Innovation Concepts.pptx
Emerging IT Trends and Innovation Concepts.pptx
Roshni814224
 
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
 
Maximize cloud and application performance with hundreds of operations bridge...
Maximize cloud and application performance with hundreds of operations bridge...Maximize cloud and application performance with hundreds of operations bridge...
Maximize cloud and application performance with hundreds of operations bridge...
Stefan Bergstein
 
Azure IoT Suite
Azure IoT Suite Azure IoT Suite
Azure IoT Suite
Samir Arezki ☁
 
Modernizing Your Data Warehouse using APS
Modernizing Your Data Warehouse using APSModernizing Your Data Warehouse using APS
Modernizing Your Data Warehouse using APS
Stéphane Fréchette
 
Windows Azure Platform Overview
Windows Azure Platform OverviewWindows Azure Platform Overview
Windows Azure Platform Overview
BusinessIntelligenze
 
Black Marble Microsoft Event Azure 3 12 08
Black Marble Microsoft Event Azure 3 12 08Black Marble Microsoft Event Azure 3 12 08
Black Marble Microsoft Event Azure 3 12 08
simondavies
 
Windows Azure Platform
Windows Azure PlatformWindows Azure Platform
Windows Azure Platform
Wade Wegner
 
inmation Presentation
inmation Presentationinmation Presentation
inmation Presentation
inmation Software GmbH
 
Virgílio Vargas Presentations / CloudViews.Org - Cloud Computing Conference 2...
Virgílio Vargas Presentations / CloudViews.Org - Cloud Computing Conference 2...Virgílio Vargas Presentations / CloudViews.Org - Cloud Computing Conference 2...
Virgílio Vargas Presentations / CloudViews.Org - Cloud Computing Conference 2...
EuroCloud
 
Opportunity: Data, Analytic & Azure
Opportunity: Data, Analytic & Azure Opportunity: Data, Analytic & Azure
Opportunity: Data, Analytic & Azure
Abhimanyu Singhal
 
Next Gen Analytics Going Beyond Data Warehouse
Next Gen Analytics Going Beyond Data WarehouseNext Gen Analytics Going Beyond Data Warehouse
Next Gen Analytics Going Beyond Data Warehouse
Denodo
 
Atlanta Cloud Users Group
Atlanta Cloud Users GroupAtlanta Cloud Users Group
Atlanta Cloud Users Group
John Willis
 
Data Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptxData Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptx
ArunPandiyan890855
 

Similar to BAS big data_v1 0 (20)

KoprowskiT_session1_SDNEvent_WASDforBeginners
KoprowskiT_session1_SDNEvent_WASDforBeginnersKoprowskiT_session1_SDNEvent_WASDforBeginners
KoprowskiT_session1_SDNEvent_WASDforBeginners
 
Data Driven Advanced Analytics using Denodo Platform on AWS
Data Driven Advanced Analytics using Denodo Platform on AWSData Driven Advanced Analytics using Denodo Platform on AWS
Data Driven Advanced Analytics using Denodo Platform on AWS
 
Big Data Expo 2015 - Microsoft Transform you data into intelligent action
Big Data Expo 2015 - Microsoft Transform you data into intelligent actionBig Data Expo 2015 - Microsoft Transform you data into intelligent action
Big Data Expo 2015 - Microsoft Transform you data into intelligent action
 
MongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoT
MongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoTMongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoT
MongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoT
 
SMAC - Social, Mobile, Analytics and Cloud - An overview
SMAC - Social, Mobile, Analytics and Cloud - An overview SMAC - Social, Mobile, Analytics and Cloud - An overview
SMAC - Social, Mobile, Analytics and Cloud - An overview
 
Azure Overview Csco
Azure Overview CscoAzure Overview Csco
Azure Overview Csco
 
Emerging IT Trends and Innovation Concepts.pptx
Emerging IT Trends and Innovation Concepts.pptxEmerging IT Trends and Innovation Concepts.pptx
Emerging IT Trends and Innovation Concepts.pptx
 
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...
 
Maximize cloud and application performance with hundreds of operations bridge...
Maximize cloud and application performance with hundreds of operations bridge...Maximize cloud and application performance with hundreds of operations bridge...
Maximize cloud and application performance with hundreds of operations bridge...
 
Azure IoT Suite
Azure IoT Suite Azure IoT Suite
Azure IoT Suite
 
Modernizing Your Data Warehouse using APS
Modernizing Your Data Warehouse using APSModernizing Your Data Warehouse using APS
Modernizing Your Data Warehouse using APS
 
Windows Azure Platform Overview
Windows Azure Platform OverviewWindows Azure Platform Overview
Windows Azure Platform Overview
 
Black Marble Microsoft Event Azure 3 12 08
Black Marble Microsoft Event Azure 3 12 08Black Marble Microsoft Event Azure 3 12 08
Black Marble Microsoft Event Azure 3 12 08
 
Windows Azure Platform
Windows Azure PlatformWindows Azure Platform
Windows Azure Platform
 
inmation Presentation
inmation Presentationinmation Presentation
inmation Presentation
 
Virgílio Vargas Presentations / CloudViews.Org - Cloud Computing Conference 2...
Virgílio Vargas Presentations / CloudViews.Org - Cloud Computing Conference 2...Virgílio Vargas Presentations / CloudViews.Org - Cloud Computing Conference 2...
Virgílio Vargas Presentations / CloudViews.Org - Cloud Computing Conference 2...
 
Opportunity: Data, Analytic & Azure
Opportunity: Data, Analytic & Azure Opportunity: Data, Analytic & Azure
Opportunity: Data, Analytic & Azure
 
Next Gen Analytics Going Beyond Data Warehouse
Next Gen Analytics Going Beyond Data WarehouseNext Gen Analytics Going Beyond Data Warehouse
Next Gen Analytics Going Beyond Data Warehouse
 
Atlanta Cloud Users Group
Atlanta Cloud Users GroupAtlanta Cloud Users Group
Atlanta Cloud Users Group
 
Data Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptxData Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptx
 

Recently uploaded

HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
panagenda
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Pixlogix Infotech
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Neo4j
 
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Neo4j
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
DianaGray10
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
mikeeftimakis1
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Speck&Tech
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Matthew Sinclair
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Zilliz
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
danishmna97
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
名前 です男
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
Kumud Singh
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Neo4j
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems S.M.S.A.
 
Mariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceXMariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceX
Mariano Tinti
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Tomaz Bratanic
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
Octavian Nadolu
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
tolgahangng
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
Matthew Sinclair
 

Recently uploaded (20)

HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
 
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
 
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
 
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalizationFull-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
 
Mariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceXMariano G Tinti - Decoding SpaceX
Mariano G Tinti - Decoding SpaceX
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
 
Artificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopmentArtificial Intelligence for XMLDevelopment
Artificial Intelligence for XMLDevelopment
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
 

BAS big data_v1 0

  • 1. AstraZeneca – Amazon Analytics Cloud Services
  • 2. Amazon Analytics Cloud Services British-Swedish multinational pharmaceutical and biologics company Business Context / Challenges Integration challenges • Point to point interfaces • Local reporting and data gathering to fill the gaps • Intensive manual reconciliation • Local systems to resolve integration gaps, incurring local costs and support effort • Little re-use of data for multiple purposes Pain points • Duplicated licences and contracts • Tying up headcount in duplicated tasks • Fragmented reporting and reconciliation • Multiple integration points Solution HCL provides a comprehensive cloud based solution which comprises of the following in addition to requirements specified in RFI(detailed solution explanation provided in subsequent slides): • A robust, proven, secure, public cloud service from Amazon Web Services (AWS) with menu based pricing • A powerful data processing layer which can leverage elastic computing • Pre-defined set of data connectors and adapters that can be leveraged to easily pull data having different formats (structured, semi-structured and unstructured) from different sources • A wide variety of technology options to implement best of breed technologies for meeting AstraZeneca’s requirements • APIs that allow easy connection to different sets of analytics, visualization and reporting tools • A robust Data Quality Framework to ensure quality of data being processed for purpose of reporting. Availability of pre-defined operational dashboards • A Next generation platform to enable advanced analytics using BigData frameworks Potential Benefits Universal • Commonly understood view of sales & marketing information Integrated • Correlated with other data and governed by common master data On Demand • Available when required, accessible in the right format, timely Cost Effective • More for less cost and effort (IT and business) • Delivered through a smart technology layer and toolset built once, shared many times Copyright © 2014 HCL Technologies Limited 2 | www.hcltech.com
  • 3. HCL’s Understanding of Requirements Data Hosting Data Supply Data Processing Analysis, Visualizations & Reporting Others Data partitioning Structured & unstructured data Create custom reports Create custom reports UI/ UX customization Data backup & restore Delta updates Work on permitted data Access reports across devices Internationalization & localization Secure data access Batch updates Collaborate on permitted data Use existing tools Friendly user interface Secure data holding Secure upload Task based collaboration Secure work areas Security policies Scalable Scalable & flexible Use existing tools Performance SLAs Monitoring AZ, Partner & Web data Report management Publish reports on the web Secure work areas User management Traffic management Task/workflow management Upload management Copyright © 2014 HCL Technologies Limited 3 | www.hcltech.com 3 @ Data Supply Data Processing Analytics & Visualization AZ Enterprise Data Third Party Data & Web Data Analysts Local Market Data Dashboards & Reports Publish Dashboards & Reports End Users Data Hosting Dashboards & Reports
  • 4. Solution Architecture AZ AZ Global Enterprise Global Firewall Data Landing Zone EDW Additional Enterprise Data (Source 1) Additional Enterprise Data (Source 2) AZ Local/Regional Enterprise Local Firewall Data Landing Zone Regional Data AZ Local/Regional Enterprise Local Firewall Data Landing Zone Regional Data Data Supply Data Processing Data Hosting Monitoring AWS Monitoring Monitoring AWS Monitoring Monitoring AWS Monitoring DWH On Cloud AWS Redshift DB User based Access Control Global Data Region 1 Data Region 2 Data Data Processing Zone AWS Informatica/ Elastic Map Reduce Data Validation Processing Program/Job Landing Zone/ Staging Area AWS Redshift Global Bucket (EDW + Additional Enterprise Data Local/Region 1 Bucket Local/Region 2 Bucket Access Control Reporting, Analysis and Visualization Single Sign-on-AWS Identity and Access Management/ Any other IAM on AWS Analysis Tool SAS(on AWS Instance) Role Based Access Control Analytics Workbench Connector(S) Reporting, Visualization Tools Existing Tools, on premise or on AWS Role Based Access Control Reporting Module Visualization Module Connector(S) Copyright © 2014 HCL Technologies Limited 4 | www.hcltech.com AZ Source Data/Systems Amazon Web Services Consumer

Editor's Notes

  1. AstraZeneca