SlideShare a Scribd company logo
1 of 1
Download to read offline
iCharts : Cloud Migration
Business Situation
                                                                                     Client Profile
The company was founded in 2008, with their SAAS application on dedicated
infrastructure hosted with a hosting provider. It went on to be become a popular     The client is a cloud-
data visualization provider with bloggers, teachers, government analysts and         based company that
small business owners, along with Fortune 500 companies and other market             enables processing,
research partners who started harnessing the power tool. The business need was       visualization and
to grow further, in terms of storage, bandwidth and processing capacity called for   distribution of big and
ad hoc needs for scaling the infrastructure, which was limited by SLAs provided by   small data. Their vision is
the infrastructure vendor.                                                           to empower the world to
                                                                                     explore and share data by
Solution Approach                                                                    enabling the free flow of
                                                                                     visual data among data
Compassites proposed and implemented migration of the whole application              owners, media, business
stack to the public cloud to ensure elastic, auto scaling, fault tolerant and high   and consumers. Users
capacity infrastructure, using the following services provided by Amazon Web         can upload and connect
Services.                                                                            to Excel sheets, csv files,
                                                                                     dynamic data, Google
Technology Used                                                                      spread sheets, survey
                                                                                     data in the form of SPSS
Adobe Flex, Adobe Life Cycle Data Services, J2EE, RESTful web services, HTML5,       or iCharts proprietary
MySQL, Pentaho and Amazon Web Services                                               data, OLAP data sources,
                                                                                     process the data, and use
Benefits & Results                                                                    it to create attractive,
                                                                                     interactive charts and
 Elastic infrastructure provided by elastic load balancer and auto scaling.         dashboards using a web
 High availability and fault tolerance provided by installing the elastic load      application.
  balancer against two availability zones.
 Higher processing capacity through Amazon RDS.
 Reduction of infrastructure costs by half.




You can read more            Reach out to us at     Via email
about Compassites at         +91 - 80- 4203 2572    info@compassitesinc.com
www.compassitesinc.com       +91 - 80- 6500 2371

More Related Content

What's hot

Arcgis server-functionality-matrix
Arcgis server-functionality-matrixArcgis server-functionality-matrix
Arcgis server-functionality-matrixEsri
 
20130117 - Big Data Architectures
20130117 - Big Data Architectures20130117 - Big Data Architectures
20130117 - Big Data ArchitecturesBlueMetalInc
 
Semantic Data Exchange
Semantic Data ExchangeSemantic Data Exchange
Semantic Data ExchangeDave Reynolds
 
ArcGIS
ArcGISArcGIS
ArcGISEsri
 
Analysis of Make data more human - TED Talk by Jer Thopr
Analysis of Make data more human - TED Talk by Jer ThoprAnalysis of Make data more human - TED Talk by Jer Thopr
Analysis of Make data more human - TED Talk by Jer ThoprDheepika Chokkalingam
 
The future of GIS as we know it
The future of GIS as we know itThe future of GIS as we know it
The future of GIS as we know itJan Willem van Eck
 
SHASPA Data Visualisation Framework - Intelligent Shared Spaces for Sustainab...
SHASPA Data Visualisation Framework - Intelligent Shared Spaces for Sustainab...SHASPA Data Visualisation Framework - Intelligent Shared Spaces for Sustainab...
SHASPA Data Visualisation Framework - Intelligent Shared Spaces for Sustainab...David Wortley
 
How map based visualisation can enhance your use of Sharepoint
How map based visualisation can enhance your use of SharepointHow map based visualisation can enhance your use of Sharepoint
How map based visualisation can enhance your use of SharepointRoss Caldow
 
Open Data Open Innovation and The Cloud gayler berlin nov12
Open Data Open Innovation and The Cloud   gayler berlin nov12Open Data Open Innovation and The Cloud   gayler berlin nov12
Open Data Open Innovation and The Cloud gayler berlin nov12Mark Gayler
 

What's hot (14)

Arcgis server-functionality-matrix
Arcgis server-functionality-matrixArcgis server-functionality-matrix
Arcgis server-functionality-matrix
 
20130117 - Big Data Architectures
20130117 - Big Data Architectures20130117 - Big Data Architectures
20130117 - Big Data Architectures
 
Semantic Data Exchange
Semantic Data ExchangeSemantic Data Exchange
Semantic Data Exchange
 
Web mapping
Web mappingWeb mapping
Web mapping
 
1 artur riel_sesiunea_1
1 artur riel_sesiunea_11 artur riel_sesiunea_1
1 artur riel_sesiunea_1
 
Web mapping
Web mappingWeb mapping
Web mapping
 
ArcGIS
ArcGISArcGIS
ArcGIS
 
Analysis of Make data more human - TED Talk by Jer Thopr
Analysis of Make data more human - TED Talk by Jer ThoprAnalysis of Make data more human - TED Talk by Jer Thopr
Analysis of Make data more human - TED Talk by Jer Thopr
 
EENA 2021: Natural hazards – challenges, technologies and response (1/4)
EENA 2021: Natural hazards – challenges, technologies and response (1/4)EENA 2021: Natural hazards – challenges, technologies and response (1/4)
EENA 2021: Natural hazards – challenges, technologies and response (1/4)
 
The future of GIS as we know it
The future of GIS as we know itThe future of GIS as we know it
The future of GIS as we know it
 
Situational awareness
Situational awarenessSituational awareness
Situational awareness
 
SHASPA Data Visualisation Framework - Intelligent Shared Spaces for Sustainab...
SHASPA Data Visualisation Framework - Intelligent Shared Spaces for Sustainab...SHASPA Data Visualisation Framework - Intelligent Shared Spaces for Sustainab...
SHASPA Data Visualisation Framework - Intelligent Shared Spaces for Sustainab...
 
How map based visualisation can enhance your use of Sharepoint
How map based visualisation can enhance your use of SharepointHow map based visualisation can enhance your use of Sharepoint
How map based visualisation can enhance your use of Sharepoint
 
Open Data Open Innovation and The Cloud gayler berlin nov12
Open Data Open Innovation and The Cloud   gayler berlin nov12Open Data Open Innovation and The Cloud   gayler berlin nov12
Open Data Open Innovation and The Cloud gayler berlin nov12
 

Similar to iCharts

Operating a secure big data platform in a multi-cloud environment
Operating a secure big data platform in a multi-cloud environmentOperating a secure big data platform in a multi-cloud environment
Operating a secure big data platform in a multi-cloud environmentDataWorks Summit
 
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
 
Data Virtualization: Introduction and Business Value (UK)
Data Virtualization: Introduction and Business Value (UK)Data Virtualization: Introduction and Business Value (UK)
Data Virtualization: Introduction and Business Value (UK)Denodo
 
IBM Relay 2015: Open for Data
IBM Relay 2015: Open for Data IBM Relay 2015: Open for Data
IBM Relay 2015: Open for Data IBM
 
Massive Data Analytics and the Cloud
Massive Data Analytics and the CloudMassive Data Analytics and the Cloud
Massive Data Analytics and the CloudBooz Allen Hamilton
 
5 Steps for Architecting a Data Lake
5 Steps for Architecting a Data Lake5 Steps for Architecting a Data Lake
5 Steps for Architecting a Data LakeMetroStar
 
Analytics as a Service in SL
Analytics as a Service in SLAnalytics as a Service in SL
Analytics as a Service in SLSkylabReddy Vanga
 
Data Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptxData Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptxArunPandiyan890855
 
Big Data: Its Characteristics And Architecture Capabilities
Big Data: Its Characteristics And Architecture CapabilitiesBig Data: Its Characteristics And Architecture Capabilities
Big Data: Its Characteristics And Architecture CapabilitiesAshraf Uddin
 
Big Data Companies and Apache Software
Big Data Companies and Apache SoftwareBig Data Companies and Apache Software
Big Data Companies and Apache SoftwareBob Marcus
 
OpenSistemas Corporate Presentation
OpenSistemas Corporate PresentationOpenSistemas Corporate Presentation
OpenSistemas Corporate PresentationOpenSistemas
 
LinkedInSaxoBankDataWorkbench
LinkedInSaxoBankDataWorkbenchLinkedInSaxoBankDataWorkbench
LinkedInSaxoBankDataWorkbenchSheetal Pratik
 
Lecture 5 - Big Data and Hadoop Intro.ppt
Lecture 5 - Big Data and Hadoop Intro.pptLecture 5 - Big Data and Hadoop Intro.ppt
Lecture 5 - Big Data and Hadoop Intro.pptalmaraniabwmalk
 
Apache Hadoop India Summit 2011 talk "Informatica and Big Data" by Snajeev Kumar
Apache Hadoop India Summit 2011 talk "Informatica and Big Data" by Snajeev KumarApache Hadoop India Summit 2011 talk "Informatica and Big Data" by Snajeev Kumar
Apache Hadoop India Summit 2011 talk "Informatica and Big Data" by Snajeev KumarYahoo Developer Network
 
OpenNASA v2.0 Slideshare Large File
OpenNASA v2.0 Slideshare   Large FileOpenNASA v2.0 Slideshare   Large File
OpenNASA v2.0 Slideshare Large FileMegan Eskey
 
Combine Apache Hadoop and Elasticsearch to Get the Most of Your Big Data
Combine Apache Hadoop and Elasticsearch to Get the Most of Your Big DataCombine Apache Hadoop and Elasticsearch to Get the Most of Your Big Data
Combine Apache Hadoop and Elasticsearch to Get the Most of Your Big DataHortonworks
 
Hadoop India Summit, Feb 2011 - Informatica
Hadoop India Summit, Feb 2011 - InformaticaHadoop India Summit, Feb 2011 - Informatica
Hadoop India Summit, Feb 2011 - InformaticaSanjeev Kumar
 
WP_Impetus_2016_Guide_to_Modernize_Your_Enterprise_Data_Warehouse_JRoberts
WP_Impetus_2016_Guide_to_Modernize_Your_Enterprise_Data_Warehouse_JRobertsWP_Impetus_2016_Guide_to_Modernize_Your_Enterprise_Data_Warehouse_JRoberts
WP_Impetus_2016_Guide_to_Modernize_Your_Enterprise_Data_Warehouse_JRobertsJane Roberts
 
Data Ninja Webinar Series: Realizing the Promise of Data Lakes
Data Ninja Webinar Series: Realizing the Promise of Data LakesData Ninja Webinar Series: Realizing the Promise of Data Lakes
Data Ninja Webinar Series: Realizing the Promise of Data LakesDenodo
 

Similar to iCharts (20)

Operating a secure big data platform in a multi-cloud environment
Operating a secure big data platform in a multi-cloud environmentOperating a secure big data platform in a multi-cloud environment
Operating a secure big data platform in a multi-cloud environment
 
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
 
Data Virtualization: Introduction and Business Value (UK)
Data Virtualization: Introduction and Business Value (UK)Data Virtualization: Introduction and Business Value (UK)
Data Virtualization: Introduction and Business Value (UK)
 
IBM Relay 2015: Open for Data
IBM Relay 2015: Open for Data IBM Relay 2015: Open for Data
IBM Relay 2015: Open for Data
 
Massive Data Analytics and the Cloud
Massive Data Analytics and the CloudMassive Data Analytics and the Cloud
Massive Data Analytics and the Cloud
 
5 Steps for Architecting a Data Lake
5 Steps for Architecting a Data Lake5 Steps for Architecting a Data Lake
5 Steps for Architecting a Data Lake
 
Analytics as a Service in SL
Analytics as a Service in SLAnalytics as a Service in SL
Analytics as a Service in SL
 
Data Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptxData Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptx
 
Big Data: Its Characteristics And Architecture Capabilities
Big Data: Its Characteristics And Architecture CapabilitiesBig Data: Its Characteristics And Architecture Capabilities
Big Data: Its Characteristics And Architecture Capabilities
 
Big Data Companies and Apache Software
Big Data Companies and Apache SoftwareBig Data Companies and Apache Software
Big Data Companies and Apache Software
 
OpenSistemas Corporate Presentation
OpenSistemas Corporate PresentationOpenSistemas Corporate Presentation
OpenSistemas Corporate Presentation
 
LinkedInSaxoBankDataWorkbench
LinkedInSaxoBankDataWorkbenchLinkedInSaxoBankDataWorkbench
LinkedInSaxoBankDataWorkbench
 
IBM Cloud pak for data brochure
IBM Cloud pak for data   brochureIBM Cloud pak for data   brochure
IBM Cloud pak for data brochure
 
Lecture 5 - Big Data and Hadoop Intro.ppt
Lecture 5 - Big Data and Hadoop Intro.pptLecture 5 - Big Data and Hadoop Intro.ppt
Lecture 5 - Big Data and Hadoop Intro.ppt
 
Apache Hadoop India Summit 2011 talk "Informatica and Big Data" by Snajeev Kumar
Apache Hadoop India Summit 2011 talk "Informatica and Big Data" by Snajeev KumarApache Hadoop India Summit 2011 talk "Informatica and Big Data" by Snajeev Kumar
Apache Hadoop India Summit 2011 talk "Informatica and Big Data" by Snajeev Kumar
 
OpenNASA v2.0 Slideshare Large File
OpenNASA v2.0 Slideshare   Large FileOpenNASA v2.0 Slideshare   Large File
OpenNASA v2.0 Slideshare Large File
 
Combine Apache Hadoop and Elasticsearch to Get the Most of Your Big Data
Combine Apache Hadoop and Elasticsearch to Get the Most of Your Big DataCombine Apache Hadoop and Elasticsearch to Get the Most of Your Big Data
Combine Apache Hadoop and Elasticsearch to Get the Most of Your Big Data
 
Hadoop India Summit, Feb 2011 - Informatica
Hadoop India Summit, Feb 2011 - InformaticaHadoop India Summit, Feb 2011 - Informatica
Hadoop India Summit, Feb 2011 - Informatica
 
WP_Impetus_2016_Guide_to_Modernize_Your_Enterprise_Data_Warehouse_JRoberts
WP_Impetus_2016_Guide_to_Modernize_Your_Enterprise_Data_Warehouse_JRobertsWP_Impetus_2016_Guide_to_Modernize_Your_Enterprise_Data_Warehouse_JRoberts
WP_Impetus_2016_Guide_to_Modernize_Your_Enterprise_Data_Warehouse_JRoberts
 
Data Ninja Webinar Series: Realizing the Promise of Data Lakes
Data Ninja Webinar Series: Realizing the Promise of Data LakesData Ninja Webinar Series: Realizing the Promise of Data Lakes
Data Ninja Webinar Series: Realizing the Promise of Data Lakes
 

More from Compassites Software Solutions (16)

Acrowit
AcrowitAcrowit
Acrowit
 
Zyme
ZymeZyme
Zyme
 
Transformanz
TransformanzTransformanz
Transformanz
 
Seedling
SeedlingSeedling
Seedling
 
Payback
PaybackPayback
Payback
 
Jiffle
JiffleJiffle
Jiffle
 
WPA
WPAWPA
WPA
 
Nri touch
Nri touchNri touch
Nri touch
 
Immumetrix
ImmumetrixImmumetrix
Immumetrix
 
Hydratech
HydratechHydratech
Hydratech
 
Graymatics
GraymaticsGraymatics
Graymatics
 
Creatlive
CreatliveCreatlive
Creatlive
 
Beverages
BeveragesBeverages
Beverages
 
Authentix
AuthentixAuthentix
Authentix
 
9 Lenses
9 Lenses9 Lenses
9 Lenses
 
Compassites Is Hiring
Compassites Is HiringCompassites Is Hiring
Compassites Is Hiring
 

Recently uploaded

New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024BookNet Canada
 
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
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
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
 
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
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
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 pragmaticscarlostorres15106
 
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
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptxLBM Solutions
 
Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Neo4j
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
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
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDGMarianaLemus7
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 

Recently uploaded (20)

New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
 
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...
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
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...
 
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
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
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
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
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
 
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
 
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
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptx
 
Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
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
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDG
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 

iCharts

  • 1. iCharts : Cloud Migration Business Situation Client Profile The company was founded in 2008, with their SAAS application on dedicated infrastructure hosted with a hosting provider. It went on to be become a popular The client is a cloud- data visualization provider with bloggers, teachers, government analysts and based company that small business owners, along with Fortune 500 companies and other market enables processing, research partners who started harnessing the power tool. The business need was visualization and to grow further, in terms of storage, bandwidth and processing capacity called for distribution of big and ad hoc needs for scaling the infrastructure, which was limited by SLAs provided by small data. Their vision is the infrastructure vendor. to empower the world to explore and share data by Solution Approach enabling the free flow of visual data among data Compassites proposed and implemented migration of the whole application owners, media, business stack to the public cloud to ensure elastic, auto scaling, fault tolerant and high and consumers. Users capacity infrastructure, using the following services provided by Amazon Web can upload and connect Services. to Excel sheets, csv files, dynamic data, Google Technology Used spread sheets, survey data in the form of SPSS Adobe Flex, Adobe Life Cycle Data Services, J2EE, RESTful web services, HTML5, or iCharts proprietary MySQL, Pentaho and Amazon Web Services data, OLAP data sources, process the data, and use Benefits & Results it to create attractive, interactive charts and  Elastic infrastructure provided by elastic load balancer and auto scaling. dashboards using a web  High availability and fault tolerance provided by installing the elastic load application. balancer against two availability zones.  Higher processing capacity through Amazon RDS.  Reduction of infrastructure costs by half. You can read more Reach out to us at Via email about Compassites at +91 - 80- 4203 2572 info@compassitesinc.com www.compassitesinc.com +91 - 80- 6500 2371