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  • Aftership Case Study

    Based in Hong Kong, AfterShip provides automated shipment tracking as a service, supporting 300 shipping services worldwide and handling over 30 million packages every month. AfterShip is using Amazon EC2 Spot Instances and Amazon ElastiCache to run API services, serving over a billion API requests per month.

  • Artfinder Case Study

    Artfinder can match its customers with art they will love thanks to recommendation tools built on AWS. The company is an online art marketplace, allowing thousands of artists to sell directly to buyers. It runs its website and recommendation tools using AWS technologies such as Amazon EC2, Amazon Machine Learning, Amazon Rekognition, and Amazon Kinesis Firehose.

  • AWS Case Study: Cenique

    Cenique’s shopper-insight and digital-signage solutions provide retailers across the globe with an easy way to analyze in-store customer behavior and optimize marketing strategies accordingly. The company migrated its analytics platform to AWS after experiencing frequent downtime with on-premises servers. By moving to AWS, Cenique has reduced its operating costs by 60 percent and scaled to support a tenfold increase in customers.

  • AWS Case Study: Civis Analytics

    Civis Analytics creates technologies that empower companies and organizations to extract valuable insights from the data they generate, transforming them into smarter organizations. The company uses Amazon Redshift to run its analytics platform enabling its customers to run tens of thousands of jobs per month regardless of their complexity. Using AWS, Civis Analytics can scale up its IT infrastructure dynamically based on the number of customer using its platform.

  • AWS Case Study: CrowdChat

    CrowdChat takes conversations on the Internet and social media networks and then unifies them for users according to topic hashtags. The company turned to AWS to run its web application as well as its big data workloads. By using AWS, CrowdChat created an infrastructure that can store more than 250 million documents and easily handle demand so users can quickly find topics of interest.

  • AWS Case Study: DataXu

    DataXu is a cloud-based provider of programmatic software that helps advertisers save money and increase sales through greater effectiveness and efficiency in their marketing efforts. The company faced issues with scale and costs associated with on-premises IT environments and turned to AWS to run its big data platform. By using AWS, DataXu evaluates more than 30 trillion ad opportunities per month while saving up to 72 percent monthly on operational costs.

  • AWS Case Study: Ivy Tech Community College of Indiana

    Ivy Tech Community College of Indiana is the largest community college in the United States. The college uses Amazon Redshift and Amazon Simple Storage Service to run analytics tools to glean insights from more than 1.7 million student records, and then archives data in Amazon Glacier. With the AWS solution, Ivy Tech can meet its petabyte-scale data needs while avoiding unnecessary IT expenses.

  • AWS Case Study: Logentries

    Logentries is a software-as-a-service provider of real-time log management and analytics services to a range of clients worldwide, from Fortune 100 companies to individual developers. Logentries worked with AWS from day one, using AWS services to get its log management solution to market fast. The easy setup and quick scalability of AWS have enabled Logentries to scale from zero users in 2011 to more than 35,000 users across 100 countries today.

  • AWS Case Study: NASA

    NASA’s vision is “We reach for new heights and reveal the unknown for the benefit of humankind.” To better share its achievements with the public, NASA turned to InfoZen, an Advanced Consulting Partner of the AWS Partner Network (APN). NASA’s new Image and Video Library, built on Amazon Web Services, provides easy access to more than 140,000 still images, video, and audio—all in one place, from virtually any device. By building its new solution in the cloud, NASA is ensuring its ability to scale on-demand, while paying for only the capacity it needs, making the best use of taxpayer dollars.

  • AWS Case Study: Pixels

    Pixels is a digital-advertising services company that delivers targeted ads to consumers on the web and mobile. The firm runs its ad server and analytics platforms in the AWS cloud. This has enabled Pixels to cut its time to market, excluding hardware procurement, from three months to one month.

  • AWS Case Study: QNAP Systems

    QNAP Systems, Inc. provides powerful and reliable network-attached storage (NAS) and network video recorder (NVR) solutions worldwide. The company’s analytics platform, running on AWS, helps QNAP improve its products and customer service by extracting insights from customer data and event logs. By using AWS, the company has reduced the time it takes to run complex queries and generate reports from days to minutes.

  • AWS Case Study: University of Maryland University College

    University of Maryland University College (UMUC) is an open-access university serving working adult students pursuing higher education through on-site and online courses. When its legacy applications were due for renewal, UMUC turned to AWS to build its new analytics platform and several administrative workloads. By using Amazon Redshift, UMUC has improved its extract, transform, and load (ETL) performance by twentyfold allowing it to build more accurate predictive models.

  • AWS Case Study: Yelp Cuts Test-Run Times by 90% Using AWS

    Yelp.com and the Yelp mobile app publishes crowd-sourced reviews and photos about local businesses across the United States and in Europe, Asia, South America, Australia, and New Zealand. Using AWS services, Yelp streamlined its testing and development environment to maximize the productivity of its hybrid infrastructure, cutting its test-run time to 10 minutes, compared to as much as two hours previously.

  • Boingo Wireless Case Study

    Boingo Wireless uses AWS to run analytical queries in 25 seconds instead of 45 minutes, load one million data records in 20 seconds instead of two hours, and scale compute resources 20 times faster. Boingo Wireless provides mobile Internet access at more than one million Wi-Fi hotspots across the globe. The company runs its big-data warehouse and dev/test environments on AWS, and uses Amazon Redshift to ingest multiple terabytes of analytical data from different sources. 

  • C-SPAN Case Study

    By using AWS to automate the process of identifying when individuals appear in video streams, C-SPAN estimates it will be able to index 100 percent of its first-run content each year, covering 7,500 hours of content compared to the previous 3,500 hours. C-SPAN is a public service created by the United States cable television industry to make government proceedings available for public viewing. The organization is using Amazon Rekognition—an image analysis service based on deep-learning technology—to detect faces in screenshots captured from eight available C-SPAN video feeds that run 24/7.

  • Cadreon Case Study

    Cadreon processes big-data queries from thousands of sources in a few seconds and quickly scales to meet growing demand using AWS. The company provides programmatic advertising solutions to branding companies across the globe. Cadreon runs an audience-insights analytical platform on AWS.

  • Chumbak India Case Study

    By using AWS, Chumbak focuses 100 percent of its IT resources on development, releasing new code for its web store every day. Chumbak sells its own designs for apparel, home décor, and consumer-life style goods via its web store and multiple stores across India. It ensures web store visitors can find and buy the products they want easily regardless of traffic numbers thanks to a back-end infrastructure running on Amazon EC2 instances with Auto Scaling, an Amazon S3 data repository, and Amazon Kinesis to capture and process web-store clickstreams in real time. 

  • CrowdStrike Case Study

    CrowdStrike uses AWS to implement a scalable, cloud-based solution for preventing cyber breaches with on-demand resources, thereby simplifying maintenance, reducing cost, and improving performance. The company provides security software solutions that help companies protect their data by finding and stopping breaches. CrowdStrike analyzes threat data by spinning up big data analysis resources on demand using the AWS platform. The organization hosts machine learning and behavioral analytics workloads on Amazon EMR and runs a custom graph database called CrowdStrike Threat Graph™ using Amazon EBS. 

  • Daniel Wellington Case Study

    Daniel Wellington re-architects its Amazon Web Services (AWS) environment with microservices for improved scalability and lower cost. The Swedish company designs and sells watches and accessories based on classic, minimalist designs. It uses services including AWS Lambda, Amazon Kinesis, and Amazon Cognito.

  • DataVisor Case Study

    DataVisor has created a global service that uses big-data analytics to provide security services to online businesses by running on AWS. The startup company provides predictive threat-management services designed to build and restore trust in online communities. DataVisor is using AWS services like Amazon EC2, Amazon VPC, Amazon IAM, and Amazon CloudWatch to quickly launch and scale its offerings to customers around the world.  

  • Driver and Vehicle Licensing Agency Case Study

    The UK Driver and Vehicle Licensing Agency (DVLA) is using an API-based approach to empower people and organizations to create innovative applications and services with valuable public data. DVLA maintains the registration and licensing of more than 47 million driver records in Great Britain, as well as the collection and enforcement of Vehicle Excise Duty in the United Kingdom. The organization uses Amazon API Gateway to host and manage data APIs with the ability to scale to billions of transactions per month, and AWS Lambda for efficient, cost-effective operational tasks such as report generation.

  • Emagine International Case Study

    Emagine International’s RED.cloud can deliver messages to millions of telecommunications customers in less than 250 milliseconds in response to events through the scalability of the AWS Cloud. Emagine International builds software solutions for telecommunications businesses to increase customer revenue and loyalty. RED.cloud uses Amazon VPC to meet stringent customer security requirements, and Amazon EC2 to run analytics databases.  

  • FICO Case Study

    Using AWS, FICO delivers high-volume analytics software and tools to enterprises around the globe, including 95 percent of the largest financial institutions in the US. FICO is a data analytics company best known for producing the most widely used consumer credit scores that financial insititutions use in deciding whether to lend money or issue credit. FICO has migrated several core applications, including myFICO.com and its flagship analytics platform, the Decision Management Suite (DMS), to AWS, and will migrate additional applications over the next three years. 

  • Flatiron Health

    Flatiron Health delivers software faster, organizes and improves the quality of oncology data, and ensures regulatory compliance by running its applications on AWS. The company provides software to clinicians to manage their practice, workflow, and patient health information. Flatiron runs its critical data-management and research applications on AWS. 

  • Fugro Roames Case Study

    By running its virtual world and asset management software on AWS and by using Amazon EC2 Spot Instances, Fugro Roames has enabled innovative new asset and vegetation management strategies for Ergon Energy’s power network, reducing annual operational costs from AU$100 million (US$70 million) to AU$60 million (US$43 million). Founded as a business unit within Ergon Energy, Fugro Roames helps its clients to remotely investigate the condition and performance of overhead power-line networks. 

  • Fusionex Case Study

    Fusionex uses AWS to shift from on-premises solutions to the cloud, allowing it to deliver products to customers in weeks verses months, all while saving time spent on maintaining hardware and infrastructure. Fusionex is a global, multinational IT consultancy and solutions provider, specializing in big data analytics and business insights. Fusionex employs Auto Scaling technology, Amazon RDS, and Amazon S3 to improve their operations and shift human resource focus towards innovation.

  • GENALICE Case Study

    During a live webinar, biomedical startup GENALICE processed genomes from 800 Alzheimer’s disease patients in just 60 minutes, which would have taken its competitor more than two weeks to complete. GENALICE develops breakthrough software for analyzing big data relating to complex DNA diseases. It uses Amazon Web Services to run the Population Calling module of its GENALICE MAP Next-Generation Sequencing data analysis suite.  

  • Goodwill Industries Case Study

    Goodwill Industries has increased uptime for its stores, schools, and offices, can back up servers hourly, and can restore servers within moments of failure using AWS. Headquartered in Maple Shade, New Jersey, Goodwill Industries of Southern New Jersey and Philadelphia is a not-for-profit organization with a mission to put people to work and help them realize their economic potential. Goodwill uses Cloud Protection Manager by N2W Software—a seller in the AWS Marketplace—for backup and disaster recovery to protect all of its data, systems, and assets.

  • GoPro Case Study

    By using AWS, GoPro quickly built and launched its GoPro Plus service to enable its customers to upload content directly to the cloud. GoPro is an action-camera manufacturer that allows customers to share experiences with others using its products, mobile apps and software. The company relies on the AWS Support team for quick assistance with its upcoming product launches.

  • Grab Case Study

    By using Amazon Redshift, Grab is able to use real time data computation and data streams to support 1.5 million bookings in Southeast Asia. Grab, a ride hailing transportation platform is available across six countries in Singapore, Malaysia, Indonesia, Thailand, Vietnam and Philippines. Grab is using Amazon ElastiCache and Amazon Redshift.

  • Hearst Data Analytics Case Study

    With its data analytics pipeline, the Hearst Corporation processes clickstream data from more than 300 websites and delivers it to website editors within minutes. Hearst is one of the largest diversified media and information organizations in the world, with more than 360 businesses. The company uses Amazon Kinesis Streams and Amazon Kinesis Firehose to transmit and process more than 30 terabytes of clickstream data daily.

  • iCHEF Case Study

    iCHEF has reduced its IT management overhead by 13 percent using AWS, while also bringing down its overall IT costs to just 7 percent of the monthly fee it charges customers to use its point-of-sale (POS) service. iCHEF provides a POS service for restaurants across Southeast Asia, where employees use the app’s interface through Apple iPads. The company runs the backend infrastructure supporting the POS on the AWS Cloud, using Amazon EC2 instances for compute, Amazon RDS for transactional database services, and AWS Lambda to run daily data integrations for customers with multiple establishments.

  • InhibOx Case Study

    Pharmaceutical company, InhibOx, requires virtually unlimited compute capacity for drug discovery research. AWS provides the capacity that InhibOx needs while reducing computing costs by hundreds of thousands of dollars.

  • Instapage Case Study

    Using AWS, Instapage increased customer in-app activity by 10 percent, enabled marketing and customer success with powerful on-demand reporting, and identified a billing error that will save the company tens of thousands of dollars. The company offers a software-as-a-service solution to build and optimize landing pages for advertising campaigns. Instapage’s data team implemented Amazon Redshift—alongside various analytics tools—to aggregate, warehouse, and synthesize data on a 2 TB cluster.  

  • Jampp Case Study

    Jampp now processes 250 times the amount of customer data while saving two-thirds on processing costs using AWS. The company uses big data and machine learning algorithms to help its clients—from Twitter to Uber—drive users to their mobile apps. It does this using AWS technologies including Amazon Kinesis, AWS Lambda, and Amazon DynamoDB.

     

  • Kansas City with Xaqt Case Study

    The City of Kansas City connected its smart city infrastructure with Xaqt on AWS, enabling it to create powerful predictive models that improve quality of life and reduce costs. One of the most connected smart cities in the United States, Kansas City takes advantage of a public-private partnership to build out a sophisticated network of sensors and access points for big-data insights. Through Xaqt, the city uses Amazon Kinesis to ingest data, Amazon Redshift as a unified data lake, and AWS Lambda for cost-effective, serverless data transformations.

  • KKBOX Case Study

    By running its big-data analytics and video streaming platforms in AWS, KKBOX has cut the time to create reports from weeks to minutes whlie reducing video infrastructure costs by up to 50 percent. Launched in 1999, KKBOX is a Taiwan-based content streaming and analysis provider with over 400 employees. 

  • Mapbox Case Study

    Mapbox can collect 100 million miles of telemetry data every day using AWS. Mapbox provides an open-source mapping platform for custom designed maps that serve more than 250 million end users across 11 countries. Mapbox is all in on AWS and running across 10 regions. Mapbox uses Amazon Simple Storage Service (Amazon S3) to store petabytes of map and imagry data, and Amazon CloudFront along with Route 53 for fast content delivery.

  • Monsanto Case Study

    By running its geospatial data platform on AWS, Monsanto quickly scales to meet growth, provisions compute and storage in seconds, and sets up development and test environments in minutes instead of months. Monsanto provides agricultural products that support farmers and other customers throughout the world. The company uses Amazon Elastic File System to support its geospatial data and analytics solution.

  • Movable Ink Case Study

    Movable Ink uses AWS to query seven years’ worth of historical data and get results in moments, with the flexibility to explore data for deeper insights. Movable Ink provides real-time personalization of marketing emails based on a wide range of user, device, and contextual data, driving higher response rates and better customer experiences. The company uses the Amazon Athena serverless query service to analyze data stored in Amazon S3, gaining insights to improve results for customers’ marketing campaigns.

  • National Bank of Canada Case Study

    National Bank of Canada’s Global Equity Derivatives Group (GED) uses AWS to process and analyze hundreds of terabytes of financial data, conduct data manipulations in one minute instead of days, and scale and optimize its operations. GED provides stock-trading solutions and services to a range of organizations throughout the world. The organization runs its data analysis using the TickVault platform on the AWS Cloud. 

  • Netflix & Amazon Kinesis Streams Case Study

    Netflix uses AWS to analyze billions of messages across more than 100,000 application instances daily in real time, enabling it to optimize user experience, reduce costs, and improve application resilience. Netflix is the world’s leading internet television network, with more than 100 million members. Using Amazon Kinesis Streams, Netflix processes network flow logs rapidly and enriches them with application metadata in a highly dynamic, large-scale networking environment.  

  • NTT DOCOMO Case Study

    NTT DOCOMO can deliver analytical queries to its data scientists 10 times faster, add new data sources and analytics capabilities in weeks instead of months, meet security requirements, work with multiple petabytes of data, and scale to support fast growth by using AWS. The company is Japan’s largest mobile service provider, serving more than 68 million customers through advanced wireless networks, including one of the world’s most progressive LTE-Advanced networks. NTT DOCOMO hosts its web service systems and corporate applications on AWS, and uses Amazon Redshift to support a data analysis platform. 

  • ProtectWise Case Study

    ProtectWise uses AWS as the basis for an innovative security-analytics solution, enabling customers to store petabytes of networking data and analyze it in seconds. ProtectWise delivers automated threat detection, pervasive visibility, and unlimited forensic exploration, all from the cloud and on demand. The company uses Amazon EBS to buffer incoming data before storing it in Amazon S3, and uses Amazon EC2 to power data processing and analytics.

  • Sanlih E-Television Case Study

    Sanlih E-Television is saving 30 percent now that its platform to support a multichannel online strategy is running on AWS. Founded in 1983, Sanlih E-Television is a nationwide cable TV network delivering some of the most popular TV channels in Taiwan. To help maintain its leading position, the company developed an online strategy using AWS services such as Amazon EC2 to run its website and Amazon Kinesis as an engine for real-time application monitoring and clickstream analytics.

  • Scotia Gas Network Case Study

    By migrating to AWS, SGN has become more secure and agile while reducing costs. SGN is a United Kingdom gas-distribution company that manages the distribution network for natural and green gas to almost six million homes and businesses across Scotland and the south of England. The company runs multiple workloads on AWS, including key analytics platforms and mobile applications.

     

  • Senao International Case Study

    Migrating its POS and CRM systems to the AWS Cloud has enabled Senao International to automate 63 percent of systems maintenance, better manage security protocols, and eliminate downtime. Senao International is the leading provider of wireless phones, accessories, and mobile calling plans in Taiwan. The company uses Amazon EC2 to power its new e-commerce site and CRM platform, Amazon RDS to manage databases, and AWS Lambda to automate control of its AWS WAF firewall. 

  • Shaadi.com Case Study

    Shaadi.com migrated from a private hosted cloud to AWS so it could focus on its core business, reduce costs, and gain the agility to develop better user experiences faster. Shaadi.com is one of the world’s largest online matchmaking services, helping people around the world meet their life partners through a curated database of verified profiles.The company uses Amazon EC2 and Amazon S3 as a foundation for its services, relies on Amazon ElastiCache for in-memory storage, and adopted Amazon Rekognition for automated profile-picture management. 

  • SimScale Case Study

    With AWS, five students were able to set up a simulation business—called SimScale—that has attracted 100,000 users in just four years. SimScale makes computational fluid dynamics, finite element analysis, and thermal simulation available to anyone via a web browser, so companies can make better-informed design decisions. SimScale runs its application using AWS services including Amazon EC2 and Amazon S3.

     

  • Smithsonian Institution Case Study

    Using AWS, the Smithsonian Institution Data Science Team can scale instances up and down as needed, allowing the team to annotate genomes in parallel while also managing costs. The Smithsonian Data Science Team's mission is to implement solutions that will accelerate science and lower the bar for entry to genomics research, not only for Smithsonian scientists but for biodiversity researchers in general. The team is working to improve a critical part of the genome-analysis pipeline—annotation. The AWS Cloud has enabled the Smithsonian Institution to share their research and increase knowledge through open data science.

  • Snowplow Case Study

    Snowplow Analytics, an open-source analytics platform, enables enterprises to track customer behavior and analyze data from any source with any tool. Needing real-time analysis of highly granular data, Snowplow Analytics built its platform on AWS, enabling real-time processing of hundreds of millions of events each day.

  • Sony DADC New Media Solutions Case Study - Microsoft SQL Server

    Sony DADC New Media Solutions (NMS) uses AWS and worked with AWS Consulting Partner Datavail to ensure high availability for critical Microsoft SQL Server–based applications, spin capacity up or down on demand, and reduce the time it takes to run a key database process by more than 40 percent. The California-based organization provides digital supply chain solutions to film studios, broadcasters, and other providers of media content globally. NMS runs several SQL Server database applications on Amazon EC2 instances. 

  • Sparta Systems Case Study

    Sparta Systems uses the AWS Cloud to host quality-management systems for the life sciences industry that maintain data integrity, foster collaboration across a company’s quality ecosystem, and enable customers to deliver safer products to consumers. Sparta Systems hosts a solution on which pharmaceutical and medical-device companies can operate validated workloads that can be secured, analyzed, and verified by regulatory agencies. Using a variety of AWS services, it helps these customers minimize the costs and work interruptions that come with regulatory investigations and manage quality for processes across their entire production life cycle.

  • The Met Office Case Study

    By adopting AWS, the Met Office has increased its ability to deliver tailored meteorological information to users—it can deploy 30 times more frequently—while maintaining the integrity of its on-premises supercomputer environment. A world leader in weather and climate services, the Met Office provides accurate, accessible forecasts, severe weather warnings, and weather services to a variety of users across the globe. The organization has taken advantage of the AWS platform to reduce costs, assess architectural options rapidly, and scale data storage by tenfold. 

  • Toyota Tsusho Case Study

    Toyota Tsusho uses AWS to quickly scale their data processing of traffic data from over 50 thousand vehicles, while reducing costs up to 35 percent. Toyota Tsusho Electronics (Thailand) is a subsidiary of Toyota Group Japan and manufacturer of vehicle embedded software applications. Toyota Tsusho launched TSquare, a traffic information broadcasting system, which provides users real-time traffic data in Bangkok and 6 suburb provinces. Toyota Tsusho uses AWS products such as Amazon EC2, Amazon Kinesis, and DynamoDB to process large amounts of data in a scalable and reliable way. 

  • TrueCar Case Study

    TrueCar, working with AWS Advanced Consulting Partner CorpInfo, has gone all in on AWS, migrating workloads and thousands of virtual machines from physical data centers to the AWS Cloud and streamlining development and test tasks to serve its customers faster and more cost-effectively. TrueCar provides a digital automotive marketplace that offers comprehensive pricing transparency about what other people paid for their cars while enabling consumers to engage with TrueCar Certified Dealers who are committed to providing a superior purchase experience.  

  • TrueCar Case Study

    TrueCar, working with AWS Advanced Consulting Partner CorpInfo, has gone all in on AWS, migrating workloads and thousands of virtual machines from physical data centers to the AWS Cloud and streamlining development and test tasks to serve its customers faster and more cost-effectively. TrueCar provides a digital automotive marketplace that offers comprehensive pricing transparency about what other people paid for their cars while enabling consumers to engage with TrueCar Certified Dealers who are committed to providing a superior purchase experience.  

  • UK Data Service Case Study

    The UK Data Service is using Amazon Web Services to provide highly secure access to data via scalable APIs, providing new ways for researchers, citizens, policymakers, and businesses to get value from the United Kingdom’s data resources. The UK Data Service provides unified access to the United Kingdom’s largest collection of social, economic, and population data. The Service will ingest data using a customized open-source infrastructure running on Amazon EC2, hosting the cloud portion of its data lake on Amazon S3.  

  • Upserve Case Study

    Upserve quickly develops and trains more than 100 learning models, streams restaurant sales and menu item data in real time, and gives restaurateurs the ability to predict their nightly business using Amazon Machine Learning. The company provides online payment and analytical software to thousands of restaurant owners throughout the U.S. Upserve uses Amazon Machine Learning to provide predictive analysis through its Shift Prep application.

  • Vidcoin Case Study

    VIDCOIN is a startup competing in the fast-growing ad tech business in France. The company wanted a solution that could offer faster ingestion of user data and better insights into end user activities. It turned to AWS Partner Network (APN) Advanced Consulting Partner Corexpert, which created a solution using Amazon Elasticsearch Service, Amazon Kinesis, and AWS Lambda along with a Kibana-based dashboard to capture and analyze millions of events daily.  

  • Vocus Communications Case Study

    Vocus Communications developed a data-analytics platform 75 percent faster by using AWS and engaging APN Partner Bryte Systems. Vocus is a telecommunications company in Australia delivering a range of services, including broadband internet. The company has built an analytics platform that features Amazon S3, Amazon EMR, and Amazon Redshift to deliver real-time business insights—designed to improve customer experience, reduce churn, and leverage new business opportunities.

  • Vpon Case Study

    Vpon is on target to cut infrastructure costs by 50 percent by moving its mobile advertising analytics platform to AWS. Founded in 2008, Vpon provides mobile advertising services, including analytics, for businesses such as McDonald’s, Coca-Cola, American Express, and Citibank. The company is using Amazon Redshift to provide highly accurate client reports in real time.  

  • WeatherRisk Case Study

    WeatherRisk in Taiwan reduces the cost of developing high-precision weather forecasts by 50 percent using AWS. The company provides government agencies and enterprises with weather forecasts and risk mitigation reports. By using AWS, the company can deliver its services, and develop new services to meet clients’ specific requirements, significantly faster. As a result of the added compute performance from Amazon EC2 and AWS Lambda, weather data is downloaded in seconds instead of minutes from satellite sources, and meteorological data can be stored cost-efficiently in Amazon Glacier.
     

  • Yelp Data Analytics Case Study

    By using Amazon Redshift and Amazon EMR, Yelp has cut data query performance from hours to mere seconds, providing for richer and more interactive data analysis that helps the company improve its offerings. Yelp is a website and mobile app that connects people with great local businesses.The company moved its big-data analytics platform to Amazon Redshift and Amazon EMR.  

  • Zendesk Case Study

    Zendesk uses the AWS Cloud to cut costs by more than 60 percent, increase data retention by 200 percent, and easily scale its internal data-logging solution. The San Francisco, California, organization provides a cloud-based customer support platform to organizations across the globe. Zendesk runs its primary platform and an internal data- logging solution on AWS, taking advantage of multiple Amazon EBS volume types for better performance and lower costs.

  • zipMoney Case Study

    By using AWS to build a data lake, zipMoney can gather unique customer insights that vastly improve its underwriting process, pushing the boundaries of analytics with artificial intelligence and machine learning. zipMoney is an Australian fintech startup offering instantaneous, virtual lines of credit to consumers upon checkout at stores or on e-commerce sites. The firm relies on Amazon EMR and Amazon Elasticsearch Service to process and query vast amounts of data, Amazon S3 buckets to store such data, and Amazon DynamoDB to support its applications with low latency.