Case Studies

About the client
The client is a leading cyber security and antivirus solutions provider for consumers and corporates.

Technology problem
The client was facing the following issues:

  • The client required to develop a single, open-source–based Business Intelligence (BI) solution instead of maintaining multiple reporting systems based on various technologies.
  • The existing data warehouse did not have dimensional modeling, which resulted in the lack of integration with new reporting tools.
  • Limited drill-down capability in the existing Excel-based reporting forced businesses to maintain various reports with the same data set.
  • Data visualization capability was not available.
  • The manual data collection and report generation process (Excel-based) in the legacy system was time-consuming and error-prone.
  • An inefficient reporting system resulted in the unavailability of useful information, which limited company data analysis and decision-making capability.

Technology solution
Cybage provided the following solution to help the client overcome its problems:

  • Cybage’s BI solution had a 2-tier architecture, which consisted of the Cube layer and the Presentation layer.
  • We designed and developed a data warehouse on the Oracle 11g server using Informatica as the Extract Transform Load (ETL) tool.
  • Cube layer: We capitalized on the intelligent compression techniques of QlikView to reduce the amount of data with daily incremental data refreshing cycle.
  • Presentation layer: We capitalized on the associativity technology of QlikView to establish the relationship among various tables and form a star schema, which, in turn, pulls data from QVD files to generate the reports.

Execution strategy
Cybage adhered to the following plan to provide effective results to the client:

  • We capitalized on the Scrum methodology for high visibility, active collaboration, effective communication, and predictable rhythm, resulting in a predictable schedule and improved productivity.
  • We used Planning Poker for agile estimation and effective planning.
  • We created a Proof of Concept (PoC), which verified the proposed architecture.
  • We capitalized on the Cenzic security framework to identify potential security vulnerabilities and take appropriate measures.

Value realized
The dashboards and analytical reports developed in QlikView:

  • Helped business users to uncover hidden trends and make discoveries that drive innovative decisions.
  • Enhanced productivity of business users by providing access to dashboards having rich reports with drill-up and drill-down facility.

Tools and technologies
Cybage used the following tools and technologies:
Development Oracle , QlikView , Informatica 
Testing  Cenzic (for UI Security)
Tools  Gliffy, Planning Poker
ALM Cisco Jabbar, integrated Atlassian tools—Confluence, JIRA

Cybage services utilized
Architectural Services, Development, Testing, and BI Capabilties.

About the client
The client is one of the world’s leading providers of market and consumer research, which enables its customers to make smarter business decisions.

Technology problem
The client was facing the following issues:

  • The client’s existing legacy platform based on the COTS analytics software was incurring high data processing costs. It also required manual intervention in multiple instances.
  • The client was incurring high customization costs for integration of new data sources.
  • The existing solution was unable to handle data synchronization (multiple source streams) and data maintainability was a problem.

Technology solution
Cybage’s solution comprised the following:

  • Business Intelligence (BI) solution on Big Data platform, capitalizing on Hadoop technologies, deployed using Atlassian Bamboo to support multiple data partitions with multiple periods using nested ETL scheduled workflows
  • Pluggable solution that enabled easy integration with new data sources.
  • Custom-made automation framework based on Oozie JMS notification system aided quality control.
  • Solution transforms the legacy data set into a common big data file system, create an inventory of all data sets, apply data science modules for imputation, fusion and weighting, and manages dependencies between processing steps and automate job execution.
  • Maintenance and utilization of versioned data to ensure data accuracy; for instance, storage and retrieval of data in versions.
  • Creation of cohesive components that could be rapidly plugged into the system for workflows to execute seamlessly.
  • Provision of rich reports on aggregated data with additional product filters.

Execution strategy
Cybage adhered to the following plan to provide effective results to the client:

  • Adhered to SCRUM and Kanban methodologies to accelerate new adoptions, help overcome common pitfalls and challenges, and to evolve a new framework that could sustain value-delivery and agility over time.
  • Utilized development tools such as SonarQube for static code analysis and code coverage to keep technical debt under control and manage code quality.

Value realized
The solution provided the following benefits to the client:

  • Using this platform, the client was able to offer comprehensive insights harmonized with local market intelligence, enabling its customers to make informed decisions.
  • The platform offered low data processing cost with high scalability and greater flexibility to adopt new data sources.

Tools and technologies
Cybage used the following tools and technologies:
Development Java, MapReduce, Pig, Hive, Oozie, Kite Dataset Management, HCatalog, Impala, Graphite, EXASOL
Testing  JUnit, PigUnit, hcatunit, kite-unit, QA automation tool
CI  Atlassian Bamboo
Tools  Git, Vagrant, SourceTree, Cloudera Manager
ALM Integrated Atlassian tools—Confluence, JIRA, Stash, Lync, SonarQube

Cybage services utilized
Development, Testing, Test Automation, Cloud and BigData, BI, ALM, DevOps Capabilities

About the client
The client is a leading fashion and style website in the United States.

Technology problem
The client was facing the following technology issues:

  • The legacy platform was facing performance challenges because report generation took up one whole day.
  • High manual processing was required to consolidate data from multiple sources and generate reports. This resulted in loss of productivity.
  • Multiple groups worked on the same data, resulting in duplication of efforts.
  • The lack of a central reporting system (decentralized data), data inconsistency, and quality issues for WebPrints of one billion page views resulted in rework for reconciliation.

Technology solution
Cybage’s solution comprised the following:

  • Business Intelligence (BI) solution on Big Data platform, capitalizing on Hadoop technologies and open-source tools, using configurable ETL scheduled workflows.
  • Data assimilation platform, which consolidated data from sources such as Google Analytics, Sailthru, Ooyala, Chartbeat, Disqus, and Pinterest.
  • Extractor for individual sources that were run on AWS-EC2, raw JSON files were stored on AWS-S3, ETL and analytics were done on AWS-EMR cluster using Hive and Impala, result TSVs were stored in AWS-S3, results were copied to AWS-RDS (MySQL) using copy activity in data pipeline, and the reports were run on this data. All the schedules were managed by AWS–Data pipeline.
  • Rich reports (Self-service BI and Ad-hoc reporting) on aggregated data.
  • Data mining capabilities for identification of specific patterns and trends.

Execution strategy
As part of its execution strategy, Cybage did the following:

  • Capitalized on phased methodology, which enables targeted solution development (infrastructure, centralized DB, ETL (Extract, Transform and Load), reporting, Self-service BI, and data mining capability).
  • Capitalized on SCRUM Agile methodology for active tracking, greater agility, and recurrent deployments.

Value realized
The solution provided the following benefits to the client:

  • Ability to develop comprehensive reports with higher quality and in-depth data analysis, aiding informed decisions.
  • Faster and efficient data processing on a centralized database.
  • Encouragement to end-users to use Self-service BI for analyzing and visualizing data.
  • 75% reduction in report generation efforts.

Tools and technologies
Cybage used the following tools and technologies:
Development Java, MapReduce, Pig, Hive, Impala 
Testing  Manual testing
Tools  AWS-S3, AWS-EC2, AWS-EMR, AWS-RDS (MySQL)

Cybage services utilized
Architectural Services, Development, Testing, Big Data and BI CoE capabilities.

About the client
The client is a leading provider of cloud-based services for the smart home and business monitoring to millions of subscribers through a network of service providers.
 
Technology problem
The client was facing the following technology issues:

  • The client required End-to-End (E2E) Functional testing in a complex Internet of Things (IoT) and cloud system landscape.
  • Test automation was absent.
  • The client required simultaneous testing of mobile apps for multiple platforms such as iOS, Android, and Windows phones.

Technology solution
Cybage provided a technology solution, comprising:

  • A comprehensive IoT lab for near real-world testing.
  • Development of reusable assets for Functional and Regression testing of various smart devices and panels.
  • Provision of a robust test automation framework using Selenium for testing to help reduce the time to market.
  • Provision of custom-made utilities or plug-ins to monitor the application, report issues, and track changes on Confluence.

Execution strategy
The execution strategy of Cybage was as follows:

  • The Cybage Testing was responsible for adopting best practices, designing test strategies, creating automation suites, and performing test execution.
  • We perform Manual testing across the entire value chain to accommodate changing requirements in a dynamic smart devices environment.
  • We capitalized on a keyword-driven framework for automation to validate the stability of various functionalities on the web.

Value realized
Using this platform, the client offered a comprehensive solution for consumers and businesses to secure and remotely monitor homes and offices with a range of devices. The client ensured:

  • Continuous quality enhancement through review and defect prevention.
  • Continuous productivity enhancement through test automation using multiple tools.
  • Lower total cost of ownership through Cybage’s mature and well-set processes for test execution.

Tools and technologies
Cybage used the following tools and technologies:
Test automation CasperJS, PhantomJS, C#.NET and Core Java, Selenium WebDriver
ALM  Integrated Atlassian tools—Confluence, JIRA

Cybage services utilized
Development, Testing, and Test Automation

About the client
The client is a leading benchmarking solutions vendor for the Telecom industry on wireless services. It offers unmatched solutions for network benchmarking, analysis, and testing.

Technology problem
The client was facing the following issues:

  • The client was incurring high annual licensing costs due to the use of proprietary collection equipment (specialized hardware) for network performance measurement.
  • The existing solution was not scalable due to the exponential increase in the licensing cost.

Technology solution
Cybage’s solution comprised the following:

  • Development of cost-effective native mobile applications for surface layer network performance analysis. The native mobile application is easily configurable, scalable, and runs on non-rooted devices.
  • Mobile App allows users to configure, run, and review multiple tests for network analysis and share the results.
  • Support for app customization, including customer-specific logos and assets for superior customer experience.
  • Development of Public apps with limited functionality for data collection using crowdsourcing.
  • Interactive web-based reporting with secure web solution to view benchmarking statistics.

Execution strategy
Cybage adhered to the following plan to provide effective results to the client:

  • Conceptualization, Architecture and development of native mobile enterprise Android app for network analysis and Public iOS or Android app with limited features.
  • POC creation to verify the proposed app network data collection capabilities.
  • Adherence to Iterative methodology to create production-ready app, which mitigated the risks and fulfilled the non-functional requirements.

Value realized
The solution provided the following benefits to the client:

  • This platform helped to replace specialized hardware with enterprise native app for network data collection, eliminating licensing cost.
  • The client was able to open up new sources of revenue by offering custom designed solutions for network analysis to third-party companies.
  • The utilization of crowdsourcing accelerated data collection, which came at a fairly lower price.

Tools and technologies
Cybage used the following tools and technologies:
Dev  Android Studio, Visual Studio, Eclipse, .NET, WCF, Java, Android
Testing  Manual testing, Fiddler
ALM  TFS
 
Cybage services utilized
Architectural Services, Development, Testing, Enterprise Mobility Center of Excellence (CoE)

About the client
The client is a leading global Cloud Software-as-a-Service (SaaS) and Platform-as-a-Service (PaaS)  provider. Its core solution is an integration platform that enables applications to network and connect with a variety of on-premises and cloud services.

Technology problem
The client was facing the following technology issues:

  • Rapid increase in customer base and transaction volumes was affecting the technology choices and hampering the scalability of the architecture. They were anticipating the year on year (YoY) load to increase at five times the prevailing rate and this had become an immediate challenge.
  • The client was also facing high annual licensing costs and insufficient instrumentation for rich reporting.

Technology solution
Cybage provided the following technology solution:

  • We developed a highly scalable (25 times the current load), multi-class, workload-supported data processing and analytical big data platform, capitalizing on open-source technologies.
  • We provided a system that supported massive parallel processing and horizontal scaling across scale vectors.
  • The system enabled continuous computation (real rime analytics) on high velocity and high volume stream data.
  • It provided near-real–time, batch, and interactive reporting for data-driven insight.
  • We implemented extensive tools for platform monitoring, management, and operational support.
  • We ensured comprehensive regulatory compliance across varied compliance regions.
  • Our technology solution enabled a growth spurt (25X) with incremental provisioning. The details are as follows:
  1. Data velocity: More than 250,000 messages per second.
  2. Data volume: 150 MB per second to 10 TB per day.
  3. Data processing requirements: Data analytics: one minute –– hourly, monthly, and historic ranges.
  4. Interactive system response time: three seconds.
  5. Raw data retention period: 90 days and after that, in offline data systems.

Execution strategy
The execution strategy of Cybage comprised the following:

  • Conceptualization and development of a big data solution from the ground up to support the predicted scale of 25 times the current load.
  • Lab experimentation to verify the proposed architecture for key NFRs (Non Functional Requirements).
  • Adherence to Scrum Agile methodology for more predictable release cycle, higher solution stability, and accurate project visibility.
  • Usage of development tools such as Atlassian FishEye and Crucible for better code quality and management of release processes.
  • Collaboration using Atlassian Confluence, JIRA, and HipChat to support cross-functional and geographically scattered teams.

Value realized
Cybage’s solution provided the following benefits:

  • Ability to identify key trends and behaviors, obtain deep data traffic understanding, perform meaningful Key Performance Indicator (KPI) reporting, and recognize additional digital revenue streams.
  • A synergistic architecture for future-proof Big Data management infrastructure.
  • Access to richer data points and analytics.

Tools and technologies
Cybage used the following tools and technologies:
Development Cloudera Hadoop and its services, Storm, Spark, Kafka, Cassandra, Java
Testing      JMeter, Data mart, Java
 
DevOPS Puppet, Vagrant, Amazon Web Services (AWS) EC2 deployment
Application Lifecycle Management (ALM) Integrated Atlassian tools – Confluence, JIRA, HipChat, Stash, FishEye or Crucible, Gliffy plug-in
Monitoring and alerts    Graphite, Grafana, Nagios

Cybage services utilized
Architectural Services, Development, Testing, Platform Monitoring, Management and Operational Support, Cloud, Big Data, ALM, DevOps Capabilities

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