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Background

In recent times, digitally born businesses have been successful in rapid disruption and value creation, through platforms. This is because platform-based business models create/enhance the ecosystem, facilitate value exchanges between different stakeholders in the ecosystem ('participants') while supporting massive amounts of data. To summarize, platforms enable data driven decision making.

As a result, enterprises to survive in an unstable economic environment and competitive landscape need to embrace platform-based business models. But to do the same, they need the ability to connect and extract value from the massive amounts of data from various data sources such as internal applications, third party systems and external sources. This is easier said than done, as even as enterprises begin unraveling their data, they need to coexist with disruptive business models, while running the business with existing systems and legacy business models.

Creating Data Platforms in traditional enterprises require the ability to architect, design, develop, maintain and enhance Data Platforms as per the digital agenda. These platforms should be based on modern technology stacks, cloud based and have the ability to integrate with existing systems.

Sonata helps create these platforms to accelerate digital transformation by building, extending and enhancing platforms, through our unique Data Platform engineering approach - a framework for architecting, developing and managing platforms that adhere to OPEN, SCALABLE, CONNECTED and INTELLIGENT platform characteristics.

Digital Transformation drives new possibilities:

  • Empowers employees with enhanced business agility
  • Optimizes operations and business processes
  • Transforms products through differentiated business models
  • Engages customers with personalized experiences

Challenges In Evolving into A Digitally Transformed Enterprise

Connecting and extracting value from massive amounts of data of different types from various data sources like internal applications, third party applications, and external sources is nearly impossible.

Enterprises must coexist with disruptive business models, embrace new digital initiatives by creating platforms and leverage the intelligence possible from data, without interruptions to existing proceses.

Creating data platforms in traditional enterprises requires the ability to architect, design, develop, maintain and enhance data platforms as per the digital agenda. These platforms should be based on modern technology stack, cloud based and also have the ability to integrate with existing systems.

Achieve Platform Business

Data Platform Engineering is Sonata's unique approach to build platforms that "Enables creation of platforms" or "Modernization/migration of existing IT into platforms" for achieving digital transformation.

Key elements:

  • Service Oriented Approach (Microservices/API's, Data Experimentations and Model Creation, Databases for use cases etc.)
  • Layered separation of concern approach. (collection layer, processing layer, data storage layer, infra layer, analysis layer, distribution layer / integration layer)
  • Design Thinking Led
  • Hyper Productivity (Tools and Frameworks)
  • Full Automation (Agile and DevOps)

The unique approach includes:

  • A structured way of creating digital agenda through digital templates
  • Building industry view and Marchitecture Sonata Software
  • Design thinking led ideation workshops and road mapping.
  • Technology architecture that archives platforms characteristics - Open, Scalable, Connected, Intelligent
  • A world class execution methodology that orchestrates and unifies multiple digital technologies into single platform.
  • Digital Links Model - Digital Strategy, Key Outcome KPI, Data Drivers, Data Sources and Gaps, Modelling using Design Thinking Model.
  • Digital Proofs - PoC Execution, Workshops…
  • Platform Architecture - Build technology architecture with data platforms characteristics - Open, Scalable, Connected, Intelligent to realize your digital business process transformation objective

Sonata's 7-Step Methodology to Achieve Data Platforms for Delivering PBBM

Sonata has a well-defined 7-step methodology to help enterprises to adopt the platform-based business model:

 

Platform Maturity Assessment:

Sonata conducts assessment of:

  • Customers business
  • Associated platform models and digital process
  • Business, data and technology assessment relevant to platform and digital processes
  • Benchmarks industry best practices
  • Makes recommendations
 

Customer Digital Agenda:

Sonata creates the Digital Agenda for the enterprise and provides a workable, customized agenda.

 

Platform Ecosystem & Design Thinking:

Sonata, through a Design Thinking process, co-creates the platform ecosystem, models, and data platforms relevant to the enterprise.

 

Digital Business Processes Definition:

Sonata helps to create a Digital Business Process library for the enterprise along with the `As Is – To Be' gap analysis (business). Based on the same, future business processes and Marchitecture Sonata Software are generated

 

Platform Characteristics:

The 16-point framework is applied to identify relevant platform characteristics to the `To-Be' Platform architecture. Further data characteristics are identified using the framework.

 

Platformation Roadmap & Proposal:

Recommendation for platform roadmap and implementation priority are outlined:

  • Implementation priority based on quick wins, phases etc.
  • Technology adoption – data, cloud, platform engineering, and apps scope
  • Implementation proposal / business case covering execution plan, budgets, timelines etc.
 

Implementation - Execution Approach:

The execution methodology is provided. Comprehensive plans for pilots, programs and projects are created and technology decisions for `build and buy' are arrived at. Platformation KPIs are continually measured and governed to ensure platform development and extensions, deployment and management.

Platformation Service Description

Data Platform helps in identifying, executing, and maintaining platforms:

  • Data Platformation Consulting: Analysis, architecture and roadmap
  • Development of Data Platform: Design, build and manage platform development adhering to the platform characteristics of OPEN, SCALABLE, CONNECTED and INTELLIGENT.
  • Development of Data Distribution and Consumption Platform: Design, build and manage integration platforms, reporting platforms, analytical platforms, and application platforms.
  • Data Platform and Consumption Platform Maintenance

Platform Characteristics

To ensure that the data strategy adheres to the Platformation concepts of Open, Scalable, Connected and Intelligent – the following elements are included in the overall execution:

  • Scalable data storage (structured &unstructured)
  • Connectivity to external systems
  • Data insights through AI / ML
  • Data integration / aggregation
  • Data governance / stewardship
  • Data encryption

Validation against Data Platformation characteristics for identified existing systems - 12 point framework:

Key Constructs of the Service

Sonata's Platform Engineering & Architecture Blueprint (PEAB Framework) provides for a robust platform architecture for creating an ecosystem-based model consisting of API, UX, Data, Device/IOT connectivity, Microservices, cloud components and engineering practices for speed and reliability.

API PLATFORM:

Sonata's PEAB framework based on:

  • API framework/reference architecture,
  • Cloud adoption framework,
  • Mobile enablement platform (Halosys),
  • IOT reference model

enables building the connected capability of this platform.

UX PLATFORM:

Digital experience must be delivered seamlessly across different devices, channels and should have the ability to connect to different APIs/Services and deliver seamless and native user experience. The intelligent experience to the digital users and adaptability of the application based on the device are some of the key aspects of the UX platform

MICROSERVICES PLATFORM:

Platforms need to be scalable to support new business lines, products, locations, markets and an elastic user base. Sonata's PEAB framework is anchored on Microservices-based architecture and cloud-based platform services. This architecture enables easier adoption of cloud service and architecture innovations that empower scalability.

DATA PLATFORM :

Data is the heart of the platform and hence our data strategy and reference architecture consist of process and tools to Identify, Store, Integrate, Share and Govern Data. This coupled with Robotic Process Automation Framework, Conversational User Interface/Front End Development framework and an engineering process based on contemporary UX design principles, leverage Design Thinking for INTELLIGENT user experience with insights, predictions and recommendations to the user/enterprise. With Machine learning/AI, this intelligence can evolve and mature with time.

INFRASTRUCTURE PLATFORM:

Platform-based Business Model, by its very nature, demands scalable infrastructure based on the demand of the services, duration and the business model requirements. By this definition, Cloud is the infrastructure backbone for platform-based businesses to meet the scalability and connected requirements of the platform.

Modern Engineering Processes:

Modern Engineering Processes based on DevOps, Continuous Integration/Testing, Blue/Green Deployments, Version management, Design Thinking are key aspects of this technology.

Assets & Accelerators – Platform

  • Data Strategy Tools
    • Internal Source Data
    • Industry Specific Data
      • External Data
      • Social Data
  • Data Flow Tools – Sonata's Swift framework is an accelerator that helps to store data in data lake and data warehouses
  • Data Processing Tools – Sonata's Ferret framework processes data to ensure data standard cleaning procedure de-duplication, statistical analysis of data, feature reduction and algorithm selection
  • Data Experimentation Tools – Ability to create experimental data infrastructure for relevant data for AI/ML model designs
  • Data Governance Tools – Operational reports for data lake and data warehouse usage
  • Industry Assets:
    • Retina – Retail Analytics – Discover ways to acquire and retain more customers
    • Transit – Travel Analytics – Provide tour and travel operators with a comprehensive analytics solutions with deeper customer engagement
    • Modern Distribution Analytics – Gain real-time 360o visibility across the supply chain and provide advanced forecasts
    • Assets through Sonata's AML Lab for:
      • Recommendation Engine
      • Forecasting
      • NLP (Social Sentiment)
      • Document Parser

API - Tools/Tech Stack/Assets

  • Microsoft Platform
    • SSIS, SSAS, SSRS
    • ADL, ADW, ADF, AMLS, AAS
  • Big Data Platform
    • Hadoop / HDFS / MapReduce
    • Sqoop / Flume / Hive / Pig
  • AWS Platform
    • S3, EC2, Athena
    • Kinesis / Data Pipeline
    • Redshift / Quicksight
  • Reporting & Visualization
    • PowerBI, Tableau, Qlikview
  • Data Science
    • 'R' / Python
    • AMLS / AWS ML
    • Sagemaker / Jupyter
    • Tensor Flow / Scikit-Learn
  • Additional Products
    • Informatica, SAP BO, Snoflake

Frameworks and Assets:

  • Framework & Platforms
    • Data Warehouse Framework
  • Templates
    • Reference Architecture
    • Questionnaires
    • Design Templates
    • Test Templates
  • Methodology
    • Data Strategy Methodology
    • Crème Report Migration Methodology

People & Technology Skills

In building and maintaining platforms, apart from tools and processes, people play a key role with their multi-dimensional skills:

  • Visualizing the Platform:
    Sonatians practice Design Thinking and Business Oriented Empathy as their way of life to help them realize the digital Agenda.
  • Digital Technology Skills
    State-of-the-art technology skills along with aptitude for problem solving and quick learning are key traits of the people building platforms at Sonata
    • Data Platform Architecture skills across on premise and cloud technologies
    • Data Engineering Skills - Azure Services, AWS Services SQL Server, MySQL, PostGres, Oracle, NoSQL, Node.js
    • Data Platform Skills - Azure, AWS, GCP Engineering and Operations, Hadoop / HDFS / MapReduce, Sqoop / Flume / Hive / Pig, Snowlflake, Informatica, SAP…
    • Data Science Skills – R, Python, AMLS / AWS ML, Sagemaker / Jupyter, Tensor Flow / Scikit-Learn, CNTK, PyTorch
    • Data Visualization Skills – Power BI, Tableau, UX, creatives, Graphics
  • Digital Engineering Process Skills
    Sonata's tech force is trained in key digital engineering processes which bring in agility for the platform to be built and sustained
    • Devops – CI/CD
    • Cloud Operations
    • Agile Skills
    • Collaboration Techniques
  • 8000+ Person Years of delivering Data & Analytics services

Case Study

A leading international membership-based tour operator with a diverse set of product offerings had identified the opportunity to grow memberships with enhanced user engagement and efficient commerce operations through a next-generation social travel platform. The company operates in a multi-level marketing model with members, sponsor members, suppliers and 3rd party service providers as the key participants of the platform.

Problem Statement

Build an integrated yield management solution that is scalable, robust and can be made to adapt to the very volatile nature of demand changes. The business challenges were:

  • Modernize the existing Revenue Management Solution to help increase & enhance channels for faster on-boarding, Expedited Booking Decisions
  • Intelligent search with high scalability and business alerts to seek abandoned customers
  • Personalize promotions and offers for relevant customer segments

How Sonata Helped achieve Platformation

  • Sonata performed Platform-based maturity assessment and identified various gaps in the existing systems
  • Sonata applied the 16 -point Platform framework and 12 point Data Platformation framework to design a highly scalable architecture and the associated modern technology components
  • Sonata built a Data Platform that consists of:
    • Data Ingestion
    • Data Lake
    • Data Warehouse
    • Consumption specific data stores
    • Dynamic Infrastructure to facilitate scaling and data science process
  • Sonata built the following analytics oriented and Machine Learning oriented consumption platforms
    • Customer 360
    • Yield Management
    • Commercial / Booking Analytics
    • Reporting Engine
    • Algorithms / Machine Learning Platform
    • Integration with inventory and booking / selling systems

Unique aspects

  • Consistent application of Platform Characteristics:
  • Application of Modern Technology and Architecture:
    • Cloud Architecture, AWS
    • Data Platform Architecture
      • Ingestion – Lambda, S3, Kinesis
      • Pipeline – Glue, talend, alteryx
      • Data Storage – S3, Glacier
      • Meta Data Store – DynamoDB, Elastic Search
      • Automation – Cloudformation, Ansible
      • Security Compliance – Macie, IAM, KWS
      • Monitoring & Alerting – CloudWatch, CloudTail
      • Data Analytics – Athena, Redshift
    • Data Consumption Applications
      • Yield Management - Tibco, Informatica, Java, Oracle Exadata
    • Integration with inventory and booking / selling systems
      • Tibco, talend, Informatica, Microservices
    • Machine Learning
      • Sagemaker, Amazon Machine Learning
      • Spark, Java
    • Data Visualization
      • Quicksight, Tableau

Key Artefacts Used:

  • Maturity Assessment
  • Data Platform Reference Architecture
  • Reporting Templates
  • Integration Best Practices
  • Automation Scripts
  • Sonata's 16 Point Technology Framework & Data 12 Point Technology Framework
  • Platformation Templates (Design Thinking ) – For deriving use cases