Data on Cloud

Cloud Data Management Services

Data Ingestion on Cloud

We help you build persistent and resilient data capture pipelines that can ingest batch & real time streaming data from internal business applications, SaaS transactional events, devices, sensors & on-prem to cloud storage.

Data Transformation on Cloud

We use Apache Spark / Hadoop with cloud ETL services to load data into cloud storage, distribute compute across multiple nodes, orchestrate pipelines and transform multi-model data into valuable information.

Storage on Cloud

We build cloud based centralized storages – massively parallel processing databases (MPP), key-value stores, performance DWH or data lakes to ingest your structured, semi-structured and unstructured data and objects.

Cloud Data Warehouse

We integrate your enterprise data sources into one central DWH using AWS Redshift, Azure SQL Datawarehouse, Google Big Query or Snowflake to seamlessly store, secure, organize & query the processed data.

Cloud Data Lake

We build data lakes to store the streaming raw & unstructured data from your extract, transform, load, and ML pipelines. Also establish a tight integration with the data transformation, exploration & consume services.

Data Science on Cloud

We explore hidden insights by consuming your raw & transformed data using cloud vendor’s proprietary real-time APIs, consumable ML models, notebooks, and libraries then embed the insights into your applications.

Data Insights on Cloud

We build cloud visualization solutions using AWS Quicksight, Microsoft Power BI or GCP Data Studio on top of their respective cloud storage, and compute services to seamlessly decode large volumes of datasets.

Cloud Data Security, Identity & Compliance

We implement cloud vendors security services on top of your applications, data & infra for auditing, regulatory compliance, DDoS protection, encryption, firewalls, threat detection and identity & access management.

Cloud Data Management Principles

Performance Efficiency

Efficiently scale the cloud storage and compute capabilities to meet the dynamic needs of customers

Operational Excellence

Run and manage applications effortlessly to make continuous improvements and faster releases

Reliability

Make data available all the time using auto-recovering, backups and workload management

Security

Implement cybersecurity principles to secure the data from development to deployment

Cost Optimization

Reduce Cloud Total Cost of Ownership (TCO) through yearly tier and pay-as-you-go models

Customer FAQs & Our Responses

1. How do you choose the right cloud data architecture?

We analyze your workloads, storage, infrastructure, performance, availability, and security requirements to choose the right data architecture that is easily maintainable, testable, isolatable and works seamlessly with your existing ecosystem. Our Data Architect and Functional SME will organize a whiteboarding session and recommend the best fit among the proven AWS / Azure / Google Cloud Architectures.

2. How do you choose the right tools & technologies?

We continuously observe the market reports on top programming languages, frameworks, databases, web servers, and server less cloud stack, evaluating them against time to design, cost of development, support community, and security breach history. Then we pick the right tools & technologies based on your business case, delivery timelines, peripheral tech stack, system load, userbase, and skillset availability to support in the future.

3. What coding, testing, and deployment practices do you follow?

We follow the 12 Factor App Methodology for building scalable, independent, and resilient enterprise products. It defines best practices for developing Software as a Service focusing on service level codebase separation, dev/test/prod environment parity, infra as a code creation, build separation, and deployment automation. We also follow the CAP theorem for creating a distributed data store system to overcome unavailability and network failure.

4. How do you ensure a smoother transition from an incumbent vendor?

We collect your application’s technical, functional, process, and domain knowledge from your incumbent vendor or in-house team through our proven knowledge acquisition and validation practices. In scenarios of no documentation or limited SME support, we assign a cross-functional team to do the reverse engineering on your ecosystem and create a portfolio knowledge repository with as-is and to-be roadmap documentation.

5. What project management and governance methodologies do you follow?

We follow an agile project delivery model with a two-week sprint cycle to create frequent team connects, increase visibility, reduce knowledge gaps, and accommodate scope changes quickly based on user feedback. Our project delivery CoE – a team of technical and functional experts acts as a support system for audits, training, and guidance. Our Project Manager and Client Partner work as risk mitigation managers and prevent unexpected outcomes.

Cloud Implementation Partner You Need

The Lean Startups

Innovation, newness, and investor attraction are the Startup foundations. With you, we act as a lean technology partner and integrate plug-n-play tools + cloud storage + web frameworks with custom development to rapidly deliver user-lovable & monetizable MVPs.

Small & Mid-size Enterprises (SME)

New customer acquisition, operations optimizations, and seamless business transactions would be your destination. We help you in this journey by creating cloud solutions with 99.99% availability, in-built workflow automation & self-service capabilities.

The Big Enterprises

Integrating business processes, subsidiaries, customers, and suppliers to create a cloud-based intranet & single source of truth data systems could be your focus area. We provide product engineering teams at scale to translate your vision into reality.