Transforming Vehicle Telemetry through Big Data Platform
Transform data into real-time intelligence with scalable, cloud-native Big Data and Engineering solutions.
Introduction
In today’s hyper-connected, data-intensive world, enterprises must move beyond traditional processing to stay agile. Tata Elxsi’s Big Data and Engineering services enable organizations to transform fragmented, high-volume datasets into intelligent insights. We design cloud-native ecosystems for real-time streaming, batch, and serverless analytics using Apache Spark, Kafka, Flink, Airflow, and services on AWS, Azure, and GCP.
We help enterprises adopt unified Lakehouse architectures with technologies like Delta Lake, Hudi, and Iceberg to support AI/ML, real-time analytics, and ACID compliance. Our solutions also address cloud migration, AI observability, and cost optimization—building secure, scalable platforms that drive innovation and resilience.
Revolutionising Driver Performance Management with AI-powered Advanced Telematics
Business Challenge
Modern enterprises face a surge in data volume, variety, and velocity—making traditional data systems inadequate for real-time decision-making and innovation. Legacy ETL processes, and limited scalability hinder operational efficiency and timely insights. Additionally, the complexity of managing hybrid and multi-cloud environments, ensuring regulatory compliance, and optimizing cloud costs creates significant challenges. Businesses need robust, cloud-native data platforms that can handle streaming and batch workloads, integrate with modern frameworks like Lakehouse and data mesh, and support AI/ML at scale. Addressing these challenges is critical to unlocking data’s full potential and achieving measurable business impact.
Here’s How We Help
1. Intelligent Data Pipelines
- Design real-time and batch ETL with Apache Spark, Kafka, Flink, and Airflow. Ingest structured, semi-structured, and unstructured data from IoT, APIs, apps, and platforms.
- Enable event-driven streaming with serverless orchestration (e.g., AWS Lambda, Google Cloud Functions) for low-latency analytics, personalization, and ML.
2. Modern Data Architecture
- Build scalable Lakehouse, Data Mesh, and Data Fabric architectures. Deploy secure, cloud-native solutions on AWS, Azure, GCP, Databricks, and Snowflake.
- Support hybrid/multi-cloud with automation and high availability. Accelerate cloud migration via templates and tools with minimal disruption.
3. Governance & Operationalization
- Embed observability, lineage, and access control across the stack. Use real-time dashboards and alerts to monitor pipeline health.
- Automate governance, auditing, and compliance (GDPR, HIPAA, CCPA). Optimize cost via workload scheduling, autoscaling, and FinOps practices.
Solution Framework
Tata Elxsi’s Big Data & Engineering framework enables scalable, cloud-native data processing via streaming and batch pipelines. Designed for hybrid and multi-cloud setups, it supports serverless execution, automated orchestration, and seamless cloud migration. It enables real-time decisioning with built-in governance, observability, and a cost-optimized, auto-scaling architecture. Technologies like Apache Spark, Kafka, Flink, Airflow, and cloud platforms including AWS, Azure, GCP, Databricks, and Snowflake ensure high performance, resilience, and scale.
Solution Features
Unified Data Engineering Pipeline
- Manages ingestion to AI/ML modeling across real-time and batch
- Uses Apache Spark, Kafka, Airflow, Flink for ETL orchestration
- Enables serverless execution via AWS Lambda, Azure Functions
- Handles structured, semi-structured, and unstructured data
Scalable, Cloud-Agnostic Infrastructure
- Deploys on AWS, Azure, GCP, Databricks with multi-tenant support
- Automates provisioning, data movement, event-driven workflows
- Supports scaling, balancing, and DR for availability
- Integrated with Terraform, Kubernetes, and CI/CD pipelines
Built-in Intelligence & Observability
- Provides dashboards, log tracking, resource schedulers, and cost tools
- Ensures auditability, lineage, and access control for compliance (GDPR, HIPAA, SOC 2)
- Embedded with Prometheus, Grafana, and OpenTelemetry for performance tuning
Why Tata Elxsi ?
- Optimize cloud costs with real-time usage insights and smart cost governance across data pipelines
- Ensure fast, secure cloud migration with minimal disruption to your business
- Deploy serverless and container-based analytics for lower overhead and quick scaling
- Simplify event-driven workloads with real-time streaming data architectures
- Proven track record of delivering 35%+ cost savings and 99.9% uptime for data-driven platforms
Info Hub
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What is Big Data Engineering, and why does my business need it?
Big Data Engineering involves designing and building systems to collect, store, process, and analyze large volumes of data. It helps businesses gain real-time insights, automate decision-making, improve customer experience, and innovate faster.
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Can you help us migrate from on-prem to cloud?
Absolutely. We specialize in cloud migration strategies that ensure data integrity, minimal downtime, and regulatory compliance. We support lift-and-shift, re-architecture, and hybrid models.
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What’s your approach to handling unstructured data?
We support unstructured, semi-structured, and structured data through NLP, computer vision, and custom parsers—processed via resilient data lakes, cloud storage, and real-time ingestion pipelines.
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How does Tata Elxsi support cost optimization in cloud-based data systems?
We use tools and practices like autoscaling, serverless computing, storage tiering, right-sizing, and FinOps strategies to minimize your cloud spend while maintaining performance.
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Can you integrate with our existing tools and data sources?
Yes, we design solutions that integrate seamlessly with your existing infrastructure, databases, applications, and BI tools — ensuring business continuity and data consistency.
