Big Data & Data Lakes Consulting

Modern organizations generate massive volumes of structured and unstructured data from diverse sources. Traditional data warehouses struggle to handle this scale, variety, and velocity, creating bottlenecks in analytics and innovation.

Digital Trendz designs and implements modern Big Data and Data Lake architectures that handle petabytes of data while enabling real-time analytics, machine learning, and AI applications. Our solutions leverage cloud-native technologies to provide scalability, flexibility, and cost-efficiency.

Big Data Services

  • Big Data Strategy & Assessment
  • Data Lake Architecture & Design
  • Lakehouse Implementation
  • Real-time Data Streaming
  • Distributed Processing (Spark, Hadoop)
  • NoSQL Database Solutions
  • Data Lake Security & Governance

Technology Stack

  • Databricks Lakehouse Platform
  • Snowflake Data Cloud
  • AWS Lake Formation & S3
  • Azure Data Lake Storage
  • Google BigQuery
  • Apache Spark & Hadoop
  • Delta Lake & Apache Iceberg

Modern Data Architecture

Data Lake Architecture

  • • Raw Zone - Source data ingestion
  • • Cleansed Zone - Validated data
  • • Curated Zone - Business-ready data
  • • Consumption Layer - Analytics & BI
  • • Metadata & Governance Layer

Lakehouse Benefits

  • • Unified data platform
  • • ACID transaction support
  • • Schema enforcement & evolution
  • • Time travel & versioning
  • • BI & ML on same platform

Big Data Use Cases

IoT & Sensor Data

Process millions of events per second from connected devices, sensors, and IoT platforms for real-time monitoring and predictive maintenance.

Log Analytics

Centralize and analyze application logs, system logs, and security logs for troubleshooting, monitoring, and threat detection.

Customer 360

Integrate customer data from CRM, web, mobile, social media, and transaction systems for complete customer insights.

Advanced Analytics

Enable data science teams to build and deploy machine learning models at scale using distributed computing frameworks.

Key Benefits

Scalability

Handle petabytes of data with elastic cloud resources that scale up or down based on demand.

Cost Efficiency

Pay only for storage and compute you use, with separation of storage and compute for optimal cost management.

Flexibility

Store any type of data (structured, semi-structured, unstructured) without upfront schema definition.

Performance

Leverage distributed processing for fast analytics on massive datasets with parallel query execution.

Ready to Scale Your Data Platform?

Let's design a modern Big Data architecture that unlocks the full potential of your data assets.