Data Engineering

Streamline Your Database Migration with Proven Best Practices

Future-Proof Your Data Warehouse with BigQuery

Modernize your data warehouse to unlock actionable insights and meet the growing demands of data analytics. Traditional data warehouse solutions often fall short in handling large data volumes and supporting advanced real-time analytics. With BigQuery (Google BigQuery), you get a serverless, highly scalable, and cost-effective solution that delivers predictive insights with exceptional speed. Its groundbreaking Dremel architecture leverages columnar storage and the strategic separation of storage and compute to provide unmatched elasticity.

BigQuery’s Technical Edge and Enterprise Readiness

• Real-time Performance: Achieve true real-time analytics through capabilities like streaming ingestion and native support for Change Data Capture (CDC), ensuring your data is always current.

• Seamless Integration: Accelerate time-to-value with native connections to your preferred BI tools, leveraging the BI engine and direct Looker integration for rapid visualization and reporting.

• Security & Governance: Ensure data security in BigQuery and robust data governance in BigQuery with built-in features that meet strict enterprise compliance standards.

Accelerate Your Data Warehouse Modernization Journey

Partner with Transcloud to seamlessly migrate your legacy data warehouse to BigQuery. We specialize in complex transitions, including Teradata migration to BigQuery, and help you navigate the competitive landscape like Snowflake vs BigQuery.

• Proven Framework: Leverage our proven data warehouse migration framework and expertise in Google Cloud Platform (GCP) to fast-track your journey.

• Strategic Investment: Future-proof your analytics investment while reducing migration risks and ensuring a smooth transition.

• Modern Strategy: Modernize your data management strategy for better scalability and performance, giving your business the agile foundation it needs.

Transforming Your Data Ecosystem: Legacy Data Lake Modernization to a Serverless Data Lake

Enhance the efficiency, scalability, and usability of your data lakes to unlock their full potential as a single source of truth in your organization’s data ecosystem. A modernized data lake acts as a centralized repository, enabling secure, cost-effective storage, data ingestion, transformation, and analysis of diverse datasets. It minimizes the need for complex pipelines through a Zero-ETL architecture. It complements data warehouses, coexisting in a Data Mesh architecture to leverage the strengths of both solutions. We provide a robust data governance framework, including essential Data Quality checks and Data lineage tracking, ensuring compliance and data quality across your assets.

Migrate Apache Spark and Hadoop-Based Data Lakes to Google Cloud Platform (GCP)

Our specialized Hadoop migration to cloud strategy provides a clear path away from complex processes like YARN management, leveraging key GCP services:

• Fully Managed Services & Architecture: Seamlessly provision, auto-scale, and govern purpose-built data and analytics clusters using services like Dataproc migration for a fully managed Apache Spark experience on Google Cloud. We implement the Schema-on-read approach, which is fundamental to a modern Cloud Storage Data Lake. We also use Federated identity management to secure access across the lake.

• Integrated Data Science and Analytics: Utilize tools such as BigQuery (for advanced querying), AI Platform Notebooks, GPUs, and other accelerators to streamline data analytics development and deployment. We integrate advanced capabilities like BigLake and Analytics Hub for superior governance and data sharing.

• Data Ingestion and Processing: We implement advanced data ingestion tools like Pub/Sub and Dataflow to handle both batch and streaming data, supporting real-time analytics within your modernized data lake.

• Cost Optimization: Reduce costs with Google Cloud’s auto-scaling capabilities, which decouple storage from compute. Enjoy faster query speeds and cost efficiency compared to traditional on-premises Hadoop setups through automated cluster deletion and custom machine configurations.

Empower Actionable Insights with Google Cloud

Transcloud’s expertise in Legacy Data Lake modernization ensures a seamless transition to Google Cloud Platform (GCP), empowering organizations to:

• Modernize their data lakes for enhanced analytics performance.

• Achieve substantial cost savings and efficiency improvements.

• Leverage Google Cloud’s tools for strategic data-driven decision-making.

We provide a specialized data management strategy that focuses on maximizing your analytics investment while minimizing migration risks.

Real-Time Data Processing and Analysis

Streaming analytics enables the continuous processing and analysis of data records in real-time (or near-real-time), offering powerful predictive insights on the fly. Unlike traditional batch processing, streaming analytics is crucial for handling constant streams of data generated by modern sources, such as telemetry from connected devices (IoT stream processing), web application log files, e-commerce transactions, social network data, and geospatial information. It is the ideal solution for real-time aggregation, correlation, filtering, and sampling, enabling immediate applications like fraud detection and personalized recommendations.

Transcloud specializes in streamlining real-time data processing on Google Cloud Platform (GCP) for businesses across various industries. Our services help organizations leverage Google Cloud’s advanced data analytics ecosystem to optimize data ingestion, build modern data warehouses and Data Lake Houses, and orchestrate powerful analytics platforms.

Core Services for Serverless Streaming on Google Cloud:

1. Efficient Data Ingestion (Using Pub/Sub)

Transcloud facilitates seamless data ingestion from multiple sources using Pub/Sub, ensuring that the system is scalable and can handle massive data volumes with reliability. Using event-driven mechanisms, we guarantee high-performance data ingestion suited for real-time analytics.

2. Real-Time Data Processing

Our solution leverages Cloud Dataflow for processing real-time streaming data, achieving true serverless streaming. It offers a unified programming model that simplifies workload management compared to legacy systems. We also utilize Apache Beam, an open-source framework for building flexible, multi-language data pipelines that handle streaming and batch processing seamlessly. This enables sophisticated real-time ETL and ELT workflows.

3. ETL Workflows

Using Cloud Data Fusion, we enable data engineers to create, test, and deploy ETL pipelines for streamlined data integration. This helps in building scalable enterprise data solutions while enhancing operational efficiency, providing a modern alternative to a monolithic data warehouse structure.

4. Workflow Orchestration

Transcloud offers comprehensive end-to-end orchestration of data pipelines with Cloud Composer, which is powered by Apache Airflow. This fully-managed service allows for the visual creation of workflows, ensuring seamless integration with GCP’s data and analytics services, improving overall productivity.

Transform Your Data Processing Strategy

Transcloud helps organizations unlock the full potential of Google Cloud for data analytics and streamlined data processing workflows. Whether you’re migrating your data pipelines to the cloud or embarking on new analytics development projects, our team of experts will support you in modernizing your data processing, accelerating time-to-insight, and reducing costs compared to traditional legacy systems.