Big Data and Data Lakehouse Solutions

Mastering Big Data and Data Lakehouse Solutions

As Nexa we are an end-to-end DataOps and Data Engineering company specializing in big data and data lakehouse solutions. Delivering these solutions demands comprehensive expertise—from the storage layer to compute, compute to application, and even proper network design. Partnering with open-source platforms and multinational vendors, we provide tailored services from technology selection to implementation and managed services, enabling enterprise success

Leverage the Power of Lakehouse Architecture

Unify your data warehousing and big data needs with a modern Lakehouse solution, enabling seamless data integration, advanced analytics, and cost-efficient scalability. By combining the best of data lakes and warehouses, Lakehouse architecture ensures high-performance querying, real-time processing, and reliable data governance. Empower your organization to harness insights faster while maintaining flexibility for future growth.

Unified Data
Management

Seamlessly integrate structured and unstructured data across your organization. With a single architecture, you can simplify workflows, reduce data silos, and enhance decision-making.

Real-Time
Analytics

Harness the power of real-time data streaming and processing to gain actionable insights. Drive instant business decisions and adapt to rapidly changing market demands.

Tailored Architecture and Technology Selection

Choose the right architecture and technology stack for your data transformation. From strategy to implementation, we guide you in selecting and building solutions that align with your unique business goals and operational needs.

Cost-Effective
Scalability

Scale your data solutions flexibly, whether on-premise or in the cloud. Our architecture ensures optimal performance while minimizing resource overhead and total cost of ownership.

Optimized Performance and Efficiency

Take advantage of optimized data querying and processing technologies. Enhance efficiency with faster insights, lower latency, and superior performance tailored to your business needs.

Managed Data
Services

Focus on your core business while we handle your entire data ecosystem as a managed service. From infrastructure setup to ongoing support and enhancements, we deliver end-to-end data solutions tailored to your needs.

Unified Data
Management

Seamlessly integrate structured and unstructured data across your organization. With a single architecture, you can simplify workflows, reduce data silos, and enhance decision-making.

Real-Time
Analytics

Harness the power of real-time data streaming and processing to gain actionable insights. Drive instant business decisions and adapt to rapidly changing market demands.

Tailored Architecture and Technology Selection

Cost-Effective
Scalability

Scale your data solutions flexibly, whether on-premise or in the cloud. Our architecture ensures optimal performance while minimizing resource overhead and total cost of ownership.

Optimized Performance and Efficiency

Take advantage of optimized data querying and processing technologies. Enhance efficiency with faster insights, lower latency, and superior performance tailored to your business needs.

Managed Data
Services

Our Data Lakehouse
Implementation Approach

Project Initiation and Planning

Define Objectives

Understand the business goals (e.g., analytics, AI/ML, operational reporting).
Identify key stakeholders and users

Define Scope

Decide which datasets and systems to include initially
Plan for scalability and future integrations.

Assess Current State

Audit the existing data infrastructure, sources,
and tools.
Identify key stakeholders and users

Select Technology Stack

Choose the lakehouse platform (intellectual property tools or open stack)
Determine supporting tools for ingestion, processing, storage, and analytics

Architecture and Design

Design Data Lakehouse Architecture

Create a unified architecture blending data lake and warehouse features.
Incorporate layers for raw data ingestion, curated datasets, and analytics-ready data.

Design Data Models

Use a schema-on-read approach for raw data
Define structured schema for curated and analytics-ready layers

Plan Data Governance

Define data cataloging, lineage tracking, and access controls.
Set compliance and regulatory standards  (e.g., GDPR, HIPAA).

Define Security Framework

Implement role-based access control (RBAC) and encryption
Plan for network and storage security.

Data Ingestion

Identify Data Sources

List structured, semi-structured, and unstructured sources (e.g., databases, APIs, IoT devices).

Ensure Data Quality

Define Security Framework
Use tools for deduplication, validation, and transformation.
Plan for network and storage security.

Build Pipelines

Implement batch and real-time data ingestion pipelines using tools like Apache Kafka, Flume, or cloud-native services.

Data Processing and Transformation

Develop ETL/ELT Workflows

Use frameworks like Apache Spark, dbt, or cloud services.
Implement transformations to prepare data for specific use cases.

Automate Processes

Schedule and orchestrate workflows using tools like Apache Airflow

Enrich Data

Integrate third-party datasets or contextual information where necessary.

Analytics and Query Enablement

Implement Query Engines

Deploy tools like Presto, Trino, or built-in lakehouse querying capabilities.

Develop Dashboards

Use BI tools (e.g., Tableau, Power BI) for visualization.

Build Analytical Models

Enable SQL-based queries and create ML-ready datasets.

Validate Data Accuracy

Measure query response times and pipeline throughput.
Optimize configurations for performance and cost.

Testing , Validation and Deployment

Functional Testing

Test data pipelines, ingestion, transformations, and queries.
Optimize configurations for performance and cost.

Deploy Lakehouse Solution

Move from staging to production environment.

Performance Testing

Measure query response times and pipeline throughput.
Optimize configurations for performance and cost.

Integrate with Existing Systems

Connect the lakehouse with data sources, BI tools, and downstream applications.
to handle growing data volumes and new workloads.

Techs we work with

Discover

Big Data and Data Lakehouse Solutions

Mastering Big Data and Data Lakehouse Solutions

Leverage the Power of Lakehouse Architecture

Unified Data Management

Real-Time Analytics

Tailored Architecture and Technology Selection

Cost-Effective Scalability

Optimized Performance and Efficiency

Managed Data Services

Unified Data Management

Real-Time Analytics

Tailored Architecture and Technology Selection

Cost-Effective Scalability

Optimized Performance and Efficiency

Managed Data Services

Our Data LakehouseImplementation Approach

Project Initiation and Planning

Define Objectives

Define Scope

Assess Current State

Select Technology Stack

Architecture and Design

Design Data Lakehouse Architecture

Design Data Models

Plan Data Governance

Define Security Framework

Data Ingestion

Identify Data Sources

Ensure Data Quality

Build Pipelines

Data Processing and Transformation

Develop ETL/ELT Workflows

Automate Processes

Enrich Data

Analytics and Query Enablement

Implement Query Engines

Develop Dashboards

Build Analytical Models

Validate Data Accuracy

Testing , Validation and Deployment

Functional Testing

Deploy Lakehouse Solution

Performance Testing

Integrate with Existing Systems

Techs we work with

Unified Data
Management

Real-Time
Analytics

Cost-Effective
Scalability

Managed Data
Services

Unified Data
Management

Real-Time
Analytics

Cost-Effective
Scalability

Managed Data
Services

Our Data Lakehouse
Implementation Approach