Artificial Intelligence
Build a robust data foundation with scalable data engineering and data lake solutions, enabling seamless integration, storage, and analysis for AI-driven insights.
Unlock the power of data
Despite access to massive volumes of data, most organizations struggle to process and harness it for advanced applications like machine learning and predictive modeling.
Without robust data engineering, you’re missing critical insights and limiting your potential for business transformation and innovation. Fresh engineers build an infrastructure for collecting, integrating, and scaling your data operations companywide.
You already own the data: we’re here to help you utilize it like never before.
Get ROI from the data you already have
Preparing the data you produce and store for advanced analytics and intelligent decision-making can be expensive and time-intensive, especially if you don’t have an in-house team dedicated to it. Our data engineering services folllow these steps to build a foundation for insights on demand.
#1: Increase Data Integrity
Enhance data quality and integrity by building robust pipelines that clean, standardize, and validate both structured and unstructured data before it enters data warehouses or data lakes.
#2: Eliminate Data Silos
Our data engineering solutions break down data silos by integrating disparate sources into unified platforms, making data accessible across departments and business units.
#3: Automate Manual Analysis
The automated data engineering workflows we build—covering ingestion, transformation, quality assurance, and analytics—replace repetitive manual tasks, drastically reducing operational costs and time-to-insight.
Unified
Fresh’s data lakehouses integrate both structured and unstructured data into a single platform, centralizing analytics and governance.
Scalable & Flexible
Built to scale, handling large volumes of data across your enterprise.
Turnkey
Ready-to-deploy platforms for analytics, data science, machine learning, and generative AI to accelerate and automate insights.
Comprehensive
Top-down implementation of access, privacy, security, and compliance policies across the entire organizational dataset.
Real-Time
Native support for high-speed, streaming analytics workloads over large datasets.
Cost-Effective
Cloud-based for scalability and computational power, bypassing expensive hardware upgrades.
Strategic planning and roadmapping
#1: Establish Strategic Objectives
Align on a long-term data strategy for organizational fitness and competitive advantage.
#2: Survey Data Maturity
Evaluate the current state of your organization’s data infrastructure, including data quality assurance, integration, governance, and analytics capabilities.
#3: Prioritize Critical Opportunities
Identify exactly where a data lakehouse will most impact your business challenges.
#4: Chart Your Roadmap
Get a phased approach for implementation and system interoperability to achieve ROI.
Data Lake architecture development
Here’s how we enable your organization to harness and analyze data faster.
- Ingestion: Collecting raw data from structured, semi-structured, and unstructured sources and bringing it into your data lake via batch or real-time pipelines.
- Storage: Storing data in a scalable storage layer, preserving the original structure for efficient, cost-effective retention.
- Processing & Transformation: Cleaning, transforming, and standardizing data for analytics and downstream applications.
- Governance & Metadata Management: Capturing and managing the metadata necessary for discoverability, trackability, and security.
- Consumption & Analytics: Making data more accessible for querying, analytics, and machine learning via custom interfaces and tools, ensuring system interoperability with your existing infrastructure.
Data engineering capabilities, tools & technologies
Ready to optimize your data pipeline?
Let's talk about how we can make your data more powerful and accessible
