Data Architecture Services
Build a Data Architecture Framework That Grows with You
In a rapidly changing data landscape, our expert data architecture consulting services turns complexity into clarity. Seamlessly integrating, securing, and transforming raw data into real-time insights for competitive advantage.
Building Scalable and High-Performance Data Architecture
Business-Specific
Custom data architectures tailored to your business needs for seamless operations and analysis with a focus on enterprise data architecture principles.
Scalable & High-Performance
Cloud-native data solutions are designed to scale effortlessly with growing business needs, incorporating modern data architecture standards and best practices.
Data Management
End-to-end data management from collection to advanced data analytics, data governance, and visualization, including database management for optimized performance.
Secure & Compliant
Industry-standard data security, compliance, and governance for safe and reliable data management at every layer of your data services architecture
Our Data Architecture Capabilities
Across Multiple Domains
Enterprise Data
Architecture Solutions
We design scalable, secure, and high-performance data architectures that ensure seamless data flow, secure storage, and high availability for enterprise applications.
AI-Driven Insights &
Real-Time Analytics
We integrate real-time data processing pipelines to deliver instant insights, enhancing decision-making with AI-powered dashboards and predictive analytics.
Centralized Data
Warehouses & Data Lakes
We create structured, scalable repositories that support advanced analytics, reporting, and business intelligence, ensuring data accuracy, accessibility, and performance.
Stryv’s Expertise in Scalable & Intelligent Data Architecture
Our Expertise
Data Integration & ETL
- Expertise in ETL/ELT Pipelines, Data Orchestration, Schema Mapping.
- Tools & Technologies include Apache NiFi, Talend, dbt, Apache Airflow, AWS Glue, Azure Data Factory.
- Seamless integration of structured & unstructured data from multiple sources.
- Automated ETL pipelines ensuring data accuracy and consistency.
- Batch & real-time data ingestion for optimized performance.
Cloud Data Architecture
- Expertise in Cloud-Native Solutions, Serverless Architectures, Multi-Cloud Deployments.
- Tools & Technologies include AWS Redshift, Google BigQuery, Snowflake, Azure Synapse, Databricks.
- Scalable & cost-effective cloud data platforms for high availability.
- Hybrid & multi-cloud architectures for flexibility and performance.
-
On-demand data access with seamless integration across cloud
services.
Real-Time Data Processing
- Expertise in Stream Processing, Event-Driven Architectures, AI-Driven Analytics.
- Tools & Technologies include Apache Kafka, Apache Flink, AWS Kinesis, Spark Streaming, Google Dataflow.
- High-speed event processing for real-time decision-making.
- Scalable data pipelines that process millions of events per second.
- AI/ML integration for predictive insights and anomaly detection.
Data Governance & Security
- Expertise in Compliance, Data Privacy, Access Management, Encryption.
- Tools & Technologies include Apache Ranger, AWS IAM, Azure Purview, Collibra, Informatica Axon.
- End-to-end data governance ensuring compliance with GDPR, HIPAA, SOC 2.
- Role-based access control (RBAC) and encryption for data security.
- Metadata management & auditing for transparency and accountability.
Our Data Architecture Case Studies
Automating Account Receivables for a Leading Services & Ratings Company
Challenge
Reduction of performance owing to compliance and data integrity concerns, hinderance of real-time reporting and decision-making by siloed data systems and delays and inaccuracies due to manual processing of account receivable files.
Solution
We audit the existing data workflows and design a smart ETL solution using Azure’s data integration services. Our approach includes consolidating data into a centralized data store for real-time analytics, automating file ingestion and processing with Azure Data Factory, and integrating validation and transformation steps with custom scripts to ensure data quality.
Result
After implementing our solutions, our clients experienced an improvement of real-time visibility and accuracy of account receivables, an enhancement of compliance through automated data validations, and a 40 percent reduction in processing time.
Data Accuracy
Operational Efficiency
Reduced Errors
Scalable Integration
Why Choose Stryv for Data Architecture Services?
Ensure a tailored, scalable, and secure solution designed to meet your unique business requirements with Stryv.ai. Our team specializes in creating AI-driven data pipelines and integrating advanced machine learning frameworks, providing real-time analytics and predictive insights that empower data-driven decisions. We design flexible systems that seamlessly integrate with existing infrastructure, ensuring minimal disruption and maximum performance. With a strong focus on security, compliance, and continuous optimization, we optimize data systems for growth and operational efficiency.
hether you’re looking to streamline your operations, enhance decision-making, or drive innovation, Stryv.ai is your trusted partner. We offer reliable, scalable, and intelligent data architecture solutions tailored to your industry and goals.
Frequently Asked Question's
Designing and implementation of a structured framework for storing, managing, integrating, and securing business data comes under data architecture services. These are crucial for enabling scalable operations, real-time analytics, data governance, and compliance across modern data ecosystems.
Modern data architecture typically includes data lakes or data warehouses, ETL/ELT pipelines, real-time data streaming, data governance frameworks, metadata management, and cloud-native platforms. It’s designed to be scalable, secure, and agile, supporting advanced analytics and AI applications.
Data integration allows organizations to combine data from multiple sources i.e., structured and unstructured into a unified system. This supports accurate analysis, reduces data silos, and improves decision-making by providing a single source of truth across business functions.
Data governance ensures that data is accurate, consistent, secure, and compliant with regulations. In a data architecture context, it involves policies, access controls, data lineage, and auditing practices that safeguard data quality and usage throughout its lifecycle.
A data warehouse stores structured data optimized for fast querying and reporting, while a data lake holds raw, unstructured, or semi-structured data for flexible analysis, including machine learning. Many organizations use both layered architectures to support diverse analytics needs.
Cloud computing enables scalable, cost-effective, and flexible data architecture. Cloud platforms offer services like managed databases, serverless computing, and storage, which support real-time analytics, AI integration, and cross-platform data access in hybrid or multi-cloud environments.
Best practices in designing a scalable data architecture includes defining clear data governance policies, using modular and loosely coupled components, implementing automated ETL/ELT processes, designing for both real-time and batch processing by prioritizing security and compliance at all layers
Get in touch, and let’s find the smartest way to move your project forward.
Learn more about Stryv’s innovative services, designed to offer a modern, secure, and customized experience tailored just for you.
General enquiries
info@stryv.ai
Talk to Our Experts
+1-904-310-4540
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