Deploy ETL Process
- Scalable ETL pipelines are designed and implemented to automate the extraction, transformation, and loading of data across systems, ensuring data integrity and performance.
Transform Your Data
Our Process
At Futurety, we don’t just manage data—we engineer it to work smarter for you. Our process starts with understanding the full scope of your data needs, from collection to storage and analysis. Then, we build custom pipelines that streamline data flow, integrate diverse sources, and ensure everything is scalable and secure. Whether it’s cleaning, transforming, or organizing data for optimal use, we create a seamless system that powers your decisions.
Warehouse Implementation
Design and architect data warehouses tailored to your organization’s specific needs, considering scalability, performance requirements, and use cases.
Learn MoreSource Integration
Develop connections to various data sources, including relational databases (SQL Server, MySQL) and cloud data warehouses (BigQuery, Redshift, Snowflake).
Learn MoreData Archiving
Implement data archiving solutions to move historical data to a safe and secure storage environment.
Learn More
Warehouse Implementation
Data Cleaning
- Data is normalized and standardized, with duplicates removed to ensure consistency and high quality.
- Predefined rules or machine learning models are applied to detect, correct, and validate errors in the data.
Automated Data Ingestion
- Automated processes are developed to extract data from diverse sources and enable real-time or near-real-time data ingestion.
- Data ingestion schedules are automated, and flexible, scalable processes are built to adapt to new data sources and growing volumes.
Source Integration
Define Integration Strategy
- Identify key data sources and their specific requirements for integration.
- Develop a tailored plan that aligns with business goals and technical needs.
Automate Workflows
- Leverage tools and technologies to minimize manual intervention.
- Ensure workflows are scalable and adaptable to changing data needs.
Connect Data Sources
- Establish secure and reliable data pipelines for consistent performance.
- Optimize connections to reduce latency and enhance data accessibility.
Data Archiving
Tool Selection
- Evaluate business and technical requirements to recommend tools that align with scalability, security, and integration needs. Conduct technology audits to identify gaps and suggest improvements or tool replacements.
ERD Strategy
- Design custom ERD models that reflect business processes and data flows to ensure alignment with organizational needs. Standardize data models to make them scalable and adaptable to future growth.
Data Ingestion Strategy
- Design scalable ingestion pipelines that can handle growing data volumes while maintaining efficiency and reliability. Implement automation to reduce manual intervention and streamline data transfers.
Case Study
How a Midwest Health System Transformed Patient and Web Data into Action
The Client is an integrated, not-for-profit healthcare organization in the Midwest. The health system operates over 40+ medical centers and 250+ locations, including acute care hospitals, destination facilities for complex cancer and orthopedics and sports medicine care, behavioral health facilities, and numerous primary and urgent care centers.
The Client’s marketing team came to us with a complex set of needs regarding data engineering and data visualization. The Futurety team worked to create web scorecards to visualize service line and location performance over time integrating various sources, including GA4, MyChart, call tracking, and other healthcare platforms.
Ready to Enhance Your Data?
Whether you’re a startup or an established brand, we’re here to help you grow.
Frequently Asked Questions
How do you ensure the security and compliance of my data?
We implement industry-standard security protocols, such as data encryption, secure access controls, and regular backups, to ensure your data is protected at all stages. We also stay up to date with compliance regulations like GDPR or HIPAA, so you can trust that your data is not only safe but also compliant with relevant laws and industry standards.
Why is archiving data important?
Data archiving is the process of securely storing historical or less frequently used data in a way that makes it accessible when needed. It’s important because it helps optimize the performance of your active systems while ensuring compliance and maintaining access to valuable historical data for audits, reporting, or long-term analysis.
How can Data warehouse implementation benefit my business?
Data warehouse implementation involves creating a centralized repository where all your business data is stored, organized, and optimized for reporting and analysis. By integrating data from different sources into one place, you can make more informed decisions faster, improve data quality, and eliminate data silos across departments.
How do you handle data source integration?
We connect and integrate data from various sources—such as CRM systems, ERP platforms, social media, and more—into a seamless, unified system. Our team ensures that data flows smoothly, is properly mapped, and is consistent, making it easier for your team to access and use for analysis or reporting.
