Structured Data Lake Offering
Companies have large numbers of disparate systems that produce data in all forms. The opportunity cost of ignoring this data is unknown but potentially strategic. The cost of warehousing this data into a BI solution is often prohibitive, especially for on-premise solutions. Traditional data stores, like NFS or SAN are expensive and inflexible. Hadoop solutions are difficult to manage. The trend towards data-driven business puts pressure on IT managers to do something, but the correct path is complex and has strategic implications.
Full 360 builds structured data lakes based on AWS S3. These are populated by reliable, scalable data producers that can provide every ETL transformation. Data management for any workstream can be dynamically scaled. Additionally, upstream and downstream data producers and consumers can be integrated into the application at minimal cost.
- Data Transparency
- Strategic Flexibility
- Higher Availability
- Improved Workflow Management
- Multiple Low Cost Tiers
- Broad Security Options
Timelines & Costs
Given sample data and access, the Full 360 team can create a preliminary design and build a working proof of concept in under three weeks. Following a solid assessment and meeting of key stakeholders and SMEs, the team can generally move very quickly based upon prior experience. Known areas of complexity like unstructured data needing custom parsing are costed via a Fibonacci scale.
Customers We Serve
- Customers who application-specific data warehouses and/or business intelligence infrastructure.
- Customers looking to save money on ETL software.
- Customers with large Storage Area Networks in the terabyte and petabyte range looking for less expensive data storage.
- Customers with many complex data inputs but are not yet ready to initiate DW projects.
- Legacy Hadoop customers looking to simplify or migrate.
- Customers needing to mix or combine batch, streaming and API-based data sources.