USE CASE
Leverage FIBO in SQL for Seamless Financial Data Governance
Timbr’s SQL ontologies simplify and democratize FIBO implementation by allowing organizations to integrate legacy data assets into FIBO’s semantic framework.
This approach enables intuitive querying, seamless interoperability, and compliance, leveraging existing infrastructure without requiring extensive technical expertise or data transformation.
FIBO USE CASE TEMPLATE
Timbr Github repository contains a collection of SQL ontology-based semantic data models. These ontologies serve as customizable templates, designed to help users jump-start their modeling process tailored to their specific business domains.
USE CASE ONTOLOGY MODEL
The ontology semantic model makes it easy to understand and find data across tables and datasets. Timbr speeds up data discoverability by displaying data as a network and in a business-friendly manner.
Challenges
Facing Technical Challenges to Integrate FIBO data?
Transforming data from diverse data sources into the graph format used by FIBO OWL ontology is a significant challenge. Financial data often originates from various systems with different structures, terminologies, and formats. Ensuring accurate and consistent mapping to FIBO requires advanced tools and techniques to bridge the gap between disparate datasets and the OWL ontology.
Inconsistent Data Formats and Naming Conventions Across Systems?
Inconsistent data formats and quality across systems complicate FIBO adoption. Variations in naming conventions, metadata, and definitions hinder seamless integration into the FIBO framework. Addressing these inconsistencies requires robust data standardization and validation processes to align with FIBO’s precise semantic definitions and ensure meaningful insights.
Technical Complexity and Detachment from Data Ecosystem?
The complexity of learning and using SPARQL queries present a significant challenge in implementing FIBO. Many organizations lack the specialized skills needed to work with SPARQL, creating barriers to adoption. Additionally, traditional querying methods struggle to scale effectively across large, interconnected datasets, making it difficult to achieve high-performance semantic integration while maintaining governance and compliance. SPARQL also presents a significant challenge for FIBO consumption by the common BI tools.
Why Timbr
Simplified FIBO Implementation
Timbr leverages SQL ontologies that allow financial institutions to work with FIBO using familiar SQL syntax rather than OWL. This approach significantly reduces the learning curve and removes the need for specialized skills. By aligning with tools and expertise that data teams already possess, Timbr simplifies the technical challenges of semantic integration.
Virtualization to Integrate Fragmented Data Sources
Timbr’s virtualization technology enables a unified, virtual view of data across disparate sources without requiring physical data consolidation. This capability aligns fragmented datasets with FIBO in real time, ensuring consistency and enabling seamless access. Timbr eliminates the need for costly and time-consuming data migrations while maintaining the integrity of existing systems.
Democratized Consumption and Seamless Integration with BI Tools
Timbr allows semantic queries directly in SQL, offering an intuitive alternative to SPARQL. This SQL-first approach ensures that complex queries are accessible to teams with standard database skills. Timbr also seamlessly connects with BI tools like PowerBI and Tableau, making data accessible across platforms.
Impact
Faster, Easier Implementation and Maintenance
The SQL familiarity accelerates the implementation of FIBO, reduces the cost of training, and empowers data teams to quickly adopt and operationalize the ontology. Organizations can seamlessly map their legacy data to FIBO, ensuring faster time-to-value and greater efficiency in aligning data with standardized financial concepts.
Cost-effective Integration
By virtually integrating data, financial institutions can reduce implementation costs and streamline compliance processes. Timbr makes it possible to harmonize data from multiple systems into a FIBO-aligned structure, unlocking valuable insights without disrupting workflows or investing heavily in infrastructure changes.
Leverage Organizational Know-how
By enabling SQL-based semantic querying, Timbr democratizes access to FIBO’s full potential. Organizations can execute powerful, scalable queries across interconnected datasets while maintaining governance and performance. This leads to more actionable insights, improved analytics capabilities, and seamless integration with existing business intelligence workflows.
