Semantic Data Modeling
Data-driven analytics is at the core of global businesses today. But any good data analytics strategy requires a capacity to quickly obtain valuable insights from large amounts of data coming from diverse data sources.
How You’ll Benefit
Take a business-first approach
Move from data-centric to knowledge-centric decision making for your business.
Adopt continuous data modeling, ingestion and reconciliation
Harmonize your data in an overall semantic model that allows easy extension in time.
Employ efficient data integration and governance
Open new avenues of looking at enterprise data and making use of it.
Use Linked Data enrichment and sharing
Refine your knowledge and make information easy to find, share and reuse.
Transform your data into knowledge
Fuel better business outcomes based on data-driven insights.
Semantic Data Models:
- Capture the “meaning” of your data with all its inherent relationships in a single enterprise Knowledge Graph for your entire organization;
- Allow your data model to evolve at the pace of your business demands so you can include additional business requirements, data sources and other models;
- Make your data more accessible to data scientists and business analysts by granting a unified access to knowledge from multiple sources;
- Provide the ability to query the data and ask questions that you haven’t anticipated while modeling your data;
- translate your data into usable information consumable for decision-making purposes.
Service Description
Take a business-first approach
- Benefit from the freedom and rapid implementation speed of an evolving knowledge-centric architecture that exists independently of vendor requirements.
- Empower your business people to work with a more intuitive data model that organizes data by real world concepts and the relationships between them.
- Ensure the alignment, consistency and compliance of your business processes by creating one single master reference source for all critical enterprise data.
Employ efficient data integration and governance
- Deploy semantic data modeling as a layer to your knowledge-centric architecture by integrating your enterprise data virtually while keeping your existing legacy systems.
- Take advantage of adopting a unified access point to all your data by integrating both structured and unstructured data.
- Outline critical turning points and risk mitigation steps by employing transparent processes and procedures for data updates and schema changes.
Transform your data into knowledge
- Discover new relationships and patterns hidden in your semantically enriched business knowledge.
- Extract more powerful and more relevant insights from your Big Data analytics by putting your information into context and drawing new conclusions from it.
- Benefit from predictive models and data-backed decision support systems that have access to untapped business intelligence.
Adopt continuous data modeling, ingestion and reconciliation
- Adopt an effective conceptual framework (ontology) that captures the questions your data should be able to answer and makes use of proven industry standard models.
- Capitalize on intuitive and powerful Extract, Transform and Load (ETL) tools and processes (incl. Ontotext Refine), optimized to decode the “meaning” of your data and describe it in a neat semantic model.
- Unearth interesting identity matches and non-apparent relationships across multiple datasets by using the semantics of your data.
Use Linked Data enrichment and sharing
- Harness powerful new opportunities that arise from putting your competitive edge proprietary knowledge in the context of open world knowledge and/or commercially specialized knowledge;
- Identify the advantages of interlinking your edge, core and cloud data;
- Benefit from a proven, easily scalable LD paradigm that allows your knowledge to grow together with your business in a constantly changing environment.
Interested in this Professional Service?
