New Course by John Singer

Data parsing, standardization, matching, and de-duplication are the cornerstones of successful Master Data Management (MDM). They are also critical parts of successful data quality programs, and are key steps in building data warehouses as well as any data integration and consolidation initiatives. Today, few organizations can function effectively without implementing data parsing and matching processes, often in many data domains.

This need is further magnified if your company has gone global and plans to create databases that combine name- and address-related data from all corners of the world. Worldwide there are more than 10,000 languages, 130 address formats, at least 36 personal and hundreds of business name formats. All of these variables are further complicated by the need to respect national and regional cultures. Failure to consider formats, styles, and cultures has huge impact on quality of data and quality of business relationships.

Entity Relationship modeling and relational databases have dominated the IT scene since the '80s, becoming the de facto standard approach for data persistence. However, the ubiquitous relational database has waned with the advent of NoSQL and big data technologies. Today’s data architect must master a new database technology – graph database – that has emerged with a solid set of use cases based on mathematical graph theory and graph algorithms.

This 4-hour online course will provide an overview of property graph database technology and teach the student how to translate business requirements to a property graph database design that can be implemented on any modern property graph database.

You will learn to:

• To understand property graphs as a new database model<\li>
• To compare and contrast property graphs with other database models<\li>
• To understand how a graph database fits into the overall data ecosystem<\li>
• How to properly design a property graph data model<\li>
• Property Graph database modeling and design best practices for entity definition, relationship definition, and modeling complex objects<\li>

Get CIMP Certified!

eLearningCurve offers a robust certification program, Certified Information Management Professional (CIMP), that builds upon education to certify knowledge and understanding of information management. CIMP is offered in the following tracks:

• Information Management Foundations
• Data Quality
• Data Governance
• Data Integration
• Master Data Management
• Data Modeling & Metadata
• Business Intelligence & Analytics
• Data Science

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