Understanding, modeling, and communicating both existing and future data is critical to successful business decisions. Business Data Modelers are the bridge to helping the business understand the value of their data. But what happens when a business can’t find a Business Modeler to delve into, document, and clearly communicate the business’s needs? How can a strong analyst be built into a business data modeler expeditiously? How can a mentor/trainer help prioritize what knowledge is most important to learn and build proficiency in less than a month?

Discover how our custom training built a proficient Business Data Modeler in three weeks to meet our client’s near-term business objectives and continued to expand to meet longer-term goals; learn how you can do the same for your business.

Learning Objectives:

• How to adapt: Flexibility is a core requirement in every situation. The best-made plans can always be upended.
• Build strong relationships: This foundation will provide opportunities for creative problem-solving.
• Avoid getting stale: Continue to update based on past experience.

Speaker: Laurel English Sturges

Laurel Sturges, a seasoned data professional, has been an integral part of the tech community, helping businesses better understand and utilize data for over 35 years. She refers to problem-solving as an adventure where she really finds passion in the process of discussing and defining data, getting into all the details, including metadata, definitions, business rules, and everything that goes along with it. Laurel is an expert in creating and delivering quality business data models and increasing communication between key business stakeholders and IT groups. She provides guidance for clients to make informed decisions so her partners can build a quality foundation for success. She has a diverse background serving in a multitude of roles educating individuals as a peer and as an external advisor. She has served in many industries, like manufacturing, healthcare, and banking. Her specialization is relational data theory and the usage of multiple modeling tools.