Webcast : ER/Studio Enterprise Team Edition

Data modelers should focus on telling a story because it helps in communicating insights and making data more understandable and actionable for the audience. Telling data stories combines data analysis with contextual narratives and visualizations, making it easier for users to understand complex information and make data-driven decisions. Data modelers should focus on telling a story to communicate insights, engage the audience, and facilitate data-driven decision-making.

The data story is important because:

• Contextualize data: By telling a story, data modelers can provide context to the data, helping users understand the relationships between unique data points and how significant the insights are.
• Capture the audience: A well-crafted narrative can get the attention of an audience and make the information more memorable, increasing the likelihood of users keeping and acting upon the insights.
• Facilitate decision-making: Data storytelling can help decision-makers understand the key insights from the data, enabling them to make informed decisions based on the presented information.
• Simplify complex information: Presenting data in a narrative format can make complex information more accessible to non-technical users, fostering a data-driven culture within the organization.

Can you read a data model as seamlessly as reading a book? Join us as we tell the cardinality story, explaining how to read the one, zero, and many symbols on our data models. We will also discuss subtyping, and weak and strong entities. You will not just be listening to Steve – this will be an interactive session. We will take a challenging yet fun quiz together which will reinforce your data modeling skills!

Speaker: Steve Hoberman has trained more than 10,000 people in data modeling since 1992. Steve is known for his entertaining and interactive teaching style (watch out for flying candy!), and organizations around the globe have brought Steve in to teach his Data Modeling Master Class, which is recognized as the most comprehensive data modeling course in the industry. Steve is the author of nine books on data modeling, including the bestseller Data Modeling Made Simple. One of Steve’s frequent data modeling consulting assignments is to review data models using his Data Model Scorecard® technique. He is the founder of the Design Challenges group, Conference Chair of the Data Modeling Zone conferences, and recipient of the Data Administration Management Association (DAMA) International Professional Achievement Award.

Experienced data modelers are important because they can create accurate, efficient, and maintainable data models that can improve decision-making and lead to cost savings for the organization:

• Accurate representation of business processes: Experienced data modelers have the ability to create data models that accurately represent the business processes. They have domain knowledge in the area they are modeling and can understand the complexities of the business requirements. This results in data models that accurately capture the relationships between data elements and how they are used in the business processes.
• Efficient database design: Experienced data modelers can design databases that are efficient and optimized for performance. They have knowledge of indexing strategies, normalization techniques, and other database design principles that can result in faster query execution times and better overall performance.
• Ease of maintenance: Experienced data modelers design data models that are easy to maintain. They understand the importance of data integrity and implement mechanisms to ensure data consistency and accuracy. This results in databases that are easy to update and maintain over time.
• Improved decision-making: Experienced data modelers create data models that can be used to make informed decisions. They can provide insights into the relationships between data elements and how they are used in the business processes. This can help stakeholders make better decisions and improve overall business performance.
• Cost savings: Experienced data modelers can design databases that are optimized for storage and processing. This can result in cost savings by reducing the need for additional hardware or software resources.