ISM-Reading, Inc.

Are you ready to expand your network and make meaningful connections? Our virtual speed networking event is the perfect opportunity to meet new people within our growing membership community. In just one hour, you'll have the chance to engage in dynamic, one-on-one conversations with fellow members, exchange ideas, and build valuable relationships. Whether you're looking to collaborate, share insights, or simply make new friends, this is your networking power hour!

Don't miss out on this fun and interactive experience. Come prepared to connect, converse, and create lasting connections.

Join ISM-Reading at Crossroads Route 61 Restaurant for an evening of learning and discussion. Jared Pummer will host a Review of the Top Supply Risks of 2024- A Retrospective look at what happened. This event is held at no charge for Chapter Members, and dinner is included! Come out and meet your fellow chapter members, share a meal, and enjoy the presentation! Please RSVP by Friday, 12/6 so we can notify CrossRoads of how many to expect. This event is offered as an in-person event to allow for networking and discussion. In addition to the talk, we will review Chapter news, Events, and direction for 2025.

Location: CrossRoads Route 61: 4643 Pottsville Pike, Reading PA 19605

We all think we know what bad data looks like, but what is it and what are the consequences?

I bet you never knew you needed a COAT for your data, but it will help protect you against all the dirty data that's around. Susan will share real-life examples of dirty data, and the consequences it has on the output, such as decision making, reporting, analytics, AI, and machine learning. She'll also share with you her COAT methodology to help prevent this, as well as learn how to make quick, accurate checks and changes to your own data in excel, regardless of your level of experience, and explain why data accuracy and maintenance is so important and implement best practices for this.

Takeaways:

• The importance of data accuracy
• The consequences of dirty data
• How to ensure data accuracy
• Make sure your data has its COAT on
• How to spot check your data