Author name: Szymon Zak

Insurance brokers waste resources and precious time on inefficient AMS data management. Their data teams spend countless hours in Agency Management Systems (like. Applied Epic and AMS360) limited by a gap in usability affecting throughput. Data administration problems compound silently until they surface at critical moments. A post-M&A Data Conversion project demands weeks of record […]

Messy, inconsistent data makes it hard to gain insights and make informed decisions. There are some normalization techniques and solutions you may already be considering. Software can help you standardize your data, correct inaccuracies, and add missing information, all while integrating data from multiple sources. But choosing and implementing the right solution requires understanding both technical

Larger businesses handle data across multiple systems, each built to serve distinct business functions. While basic data preprocessing focuses on cleaning and standardization, core business systems reality reveal deeper challenges that technical solutions alone cannot solve. Key takeaways: Using data preprocessing as a downstream replacement for data quality and standardization is asking for problems. Cleaning