If data integration isn’t handled well, businesses can end up with data silos—where important information is stuck in one place and can’t be accessed by those who need it. This can lead to inconsistencies, making it difficult to trust the data used for decision-making. This blog post discusses common integration challenges that can hamper your business efficiency. Also, we will be shedding light on solutions for the challenges. 1. Data Quality Issues When data from different sources comes in varying formats, with missing values, duplicates, or inaccuracies, it can lead to unreliable insights. Poor data quality not only hampers decision-making but also erodes trust in the data. If left unchecked, these issues can propagate through systems, leading to widespread errors in reporting and analysis. To address data quality issues, businesses should implement rigorous data cleansing processes that standardize formats, remove duplicates, and fill in missing values. Additionally, setting up aut