The role of data analytics in the finance industry is profound and growing with each passing year. With data science, machine learning, and modeling, data analytics professionals can use these tools for organizations to minimize risk and create more efficient and profitable decisions based on fact rather than fiction. Data analytics adoption in enterprises raised from 17% in 2015 to 59% in 2018, reaching a compound annual growth rate of 36%. The need to eliminate risk and predict market trends has always been the goal of financial professionals on behalf of their companies or clients. Data analytics can even detect fraud or mismanagement of resources to reduce the likelihood of audits, operational shutdowns, or criminal activity. While this can create incredible returns when it’s used properly and well, there are several challenges that companies can face to implement these technologies in their workflow. Mentioned below are a few common challenges finance companies face while adopting BI platforms.