How enabling data and AI at scale will transform your organization. A guide for CDOs, CIOs, CTOs, and enterprise architects Every organization is working to improve business outcomes while effectively managing a variety of risks — including economic, compliance, security and fraud, financial, reputation, operational and competitive risk. Your organization’s data and the systems that process it play a critical role in not only enabling your financial goals but also in minimizing these seven key business risks. Senior data leaders have realized that their legacy information technology platforms are not able to scale and meet the increasing demands for better data analytics.
As a result, they are looking to transform how their organizations use and process data. Successful data transformation initiatives involve not only the design of hardware and software systems but the alignment of people, processes, and culture. These initiatives always require a major financial investment and, therefore, need to yield a significant return on investment — that starts in months, not years.
Read this guide to learn about the 10 key considerations data and analytics leaders face when developing their data and AI strategy.