Overall spending on Artificial Intelligence (AI) systems is projected to reach $79.2 billion in 2022, which is more than double the amount spent in 2019.
Just like most industries, banking and finance have forever changed due to the explosion of big data and the infrastructure required for processing such data.
Data-driven organizations understand that their data is a strategic asset and to properly harness its power it must be supported by a sophisticated data strategy.
Many c-suite executives are perplexed at the amount of money their organizations spend implementing and integrating data and software applications with limited evidence that they will even align with desired business outcomes.
Master Data Management (MDM) allows you to manage data assets better. MDM’s goal is to implement best practices that will help you optimize the management of your organization’s data assets.
Today, many organizations have numerous applications and systems in which data, spanning multiple departments, quickly becomes fragmented, duplicated, and even outdated.
A well-known issue with legacy data platforms is what’s known as the garbage in, garbage out (GIGO) obstacle. As data began to flourish due to cheap storage options and increased digitization, data quality issues and fragmentation proliferated, creating GIGO issues that affected an organization’s business intelligence.
To progress to a future state of mature Data Governance and analytical capability, decision-makers should focus on starting with the integration of the data across an entire enterprise. A Data Governance program will be critical to support the continued growth of an organization.
Data is at the center of People, Process, and Technology, representing a crucial asset used by all three. Simply put, people should embed data in any project to ensure that organizations follow a defined road map around enterprise data governance; technology can also help enhance and automate several processes and transactions.