Data is the “oil” for all digital transformation initiatives including big data analytics, AI, Machine Learning, and more. Many of these initiatives intend to relentlessly improve customers’ experience with your business. However, failure can occur when computing with inaccurate data resulting in lower ROI, costly overruns, decreased productivity, and loss of trust. IT executives, business managers, and knowledge workers all have a shared responsibility to implement the best processes and technology to eradicate bad data. The negative impact of data inaccuracy can be widespread throughout organizations.
Companies are now able to cut unnecessary infrastructure purchases by nearly 50%, by avoiding processing duplicate or incorrect data.
Top 3 Challenges
Many companies have searched for decades for accurate data in order to be able to provide key information for making board-level decisions. Some of the areas for which accurate information is needed include where to launch new products and how to keep repeat customers and maintain or expand market presence. If the data is inaccurate, these decisions can, in many cases, make or break a company.