Many organizations have deployed Hadoop to gain additional value from big data. Most envisioned they could use Hadoop to easily combine and analyze large data sets to identify new market opportunities or better detect fraud. However, combining data sets within Hadoop is easier said than done. Most organizations, thus far, have faced obstacles and failed to achieve estimated return on investment from their Hadoop deployments.
Organizations can easily use Hadoop to process or model larger volumes of data from single sources. However, companies experience challenges when attempting to combine and analyze different data sources due to their varied structures, making connecting and mapping them together extremely difficult. Even data from a company’s internal accounts and systems may include multiple account numbers for the same customers, and the problems become even more complex when an organization makes acquisitions or merges with other companies.
Register or login for access to this item and much more
All Information Management content is archived after seven days.
Community members receive:
- All recent and archived articles
- Conference offers and updates
- A full menu of enewsletter options
- Web seminars, white papers, ebooks
Already have an account? Log In
Don't have an account? Register for Free Unlimited Access