There is a perfect storm brewing: organizations are amassing large volumes of multi-structured data, yet there are few cost-effective ways to analyze this data without data scientists, who seems to be as elusive as a white unicorn. Although there are higher level languages on the horizon, like Hive and Pig, that promise to give mere mortals access to Hadoop-bound data, there is an easier approach that some may consider old school: search technology.
Think about it: search tools can index both structured and unstructured data and thanks to new add-ons, such as Hadoop integration, natural language processing, columnar databases, simple query languages, and visualization interfaces, they can also handle many analytical tasks.
In this podcast, you will learn:
- The value of using search to perform analytics
- The marriage of search and big data
- The technology that powers search-enabled analytics
- Use cases for search-enabled analytics