Summary: Everyone talks about how big data is the key to business success, but the process of getting value from big data is time intensive and complex. Examining the big data analytics workflow provides clues to getting to big data results faster.
Most organizations recognize that big data analytics is key to their future business success, but efforts to implement are often slowed due to operational procedures and workflow issues.
At the heart of the issue is the big data analytics workflow including loading, ingesting, manipulating, transforming, accessing, modeling and, finally, visualizing and analyzing data. Each step requires manual intervention by IT with a great amount of hand coding and tools that invite mistakes and delays. New technologies such as Hadoop and NoSQL databases also require specialized skills. Once the data is prepared, business users often have new requests to IT for additional data sources and the linear process begins again.
Given the potential problems that can crop up in managing and incorporating big data into decision-making processes, organizations need easy-to-use solutions that can address today’s challenges, with the flexibility to adapt to meet future challenges. These solutions require data integration with support for structured and unstructured data and tools for visualization and data exploration that support existing and new big data sources.
A single, unified business analytics platform with tightly coupled data integration and business analytics such as Pentaho Business Analytics is ideal. Pentaho supports the entire big data analytics flow with visual tools to simplify development and remove complexity for developers and powerful analytics to allow a broad set of users to easily access, visualize and explore big data. By dramatically improving developer productivity and offering significant performance advantages, Pentaho significantly reduces time to big data value.
- Donna Prlich Senior Director, Product and Solution Marketing, Pentaho
this blog originally appeared on GigaOM at http://gigaom.com/2012/12/06/how-to-reduce-complexity-and-get-to-big-dat...