What is big data?
For most organizations, big data is the reality of doing business. It’s the proliferation of structured and
Imagine being able to analyze data to determine the root cause of failures. Or detect fraudulent behavior before it affects revenue. Implementing the right solutions to make the most of your big data from data management to analytics can be key to your business success.
Big Data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process the data within a tolerable elapsed time.
IDG published their latest big data enterprise survey and predictions for 2014 finding that on average, enterprises will spend $8M on big data –related initiatives in 2014.
The study also found that 70% of enterprise organizations have either deployed or are planning to deploy big data-related projects and programs. The study 2014 IDG Enterprise Big Data Research is summarized here. The goal of the study includes gaining a better understanding of organizations’ big data initiatives, investments and strategies.
IDG’s methodology includes interviews of 751 respondents randomly selected from CIO, Computerworld, CSO, InfoWorld, IT world, and Network World subscribers, e-mail subscription lists and LinkedIn forums. An online survey of 46 questions was used. To get the full study that includes a description of the methodology please contact IDG’s representatives listed on this page.
For purposes of the study, IDG defined big data as large volumes of a wide variety of data collected from various sources across the enterprise including transactional data from enterprise applications/databases, social media data, mobile device data, unstructured data/documents, machine-generated data and more.
Data analysis driving corporate spending "anyone who has experience in and around data is in a great spot right now. This includes the standard database developer, data engineers who structure data with Hadoop and data scientists who make sense of that information.
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.
The project includes these modules:
Hadoop Common: The common utilities that support the other Hadoop modules.
Hadoop Distributed File System (HDFS™): A distributed file system that provides high-throughput access to application data.
Hadoop YARN: A framework for job scheduling and cluster resource management.
Hadoop MapReduce: A YARN-based system for parallel processing of large data sets.