Big Data” is data whose scale, distribution, diversity and/or timeliness require the use of new technical architectures and analytics to enable insights that unlock new sources of business value.
a) Requires new data architecture
b) New tools
c) New analytical methods
d)Integrating multiple skills
Organizations are deriving business benefit from analysing ever larger and more complex data sets that increasingly require real-time or near-real time capabilities.There are multiple characteristics of big data, but 3 stand out as defining Characteristics:
Huge volume of data (for instance, tools that can manage billions of rows and billions of columns) • Complexity of data types and structures, with an increasing volume of unstructured data (80-90% of the data in existence is unstructured)….part of the Digital Shadow or “Data Exhaust” Speed or velocity of new data creation.
In addition, the data, due to its size or level of structure, cannot be efficiently analyzed using only traditional databases or methods. There are many examples of emerging big data opportunities and solutions. Here are a few: Netflix suggesting your next movie rental, dynamic monitoring of embedded sensors in bridges to detect real-time stresses and longer-term erosion, and retailers analyzing digital video streams to optimize product and display layouts and promotional spaces on a store-bystore basis are a few real examples of how big data is involved in our lives today. These kinds of big data problems require new tools/technologies to store, manage and realize the business benefit. The new architectures it necessitates are supported by new tools, processes and procedures that enable organizations to create, manipulate and manage these very large data sets and the storage environments that house them.