What is big data?
The concept of “big data” stems from the ever-increasing size and quantity of data sets today, and the pace at which they are being generated.
With the growth of the cloud, organizations of all sizes and industries are producing more data than ever—even up to terabytes per second. Hidden in this data are insights with potential business value. The challenge lies in organizing and analyzing the data to create new business strategies and make organizational decisions.
Until recently, the most prevalent tools for organizing and analyzing data were relational database management systems (RDBMS) leveraging Structured Query Language (SQL). SQL solutions use structured data sets, typically stored and manipulated on a single server. When the size of the data set increases to the capacity ceiling of the existing server, the solution has to “scale up” by moving to a larger server with higher processing power and more storage and RAM capacity. Scaling up like this can be time-consuming and lead to a substantial rise in cost.
Naturally, with data now arriving quickly, from many different sources, and in myriad schemas, database administrators find the need to maximize the efficiency and scalability of their solution. The industry has begun shifting to NoSQL (Not Only SQL) databases which use non-relational and unstructured data sets. This allows data to be stored across multiple systems, enabling NoSQL applications to “scale out” through the incremental addition of commodity systems, achieving on-demand capacity growth and higher cost effectiveness.
In addition to database models for manipulating and processing data, the architecture and size of big data sets present particular infrastructure requirements including:
- Storage to accommodate the sheer size of the data itself
- RAM to load as much data as needed at one time
- Processing power commensurate with the level of performance required from the solution
- Network capable of connecting distributed data stores with low latency to enhance performance
From infrastructure solutions to processing and manipulating data sets, the big data revolution is just beginning. Its insights can transform the way business is done. Is your business poised to take advantage of big data opportunities?
The Four Vs of Big Data
The size and number of sources generating huge data sets are orders of magnitude larger than data managed in traditional storage and analytical solutions. Think in terms of petabytes instead of terabytes.
Large volumes of structured and unstructured data generated in myriad forms including email, social media, video, images, weather data, blogs, data, Web search histories, and much more.
Data is generated in a constant stream with real time queries for meaningful information to be served up on demand rather than batched.
Meaningful insights derived from big data that go beyond the results of traditional intelligence querying and reporting. These insights can be transformed into predictive analytics for trends and patterns.