Data, data and more data – data is growing faster than ever. According to Gartner, a leading IT analyst firm, there will be nearly 3 billion people online that together will be pushing the amount of shared data to nearly 8 zettabytes by the year 2015. If you do not know what a Zettabyte is, look at the table below.
- 1,000 Megabytes = 1 Gigabyte
- 1,000 Gigabytes = 1 Terabyte
- 1,000 Terabytes = 1 Petabyte
- 1,000 Petabytes = 1 Exabyte
- 1,000 Exabytes = 1 Zettabyte
- 1,000 Zettabytes = 1 Yottabyte
- 1,000 Yottabytes = 1 Brontobyte
This represents huge growth! Globally, we are estimated to have 1.8 Zettabyes of data at the end of 2011; this represents a 45% annual growth rate. Video is fastest growing file type and expected to account for 50% of all internet traffic by the end of 2012. Let’s look at some examples of this explosive growth.
- 30 billion pieces of content were added to Facebook during the past month by 600 million plus users.
- Zynga processes 1 petabyte of content for players every day, a volume of data that is unmatched in the social game industry.
- More than 2 billion videos were watched on YouTube … yesterday.
- The average teenager sends 4,762 text messages per month.
- 32 billion searches were performed last month … on Twitter.
- Worldwide IP traffic will quadruple by 2015 (Cloud is a big driver for this;
According to Gartner, this demand for data will have a significant impact on enterprise data centers between now and 2015.
- The number of physical and virtual server will increase by 10 times.
- The amount of information managed by enterprise data centers will increase by 50 times
The increase in the amount of data moving through data centers will increase by 75 times
The term “Big Data” originated from the open source community, where there was an effort to develop analytics processes that were faster and more scalable than traditional data warehousing and could extract value from the vast amounts of unstructured data produced daily by web users. However, the term Big Data is now a source of confusion for many users as vendors put forth their own unique and often conflicting definitions of the term. The most common source of confusion results from the conflation of Big Data Storage with Big Data Analytics.
Big Data storage aims to address the vast amounts of unstructured data that is fueling enterprise data storage growth. Most technologies underpinning Big Data Storage such as scale-out NAS and object-based storage have existed for a number of years and are relatively well understood. However, may enterprises are beginning to look at new emerging technologies such as in-line deduplication, automated tiering of data to get the most efficient usage patterns, and flash or solid-state drives for higher-end performance to manage the large influx of data.
Big Data Analytics is more emergent and less understood by the IT community. The web historically drove development of Big Data analytics processes. However, all major vertical industry segments are now seeing the rapid growth of Big Data analytics applications. The factors below are driving the demand for Big Data analytics.
- The need to converge data from multiple structured and unstructured data sources.
- The need to analyze large amounts of external data such as social media information.
- The need to extract data from new data sources such as mobile devices, RFID, the web, and a growing list of automated sensory technologies.
- The realization that time to information is critical to extract value from the data.
- The perception that traditional data warehousing processes are too slow and limited in scalability.
Gartner lists Big Data as number two of its top ten strategic technology trends for 2012. According to Gartner, unstructured data will grow some 80% over the course of the next five years, creating a huge challenge for IT.
Enfocus Solutions Inc. believes that many organizations will need to face these issues in the coming years and should start planning now. A good set of requirements will be needed to help organizations evaluate and select appropriate technologies to fit their needs. Enfocus Solutions is developing a set of requirements that organizations can use to get a quick start in initiating a Big Data project. Example requirements such as these are available as part of our subscription offering in the Requirement Coach,™ one of the components of the Enfocus Requirement Suite.™ To find out more, please download our product fact sheet below.