Big Data & Characteristics of Big Data V3s
Big Data may well be the Next Big Thing in the IT world.
Big data burst upon the scene in the first decade of the 21st century.
The first organizations to embrace it were online and startup firms. Firms like Google, eBay, LinkedIn, and Facebook were built around big data from the beginning.
Like many new information technologies, big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings.
‘Big Data’ is similar to ‘small data’, but bigger in size
But having data bigger it requires different approaches: Techniques, tools and architecture
An aim to solve new problems or old problems in a better way
Big Data generates value from the storage and processing of very large quantities of digital information that cannot be analyzed with traditional computing techniques.
Example of Big Data
Walmart handles more than 1 million customer transactions every hour. o Facebook handles 40 billion photos from its user base.
Decoding the human genome originally took 10 years to process; now it can be achieved in one week.
Twitter generates 7TB of data daily. o IBM claims 90% of today’s stored data was generated in just the last two years.
How Is Big Data Different?
Automatically generated by a machine (e.g. Sensor embedded in an engine)
Typically, an entirely new source of data (e.g. Use of the internet)
Not designed to be friendly (e.g. Text streams)
May not have much values need to focus on the important part
A typical PC might have had 10 gigabytes of storage in 2000. o Today, Facebook ingests 500 terabytes of new data every day. o Boeing 737 will generate 240 terabytes of flight data during a single flight across the US.
Moreoveer, The smartphones, the data they create and consume; sensors embedded into everyday objects will soon result in billions of new, constantly-updated data feeds containing environmental, location, and other information, including video.
Clickstreams and ad impressions capture user behavior at millions of events per second o High-frequency stock trading algorithms reflect market changes within microseconds o Machine to machine processes exchange data between billions of devices o Infrastructure and sensors generate massive log data in real-time
Moreover, On-line gaming systems support millions of concurrent users, each producing multiple inputs per second.
Big Datas isn’t just numbers, dates, and strings. Big Data is also geospatial data, 3D data, audio and video, and unstructured text, including log files and social media.
Moreover, Traditional database systems were designed to address smaller volumes of structured data, fewer updates or a predictable, consistent data structure.
Also, Big Data analysis includes different types of data
Benefits of Big Data
Real-time big data isn’t just a process for storing petabytes or Exabyte of data in a data warehouse, it’s about the ability to make better decisions and take meaningful actions at the right time.
Fast forward to the present and technologies like Hadoop give you the scale and flexibility to store data before you know how you are going to process it.
Moreover, Technologies such as MapReduce, Hive and Impala enable you to run queries without changing the data structures underneath.
Now newest research finds that organizations are using big data to target customer-centric outcomes, tap into internal data and build a better information ecosystem.
Big Datas are already an important part of the $64 billion database and data analytics market.
Also, It offers commercial opportunities of a comparable scale to enterprise software in the late 1980s and the Internet boom of the 1990s, and the social media explosion of today.
Application of Big Data Analytics
Leading Technology Vendors
IBM – Netezza
EMC – Greenplum
Oracle – Exadata