A large unstructured big volume data set; too complex to be handled by commonly used database management systems like RDBMS or DBMS is BIG Data. The size of the data stored in the world has exploded as it is constantly being gathered by various sources and these keep increasing too. The capacity of the world to store data doubles every two years. Everyday around two and a half exabytes of data is created.
That is BIG.
Big data uses statistical inference to determine regressions, nonlinear relationships and data dependencies from a large volume of data.
Sources of Data in Today’s World
Radio Frequency Identification (RFID)
Wireless Sensor Networks
Challenges for Big Data
Growth and Digitization of Global Information Storage Capacity itself is a challenge today. The challenges for BIG Data are divided into the three classical fronts.
The unceasing increase in the amount of data created everyday is overwhelming.
It can bring a long running software system to a standstill by sheer size and the inability to process in an acceptable time limit.
The speed of data in and out, the transactions and the analysis to be done as expected by the business could be in fact outdoing the speed of light itself.
If variety is the spice of life, here in the Big Data world it could very well be the reason for sleepless nights for the technology gurus.
To decipher the range of data types and sources itself is a challenge. Much later is the question of devising the methods to capture, curate and store these.
Once this is done comes the challenge to allow meaningful analysis, search and visualization of the data.
Big Data Rollout
The Big Data Systems can be implemented by following these steps to have a mature and meaningful data set.
Data Integration of structured and unstructured data
ETL / ELT / ETLT Design and Development
Interfacing legacy systems with the modern approach
Big Data Tools
The Big Data Toolkit consists of an impressive portfolio of tools.
Hadoop, a distributed file system
MapReduce, a framework for data abstractions
Hive for data summarization and adhoc queries
Pig for parallel processing
HBase, a structured storage for large tables
Sqoop for data integration of Hadoop with RDBMS
Flume for data transfers of log data to centralized data repositories
SPEC INDIA is a boutique ISO 9001:2008 certified software solutions company with 27+ years of consistent and sustained growth implementing critical business systems at Multi-location.
We provide end to end custom BIG Data solutions with assurance of easy availability and accessibility of real time business critical information at right time using both open source and license platforms. We offer simple proof of concepts or fully integrated solutions with Big Data architecture and solution design, Big Data Analytics, MongoDB and Hadoop setup and implementations.
Get more information about Apache Hadoop – Taking a Big Leap In Big Data
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