Big Data – The Emerging Technology Trend

Big Data is the exponentially growing streams of data, which needs to be processed with the help of new technologies and techniques, to bring enterprise-wide visibility and insights to make quick critical business decisions.

To explain it in very simple terms – Huge amounts of Data need to be processed at the right time to help businesses make critical decisions. This exponentially huge amount of Data is Big Data.

Big Data
Image source:: FreeDigitalPhotos

How did Big Data come into play?

Companies for decades have relied on transactional data stored in relational databases. Mining into information or data beyond this critical data i.e. into the non-conventional, less-structured data like weblogs, social media, emails and photographs, has helped discover a hidden treasure. This data treasure requires high-speed analytics using advanced cloud integration services to complement the pre-existing information management systems and programs that companies already have in place.

What does Big Data include?

Big Data typically refers to the following types of data:

  • Traditional enterprise data– this type of data is the typical data received like transactional ERP data, customer information from CRM systems, online- store transactions and general ledger data.
  • Machine-generated/sensor data– this type of data is usually collected from places like weblogs, Call Detail Records (‘CDR’), smart meters, manufacturing sensors, trading systems data and equipment logs or digital exhaust.
  • Social data– this type of data is collected from social interactions like customer feedback streams, micro-blogging sites like twitter or from social platforms like Facebook, LinkedIn.

 

The McKinsey Global Institute forecasts the increase in Data volume as 40% per year. Although the volume of Data is a key indicator to predict the extent of growth for the Big Data, it is not the only indicator. The 4 characteristics that help define Big Data in true sense are:

  1. Volume – Machine- generated data is produced at an exponential rate when compared to non-traditional data. With the capacity to produce over 10TB of data in less than 30 minutes, Smart meters and heavy industrial equipment like oil refineries and drilling rigs produce data in petabytes on a daily basis.
  2. Velocity – Although social media doesn’t generate the volume of data that the machine generates, it does create a large pool of data in a very short time with opinions and responses that are very valuable for better customer relationship management.
  3. Variety – Traditional data formats were very well structured and defined, but the new non-traditional data formats change sporadically. New marketing campaigns are launched, new sensors placed, new services added – all these require different data types.
  4. Value – The value of different types of data varies to a great extent. Typically there always lies, very valuable data hidden within the larger body of the non-traditional data. To identify and extract this data for analysis is a challenge.

 

Enterprises must evolve their IT infrastructures to handle the extreme volume of data received at very rapid rates with varying data types. This must then be well integrated with the organization’s other enterprise data to be accurately analyzed.

This is our attempt to provide an easy-to-read summary of the original Oracle Whitepaper on Big Data.

Compiled by M.Sah

Learn more about how Cloud Development Services can help you organization take advantage of the Big Data. Contact us or call us on 1-877-RISHABH (1-877-747-4224).

  • BI Expert

    This is a simple copy paste of Oracle whitepaper on big data. Where is the originality?

    Bad example of showing your domain expertise.

  • K. Shah

    Hello BI Expert,
    Thank you for pointing out our mistake! We forgot to reference the Oracle whitepaper from which we have tried to provide a summary in simpler words. This is just our attempt to spread useful information on this trending topic. We do not intend to take away any credit from the original Whitepaper. We’ve updated our blog and given due credit to the real authors. We apologize for our mistake in not doing so earlier.

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