Big Data Tendency Moving the face of Business
Machines data and the internet of things take center stage:
From Radio-Frequency Identification (RFID) tags and industrial equipment to jet engines and consumer electronics, the world around is generating ever increasing amounts of data. Companies are beginning to use that data to improve product drive efficiencies identity defects and enhance security.
- Compound applications that combine data sets to create value:
The new cornucopia of public and private data is providing a new opportunity to mash up multiple Big Data sets to gain new insight beyond what a single Big Data set allows.
- There’s an explosion of innovation built on open source Big Data tools:
From an open source core, companies are building an array of big data platform technologies, tools and components.
- Companies taking a proactive approach to identifying where Big Data can have an impact:
Many early Big Data projects were skunk work projects intended to prove the value of Big Data, but that’s changing.
- There are more actual production Big Data projects:
Test – bed projects have dominated the Big Data Industry for the past several years, but these days there are a lot more actual production projects. These projects are largely about achieving data scalability and cost containment, like building a data lake, but the innovators who got started early are beginning to turn their attention to leveraging their new analytic capabilities for business transformation.
- Large companies are increasingly turning to Big Data:
Large enterprises took to big data initiatives in a major way in 2012: 53% of 1217 large companies surveyed in a global study conducted by TCS undertook a Big Data Initiative that year.
- Most Companies spend very little; a few spend a lot:
Most companies are not spending on their Big Data initiatives, but some are investing heavily. TCS found that large companies undertaking big data initiatives are spending a median of $10.
The Biggest challenges are much cultural as technological:
The technological issue of dealing with the volume, velocity, and variety of data still ranks highly. But getting at the data in the first place takes precedence. Companies are also struggling with which data to use make better business decisions.