Big data analyzes the data that leads to better decisions and smooth business moves. In an usual word “Big data” is a term that describes the vast amount of data; it may be structured or unstructured. A large volume of unstructured data inundates a business on a day-to-day. Big data training is all about collection of data in a synchronized way for smooth and proper business moves.
Big Data History and Current Attentions
While the word “Big Data” is somewhat new, the process of gathering and storing large amounts of informative data for concluding analysis is ages old. The big data concept gained in the early 2000s when industry expert Doug Laney expressed the now-mainstream explanation of big data using the three Vs:
Volume: - Industries collect data from different sources of information, including day to day business transactions, social media and from sensor or machine-to-machine data. Before this technique, storing these data would’ve been a problematic – but new technology has relieved the burden.
Velocity: - Data streams in at a unique speed and must be distributed within time.
Variety: - There are variations in data that we receive; data comes in all formats from different sources– structured numeric data in a traditional style or unstructured text data, electronic data like email, video, audio or financial data.
Why Is Big Data Important?
The importance of Big Data depends on the activity you need to do with the collected data. You can receive data from multiple source and analyze it, is your data following the standard norms or able to
- Cost reductions
- Time reductions
- New product development and optimized offerings and
- Helps to smart decision-making
When an industry combines big data with highly accurate powered analytics the main factor that is beneficial for them is detection of fraudulent behavior before it affects the organization’s development.
Who uses big data?
Today most of the government and private organizations are using a technique of
Big Data Training. It helps them in a various manner like; quick analysis, filtering, proper storing and easy exchange. The industries, using big data techniques for different purposes are: -
Banking
- Proper storing
- Accurate calculation
- Security of data
- Avoid fraud activities and minimize risk
- Easy transaction/sharing of data
- Easy and regular maintenance
- Boost customer satisfaction
Education
- Proper storing
- Accurate calculation
- Security of data
- Avoid fraud activities and minimize risk
- Identity security
- Easy and regular maintenance
Government
- Proper storing
- Accurate calculation
- Security of data
- Avoid fraud activities and minimize risk
- Easy transaction/sharing of data
- Easy and regular maintenance
- Boost customer satisfaction
Health Care
- Proper storing of patient records
- Accurate analysis of treatment
- Secure confidential data
- Avoid fraud activities and minimize risk
- Easy sharing of data internationally
- Easy and regular maintenance
- Boost patients satisfaction
Manufacturing
- Proper storing/shifting
- Accurate calculation
- Minimize damage risk
- Avoid fraud activities and duplicity
- Easy and regular order maintenance
- Boost buyer and vendors satisfaction
Retail
- Proper storing
- Accurate calculation
- Security of data
- Avoid fraud activities and minimize risk
- Easy transaction and launching new offers
- Regular maintenance of customer records
- Boost customer believes