Technologies Deciding Future of Agriculture

Today world is changing at a rapid speed. Technology is playing an important role. Agriculture technology is also advancing and promises to unleash its productivity. The combination of advanced mathematics, automation, advancements in sensor systems and next-generation plant breeding are setting the stage for the next Green Revolution, which is needed to ensure a better future. Next-generation farms are putting science and technology to work towards delivering a step change in yields and growing more from less. Here are the four most exciting developments in 2016.
1) The Mathematics revolution,
2) The Sensing Revolution,
3) Putting it together with automation and
4) Next generation plant breeding of corn.
Read more at: http://www.forbes.com/sites/gmoanswers/2016/01/26/four-technologies-that-will-usher-next-generation-farming/#3cfe147b69f5

Predictive Analytic supported with contextual Integration is the secret of success

Contextual Integration refers to identifying meaningful relationships between different information types. This gives a multi-dimensional view of the data rather than a single access point. The best approach is to analyze these volumes of data from different perspectives. The traditional way is to follow a fragmented approach. The web teams, marketing and sales team will look at the different statistics offered by data. This lengthens the time to take decisions and also introduces inaccuracy. The need is to look at data from many angles to create a multi- dimensional profile of the customer. Then predictive analytics can assess and lead to intelligent messaging. Machine Learning is also helping to improve these predictive analytics algorithms by checking it on the real time data. Read more about it in the article written by Dominik Dahlem (Senior Data Scientist at Boxever) at: http://data-informed.com/contextual-integration-secret-weapon-predictive-analytics/

Prevent System outage with Machine Learning

Failures in the functioning of equipment are inevitable in any kind of industry. The repair and recovery time often leads to big financial losses each year. But we have machine learning and predictive analytics as a solution. The machine learning models are trained to learn the ideal functioning of the machinery. Then this functioning is compared with how the machines are working at present. So if even a minor change occurs somewhere, it doesn't go unnoticed. Then, with the help of predictive analytics the loss that can take place in the near future is predicted. This adds to the huge advantage of the firms. Learn more about this in the article written by Mike Reed   (manager of analytical services for Avantis PRiSM software) at: http://www.intelligentutility.com/article/16/02/saving-money-and-man-hours-machine-learning

Workforce Analysis helping Businesses

Even at the time of hiring, workforce analysis influences from starting i.e. creation of a job description and worker roles, till the recruitment of the person with better chances to succeed in the organization. Through the analysis, companies can make better hiring choices and monitoring the performance in real time. This will help companies to refine their organizational structure and develop talent and leadership within the organization. Workforce analysis will also help in reducing legal claims issues. These all will contribute in cost reduction and smooth working of the organization. Read more at: http://www.smartdatacollective.com/sarah-smith/358073/control-business-costs-workforce-analytics