The existence of a gender based price discrimination where women’s products are typically more expensive than men without any reasonable cause is widely known as ‘’pink tax’’. Lately, this gender discrimination has extended to car insurance with women paying more despite men being risky drivers. A recent study concluded that women especially older ones pay higher care insurance in at least 25 states. The Consumer Federation of America (CFA) revealed that insurance company not only charges different rates based on gender but also on the city in which a particular person lives in. While some countries including California, Massachusetts have already prohibited gender based car insurance pricing, we can hope that greater reliance on big data can provide some solution. Big data is greatly helpful in determining fairer and accurate insurance rates based on relevant factors. Read more at: https://channels.theinnovationenterprise.com/articles/inconsistent-correlations-between-gender-car-insurance-rates

The buzzing technology giants, big data, IoT and cloud computing are completely separated disciples. But the union of these technologies is leading us towards an advanced version of our world. According to IDC, “Within the next five years, more than 90 percent of all Internet of Things data will be hosted on service provider platforms as cloud computing reduces the complexity of supporting the Internet of Things ‘data blending’.” Nowadays IT sector is shifting itself from product orientation to information based outcome orientation. The coupling of these technologies is helping our healthcare industry to become smarter, advances in self service analysis, beneficial for industrial IoT, adoption of edge-computing and so on.  

For more info, go to:

https://www.analyticsinsight.net/convergence-of-big-data-iot-and-cloud-computing-for-better-future/

Data is an important aspect of decision making and for valuable insights over the data, BI has emerged crucial in organizations. Some useful ways to manage your data and team are : 1.Invest in a robust BI service like Google Analytics or CoolaData so as to get better insights on behavioral analytics and better collaboration. 2.Break down silos - when organizations go through silo effect and information stops flowing, BI can prevent this through transparency. 3.Teams should acquire data analysis skills and grow as they work. 4.One should relate to the context, not depend solely on the numbers but on the why, how. 5.Decide on how to decide for better data implementation. 6.Drive action through insights, study how trends correlate and act accordingly. Read more at :

http://www.networkworld.com/article/3197753/big-data-business-intelligence/6-ways-to-manage-your-data-and-team.html

The world is entering the age of abundance, abundance of data. And with this, the age of intelligence is on its way. According to Eric Scht, the author of the original article, in today’s world, science and critical thinking really matter a lot. People are becoming wary of changes looking at the rate at which technological advancement is taking place. With the massive increase in data in almost every field, the need for artificial intelligence and machine learning is being felt in a broad range of sectors including farming, energy, fashion and healthcare. Read more at: https://www.theguardian.com/small-business-network/2017/jun/22/alphabets-eric-schmidt-google-artificial-intelligence-viva-technology-mckinsey

Technical revolution is always an unbiased phenomenon but the human makes that positive or negative. After the mechanical revolution of the 19th century, AI is considered the next revolutionary phenomenon in human civilisation which will make a significant impact on technology and global socio-economic condition. AI’s decision making capability is still not highly advanced so AI can’t replace humans now. AI will kill some jobs and create some exciting jobs also. Technical innovation creates new opportunities and friends also. Read more at:https://www.entrepreneur.com/article/288956

Big data and analytics projects will be managed by individual departments when the analytics solution at hand concern to a specific function that department does. The analytics solution is required to answer key questions that about the business, whether it is struggling with in a particular area of expertise or not. This makes the owning department the most logical area to start the search for an analytics solution. Some good practices can be: i) develop a compelling business case for the application ii) Get support for the project. iii) don't let IT run the project iv) Trial the new application v) Perform due diligence vi) Develop a roadmap vii) Don't let the technology take over viii) Create a super user ix) Always attempt for a "quiet" system. Read more at: http://www.techrepublic.com/article/10-tips-for-running-a-successful-analytics-project-outside-of-it/

The growing potential of big data should incorporate analytics into its strategy to make better and faster decisions. Businesses can use data and analytics to make better decisions by using granular data. New machine learning has a lot of applications and benefits. Systems enabled by machines can provide better benefits. The technologies could generate productivity gains and an improved quality of life, but they carry the risks associated. Industries are getting greatly influenced by data and analytics, and the effects will become more pronounced when it reaches the masses. Organizations that can harness these capabilities will be able to create significant value and differentiate themselves, whereas other people might not be happy with this. Read more at: http://blogs.economictimes.indiatimes.com/et-citings/managing-analytics/

Big data imply huge sets of organized and unstructured information. It is very complex and regular data processing techniques don't work in managing this kind of data sets. In business, the 3V model is utilized to depict enormous information. These 3V's are: volume, velocity, variety. Now let's understand how big data helps businesses and why it is important:

• Examining big data helps understanding the current economic situation so that it can get an idea of getting ahead of it’d competitors.

• Big data analysis helps to understand your customer better, predict what they need in advance and can provide better service.

• You can control your online reputation with the help of doing sentiment analysis.

• Big data tools, save lots of money as it reduces the manpower to handle large amount of data.

Read more at: http://www.business2community.com/big-data/big-data-important-businesses-01818898#DOiRF3OOYiZ3JlAb.97