To all voracious readers, here is an ideal list of books to have in bookshelf of every data scientist and analyst. These books cover a wide range of topics and perspective, which would help to become a well-rounded data scientist and analyst. Here are a few:

• R Cookbook by Paul Teetor

• Python for Data Analysis by Wes McKinney 

• Web Analytics: An Hour a Day by Avinash Kaushik 

• Web Analytics 2.0 by Avinash Kaushik 

• How to Measure Social Media: A Step-By-Step Guide to Developing and Assessing Social Media ROI by Nichole Kelly

• The Visual Display of Quantitative Information by Edward R. Tufte

• Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics by Nathan Yau

• The Wall Street Journal Guide to Information Graphics: The Dos & Don’ts of Presenting Data, Facts, & Figures by Dona M. Wong

• Now You See It: Simple Visualization Techniques for Quantitative Analysis by Stephen Few

Read more at https://www.analyticsvidhya.com/blog/2015/06/infographic-read-books-analytics-data-science/

According to Mary Shacklett (president of Transworld Data), organizations need big data and analytics capabilities for immediately transferring big data into actionable decisions. According to a Gartner September 2014 report, there is an increase in investment in big data by 64% from 2013. Jeff Kelley (Big data analytics analyst from Wikibon), says that “customers expect personalization when they visit websites, so companies need to develop analytical capabilities and in the long term apply real-time will grow as Internet of Things.” Preventive maintenance analytics can be developed, if data on the Internet to thing can be analyzed. To know more about real time analytics and Internet of Things read on:  http://www.techrepublic.com/article/surge-in-real-time-big-data-and-iot-analytics-is-changing-corporate-thinking/

According to Vincent Weafer (Senior Vice President of Intel Security), analytical capabilities will help you to be ahead of your competitors. Predictive Analytics help you to analyze the future trends more accurately and help you to realize your threats and opportunities which affects budget, purchase and staffing decisions. For prediction, a large amount of data is required from a range of activities which organizations perform, historical events and third party intelligence and to make predictive analytics more effective, you need to build foundational abilities like real-time hunting, prioritization and scoping of security incidents in their environment. You need to analyze your stakeholders for blocking decisions. Read more at: http://www.darkreading.com/partner-perspectives/intel/predictive-analytics-the-future-is-now/a/d-id/1319956