Today’s Biggest Success Tip: Predictive Analytics Using Big Data

Are you looking to change your life?

Are you looking to change your life? If you answered “Absolutely!” then prepare yourself to take advantage of one of today’s biggest opportunities: Predictive Analytics using Big Data.
Trends such as globalization, economic uncertainty, and rapidly changing technology have shaken up our society. Right now, we face several major disruptions within computer technology: Cloud, Personalized Assistants (tablets, smartphones, and other mobile devices), Social Media, Big Data, and Analytics.

Ten years from now, all of these trends will have transported us into a completely new business environment.

A connected population of billions of people generates a massive amount of data which, properly digested and analyzed, will lead to an explosion of knowledge. Smart people will leverage this knowledge to take beneficial action, either for themselves personally or for the good of others.
Technologies such as Hadoop and Map/Reduce emerged to enable storing large amounts of unstructured data. Companies will combine their traditional data warehouses containing structured enterprise data with unstructured mountains of external data and store the results in the cloud (using services such as Amazon AWS/EC2, Rackspace, Microsoft Azure, or Google App Engines).
After storage comes the application of algorithms to make sense of the data. Computer programming languages (such as Java, Python, C/C++, and R) that can perform large data set techniques (e.g., regression, classification, natural language processing, clustering, collaborative filtering, and machine learning) will be enhanced with toolkits (such as Weka, OpenNLP, and NLTK) and evolve into entire frameworks for analyzing Big Data, finding patterns, reducing uncertainties, and enabling new decisions and actions.
With all these technologies, our challenge will then be to identify the questions we want to ask of the data.
If you could solve a world problem (or make millions of dollars) if you had answers to just a few difficult questions, wouldn’t you start today to gather the data?