I work in a consultancy that works with companies who are trying to get more from their data and I'd say that the majority are barely scratching the surface in terms of predictive analytics. I think this is partly because they don't feel their data is ready, partly because they don't have the right internal skills and partly because they've not managed to get the value from predictive analytics in the past. The first 2 reasons I think can be fixed fairly easily by spending some time working with your data and getting better people. The 3rd is more about realising how to use predictive analytics correctly. For example, someone might say that sales are so volatile that only sales reps can predict sales and that no algorithm will do a better job.
Predictive analytics is an area of statistics that extracts information from historical data and uses it to predict future trends. Used across numerous industries to meet diverse purposes, predictive analytics help people make more informed decisions for better results. For instance, Amazon suggests items of potential interest, encouraging another purchase by comparing your buying history with similar users. Email filters, text suggestion/autocorrect and streaming recommendations are just a few everyday instances of predictive analytics.
Hi, I am a MBA with 10 years experience primarily in consulting and strategy. My last stint for my company was in BI and descriptive analytics and I was hooked onto learning more. Given my background and my interest, I am looking to be the analytics-business liason not the core data-scientist, but someone who understands enough of analytics and business.