by Angela Guess
Michael Vizard of IT Business Edge recently wrote, “One of the biggest problems with Big Data is the whole notion that organizations need to hire data scientists in order to be able to work with it. In case you have not noticed, there are not that many data scientists actually walking around these days. That’s what makes version 7.1 of Alteryx Strategic Analytics worth noting. According to Alteryx President George Mathew, if only a handful of people can really take advantage of Big Data, it more or less defeats the purpose of making the investment in the first place.”
He continues, “Outside of Wall Street and Fortune 500 organizations, most companies can’t afford to have a data scientist. They are lucky to have anybody who could be called a data analyst. It’s really going to be up to the providers of analytics applications to find ways of making all that data more accessible. Once that happens, notes Mathew, it will make sense for the average organization to start investing in collecting all that Big Data.”
[...] The Big Data Problem in Customer Experience Management: Understanding Sampling Error October 18, 2012 By Bob Hayes Leave a Comment TweetShare via emailBig Data is being touted as the next big thing for businesses. The benefits of Big Data are apparent in many areas, from search results and recommendation engines to customer experience management. By analyzing massive amounts of quickly expanding, diverse data, businesses are able to gain the insights they need to beat their competitors. A major roadblock to discovering these insights, however, is the lack of people with the skills to analyze these data. For example, in a late 2010 study, researchers from MIT Sloan Management Review and IBM asked 3000 executives, managers and analysts about how they obtain value from their massive amounts of data. These respondents said that the number one obstacle to the adoption of analytics in their organizations was a lack of understanding of how to use analytics to improve the business. Also, McKinsey and Company estimated that the US faces of huge shortage of people who have the skills to understand and make decisions based on the analysis of big data. There are simply not enough people with Big Data analysis skills, suggesting that the unmet need for data scientists is a problem for Big Data and undercuts the value of Big Data. [...]
[...] that the unmet need for data scientists is a problem for emerging fields like Big Data and undercuts the value of Big Data. In addition, because the US students rank 31st in math and 23rd in science compared to the rest [...]
[...] that the unmet need for data scientists is a problem for emerging fields like Big Data and undercuts the value of Big Data. In addition, because the US students rank 31st in math and 23rd in science compared to the rest [...]