Big Data What is "big data" and how does this field relate to decision analysis?

Big data is really an expansion and improvement on what has been done for years and that is the collection and analysis of data. However, the two major differences that have emerged over the years is that the amount of data that can be harnessed at one time is much larger than it used to be and analytics/analysis of modern information systems can analyze the data much quicker, with much better accuracy and in ways that were elusive if not impossible in prior years and generations of technology. As an example, a robust information services/Big Data framework could find trends and outliers much quicker than a person, presuming a person could find them at all. This all relates to decision analysis in that the computers of today can do a lot of the work for the analysts. For sure, the analysts need to know how to program, use and harness the data at their fingertips but the system does most to all of the heavy lifting and what would normally take up most of the time available to the analysts. This allows for decisions that are more informed and decisions that can be made much quicker because the data can be assembled and parsed within a much narrower time horizon (IBM, 2011).

2. Identify and discuss three key points from the article "Power of Analytics in the Public Sector" that you found interesting and useful from a public sector decision-making perspective. Explain your response.

The very first point made by the article is that the growing complexity...

The article also speaks about an "information explosion." It notes that this wealth of data is both a blessing and a curse. It is a blessing because there is the ability to make more informed and complete decisions. On the other hand, it is a curse because wielding and molding all of that data can be extremely hard to do unless the right people and systems are in place. The IBM report makes much the same point when it describes what analytics are and then they describe analytics competency. Indeed, the author of this response recognizes that getting all of the data together and the software to analyze it is one thing. However, having the organizational resources and people in place to do that analysis is an entirely different matter. Sometimes, finding the right people with the proper training and motivation can be a hard thing to pull off (IBM, 2011).
The author of this response was already aware that even non-profits and public sector businesses can (and should) use analytics and proper data analysis just like private sector/for-profit businesses do. Obviously, the underlying motives and goals are different but any organization can use analytics to keep things streamlined and decisions based on facts rather than best guesses or rosy assumptions. However, IBM's report confirms all of this but also expands on it. For example,…