애널리틱스, 빅데이터 관련 6개 기사 독후감상문_Columbia Univ_Reading Reviews on 6 articles about big data and analytics

and numerous product lines of the business, the data size will significantly increase. Therefore, the server capacity of database must be increased accordingly (after upgrading the whole systems, the data scale is expected to be big data and implementation of big data technology such as Hadoop will be required). Last but not least, all of the data would be useless if data science and analytics are not implemented to analyze the data, monitor the test procedure, and come up with actionable plans or ways to improve the systems. Yet, on top of the lack of the experience, knowledge and technologi

and values are the most important elements that shapes the culture of innovation.Meanwhile, GEs analytics team takes researcher-minded approach where searching for problems, asking the right questions, and understanding them are crucial. Plus, Yet, in terms of using simplicity and easiness for solving analytical problems, the teams culture too is similar to that of Google.Googles working environment would also fit well in research labs whose main goal is to find a breakthrough solution, for example a vaccine. In this case, focusing-on-the-user mind, and hiring talented people would be as

Review some responses from some of the other students, and comment on one additional technique you could have employed to address the problem.While it was not necessarily a model, I struggled to enhance budget forecasts in construction projects, which was difficult because the materials and equipment used were mostly made to order in accordance with the technical designs proposed by the companys engineers and did not have standard price. The budget estimations were significantly different from the actual costs. I performed an analysis using the companys internal data on completed construct

on Uber. Instead, it continued its effort for the society and, the media and public applauded the company’s decision. With its socially responsible image, Lyft gained significant momentum, and many users shifted to the company’s service. This event substantially transformed the market situation; Now the current market share distribution is 60% Uber, 35% Lyft, and 5% others, as of May 2018, with valuation at about $50 billion for Uber and $11 billion for Lyft. In addition, what make Lyft full of potential is its focus on the long-term vision, not the immediate profits. So far, Lyft has be

Tom Davenport, in “Analytics 3.0,” discusses the distinguishing features of what he calls 3 stages: Analytics 1.0, 2.0 and 3.0. Do you agree or disagree with his characterization, and why or why not? What evidence do you bring to bear on this?The authors characterization in analytical stages are evident. The construction company I worked for in the past, and many of the suppliers I had transactions with fall into somewhere around analytics 1.0. They agree that data analysis is important and utilizes it to some extent. However, they tend to focus their resources more on sales and project