The promise of graph databases in public health
One of the main advantages of a NoSQL graph store is web-scale discovery. The graph store is one of many innovations creating a sea change in database technology: explore the promise and upheaval caused by these new technologies.
The future of collaboration: Large-scale visualization
Why large-scale visualization may be the key to success for improving business decision making with data analytics.
The 5 Dimensions of the So-Called Data Scientist
What is “data science”? Is it really a new emerging discipline as some claim it to be; or is it the emperor in new clothes – data mining, statistics, business intelligence or analytics re-branded? Moreover, is it possible that one person can fulfil the role of a data scientist? Rather than answering this question directly, let’s review some of the skills required for someone to be a “data scientist.” First and foremost, a “data scientist” is a business or domain expert: Someone who has to have the ability to articulate how information, insights, and analytics can help business leadership answer key questions – and even determine which questions need answering – and make appropriate decisions. The data scientist will need a thorough understanding of the business across the value chain (from marketing, sales, distribution, operations, pricing, products, finance, risk, etc.) to do this well. Second, a “data scientist” is a statistics expert: Someone who has to have the ability to determine the most appropriate statistical techniques for addressing different classes of problems, apply the relevant techniques, and translate the results and generate insights in such a way that the businesses can understand the value. This will be predicated on a …