Getting started with Google BigQuery and GDELT Project

Getting started with Google BigQuery and GDELT

          Once upon the time, the new kid on the block left more established search engines in the dust, then, after reinventing web-based email service, Google introduced its Apps. Today, let’s talk about one of the myriad services Google offers to us: BigQuery. Basically, this cloud-based service allows us to utilize Google’s hardware to store our own datasets or access public data on the go. Google provides API for Java, PHP, and Python access. In addition, various third-party tools now connect directly to BigQuery: Tableau, R, JasperSoft, and Simba to name a few. We get a 1 TB monthly usage quota to query BigQuery’s data for free. Some of the downsides of this service include: premiums for storing our own data and querying in excess of the free quota. We are also limited with data manipulation tasks we can perform in BigQuery; in fact, we can only append records to our table, we cannot update or delete them. Finally, this service uses a SQL language dialect, which lacks some of the SQL commands we are accustomed to: DISTINCT comes to mind, or resort us to some convoluted workarounds (try using the TOP command.) Meet, the GDELT Project – “the largest, most comprehensive, and highest resolution open database of human society ever created.” In this tutorial, we will learn some interesting facts about different countries, using GDELT data in BigQuery.

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Highlights of Gary Cokins Business Analytics seminar

Business Analytics

         Last month I attened Business Analytics seminar by “an internationally recognized expert, speaker, and author in performance improvement systems and cost management” : Gary Cokins.

         My slideshare presentation in the bottom of this post summarizes Gary’s informative and thought-provoiking presentation. In fact, some statements in this post were provoked by this seminar. Gary started by quoting Jeanne X. Harris :“40% of important decisions are not based on facts but rather on intuition, experience, and anecdotal evidence.” Arguably, we could improve the world by basing our decisions on facts, and making better decisions in the process. In addition, better decisions result in better actions, saving us time, effort, money, and other resources. The “actions” part is really important in terms of differentiating Business Analytics from Business Intelligence.

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