Microsoft Build was organized once again a couple of weeks back. Read our thoughts about the event, and how we agree with Microsoft's vision of the future.
This blog post is intended for readers who already have some experience on building Data Warehouses with earlier versions of SQL Server (2008 or 2012) and are looking for updating their knowledge on how to do it today on SQL Server 2016 and/or on Azure. In addition, I included some insight on the technology trends on the matter.
Couple days ago The Economist published an article titled "Linux and AWS: Cloud chronicles". The article stressed the undeniable importance of Linux and Amazon Web Services (AWS) in the upsurge of cloud computing and went on to explain how network effects have helped both grow in popularity. Despite similar paths, article predicted that their future will diverge and Linux will "happily plod along" whereas "AWS could end up dominating the IT industry just as IBM’s System/360, a family of mainframe computers, did until the 1980s".
Cloud analytics have changed the world big time. BIGDATAPUMP is an independent and objective solution provider using always the best fit technology for each purpose. Personally I have not written earlier about any specific analytics technology but this time I decided to make an exception. Microsoft and Azure deserve a special focus.
tl;dr: Gartner's Magic Quadrant for advanced analytics doesn't do a good job in helping to decide which analytics tool(s) to acquire. It also misses the point that open source projects are the real leaders in advanced analytics. Vendors that position themselves to complement open source projects rather than competing against them will be ones to watch.
Online advertisement is sold more and more through ad exchanges and auctions in particular. Ad auctions are an efficient way of buying and selling ad space and they will get more popular simply because they are better for everyone. In theory, auctions are "strategy proof" and hence you can't game them.
In BIGDATAPUMP, we have had two main BI visualization tool families in most active use in our customer projects: Qlik products and Tableau. However, also Microsoft’s Power BI started to look really promising, and in February it ranked really well in Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms.
Many people have a biased view of what econometrics really is and how it can be applied to business problems. In the following posts I will introduce some methods from applied econometrics, structural modelling and panel data/time series tools and show how they can be used to solve problems where standard statistical and machine learning tools do not work.