We have a new ebook that is set for release shortly and it’s fair to say we’re getting a little bit excited over it!
‘Log Everything!’ will be the latest addition to the Developer.Press family and comes from Stefan Schadwinkel and Mike Lohmann.
So firstly, we thought we’d introduce you to the guys behind the ebook.
First up, Stefan:
Stefan Schadwinkel currently works as Senior Analytics Engineer at ICANS GmbH, a Germany-based IT company developing and operating Online Community websites. Stefan’s main interests revolve around sophisticated data analysis techniques and machine learning. Having majored in artificial intelligence during his computer science studies, he later on received his PhD in human sciences for MRI studies on human auditory cognition. Currently, these interests are nourished in a diverse set of fields: developing user-based metrics to enhance user experience, fostering online fraud prevention, simulating financial trading activities within different markets, and developing backend processing tools in Erlang.
Mike Lohmann started in 1998 with web technologies as Junior Systemadministrator. After a 3 years he came to Lycos Europe as Base PHP Programmer and started 2004 with studying Informatics in Bielefeld. During his studies he worked as Freelacer for different companies like Dannemann, IBM and Lycos Europe. After that he began at Gruner + Jahr in Hamburg as Software Architect and changed 2011 to his current company ICANS Gmbh where he works as Software Architect, too. Beside his work he writes Articles for Heise.de, IX and PHPMagazin and sometimes you can find him on Conferences.
So, what to expect from the book itself?
Big commercial websites breathe data: they create a lot of it very fast, but also need the feedback based on the very same data to become better and better. In this book, we present our journey towards a very generic solution to gather and utilize all data produced by our web application and associated systems, be it technical or business data. We show what technologies we have evaluated and which tools emerged in the end as the (currently) best solution for us. By showing you our ideas, our process, the drawbacks and the solutions, we provide a guide towards building your own data infrastructure. Further, we explore the possibilities to access and harness the data using the map/reduce approach in order to prepare you for the most challenging part of it all: gaining relevant knowledge you did not had before.
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