AppLift Tech Blog

Actionable Business Intelligence is changing the way businesses are done. We dig into the three levels of implementations of actionable Business Intelligence that can make a true business impact.


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By Uzi Blum in Development — January 5th, 2018

Apache Spark ecosystem has revolutionised the Big Data processing world with its unique unified programming model. This has made Spark a must-have technology for companies such as AppLift, which rely heavily on open source technologies for its data engineering and data science needs.


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By Chandan Prakash in Development — April 19th, 2017

Machine learning models are ubiquitous in adtech today. One of the most common applications of machine learning in adtech is building a predictive model to estimate probabilities of rare events like clicks and installs.


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By Girish Sathyanarayana in Backend, Development — January 11th, 2017

One of the key meetings in a scrum cycle is the Pre-Planning. As each team adapts the process differently, it probably has a bit different way of doing this meeting.


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By Eyal Golan in Development — August 30th, 2016

AppLift specializes in delivering data-driven performance-optimized mobile app install campaigns. Some of the problems that we come across when solving these problems, include click-through-rate prediction (rate at which to expect clicks given that we have shown an impression), conversion-rate-prediction (rate at which to expect conversions or app-installs given that we have a click on the impression shown) and fraud-traffic classification.


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By Sunil Nandihalli in Backend — May 26th, 2016

At AppLift, we are using Apache Storm to build Real Time Events Processing Pipeline for analyzing, aggregating, frequency capping and most importantly taking budget decisions in real-time per Ad-campaign with least possible latency. The events data is streamed to Apache Storm in real-time; via in-house built publisher-subscribers mechanism using ZMQ; where events are processed and persisted.


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By Servesh Jain in Backend — May 26th, 2016

Looking to grow and be in control of your career? Come and meet the AppLift team during the first AppLift MeetUp in 2016. We are looking forward to welcoming you!


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By Alexander Dötsch in News — May 9th, 2016

At AppLift we use Apache Spark for quite a few data pipelines, and we are big fans of both Spark and Scala. That said, recently we were a little bit puzzled after getting exceptions while trying to upgrade to the recently released version 1.5.2 - even more so because the exceptions were stemming not from misusing the Spark API itself but rather something more fundamental: JDBC.


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By Bruno Wozniak in Backend — March 11th, 2016

The tech team at PubNative have come up with a nifty new Go MySQL driver that creates less objects in the heap, resulting in a lower Garbage Collection time. It’s really easy to use. Check out the readme, try it out, and give them your feedback!


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By Eyal Golan in Backend, News — February 12th, 2016

Here at AppLift we have multiple internal tools for managing our ad campaigns. Our methods don't deviate much from well-known practices, we prefer small autonomous components with explicit interface and we try to re-use as much code as possible. This post will be about these and other ideas that worked well for us.


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By Vladimir Feskov in Frontend — January 28th, 2016