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Graduate from Mixpanel: Funnel Analysis with SQL and R

This post is part one of a two part series. See part two here. What is Funnel Analysis? In a nutshell, funnel analysis allows you to follow a user through a series of self-defined events as well as, allowing you to calculate the given conversion rates between event to event. There are multiple ways and ... Graduate from Mixpanel: Funnel Analysis with SQL and R

Redshift is 400x Bigger than MySQL Yet MySQL is More Popular

The Amazon Redshift COPY Command Guide is now available! There are good reasons for the hype around Amazon Redshift. Redshift is blazing fast and not that much more expensive than MySQL or PostgreSQL, the traditional mainstay of data engineers. But is Amazon Redshift really becoming predominant in the world of analytic databases, taking over its ... Redshift is 400x Bigger than MySQL Yet MySQL is More Popular

Move your data – from MySQL to Amazon Redshift (in less time than it takes to ignore an index!)

Redshift, as you may already know, is quickly gaining broad acceptance, especially among consumers of free software like MySQL and PostgreSQL, for its “pay as you go” pricing model. However, the same pricing model can still make it a very expensive one. Not all queries need to be done against the Redshift instance itself, as ... Move your data – from MySQL to Amazon Redshift (in less time than it takes to ignore an index!)

Elasticsearch vs. Hadoop For Advanced Analytics

A Tale of Two Platforms Elasticsearch is a great tool for document indexing and powerful full text search. Its JSON based Domain Specific query Language (DSL) is simple and powerful, making it the defacto standard for search integration in any web app. But is it good as an analytics backend? Are we looking at a ... Elasticsearch vs. Hadoop For Advanced Analytics

5 Tips to Optimize Fluentd Performance

We’ve rewritten the Ruby supporting MessagePack, the highly efficient binary serialization format used internally. (MessagePack was invented by TD‘s co-founder Sadayuki Furuhashi)...

Making Magic with pandas-td

Magic functions enable common tasks by saving you typing. (NOTE:  Pandas itself doesn’t have magic functions; the IPython kernel does.) Magic functions are functions preceeded by a % symbol. Magic functions have been introduced into pandas-td version 0.8.0!  Toru Takahashi from Treasure Data walks us through. Treasure Data’s magic functions work by wrapping a separate ... Making Magic with pandas-td

Collecting All Docker Logs with Fluentd

Just in case you have been offline for the last two years, Docker is an open platform for distributed apps for developers and sysadmins. By turning your software into containers, Docker lets cross-functional teams ship and run apps across platforms seamlessly...

Data Science 101: Interactive Analysis with Jupyter, Pandas and Treasure Data

TD gives you a cloud-based analytics infrastructure accessible via SQL. Our interactive engines like Presto give you the power to crunch billions of records with ease. As a data scientist, you’ll still need to learn how to write basic SQL queries...

Python 101 for Aspiring Data Nerds

As a data scientist, or anyone interested in collecting data for that matter, it’s no doubt helpful to know about how to go about collecting the data in your app – data that you’ll want to later query and analyze. Here, we’ll build an app in Python from A-Z,  iterate on it to make it ... Python 101 for Aspiring Data Nerds

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