Enterprise Customer Data Platform - Treasure Data Blog - Part 25

Supercharge your Salesforce Data Search Efforts with Treasure Data and Elasticsearch

Elasticsearch is growing by the day, and its users include companies like Ebay, Verizon, Reuters, The New York Times, Microsoft, and Facebook (and those are just a few of the bigger ones!) Elasticsearch bene...

Accurate Sales Forecast for Data Analysts: Building a Random Forest model with Just SQL and Hivemall

In this blog post, we will use Hivemall, the open source Machine Learning-on-SQL library available in the Treasure Data environment, to introduce the basics of machine learning. We will use an E-Commerce dataset from Kaggle, the data science competition platform. Introduction The first challenge i...

Using Analytics to Uncover the Best Path to Monetization

At some point, every successful app needs to turn a profit - no two ways about it. Those millions of daily active users don't mean jack to your investors until you find something they'll actually pay for. And, when it comes to mucking around with your user experience looking for paydirt, good analyt...

AdWords Reports: An Awfully Partial View

Which AdWords campaign has the best return on ad spend (ROAS)? Every digital marketer has been asked this question at least once, if not every week. You would think such a simple question could be answered with an AdWords report. But as you dig deeper into your data and product, you realize that ...

Capture your Kinesis Stream Analytics Events in Treasure Data

With data-driven companies like Coinbase, Dash and Supercell all getting on board with Amazon Kinesis for real-time delivery of in-app data, handling billions of events per day, we can imagine why you too might...

We Analyzed Over 6 Million SQL Queries & Here’s What We Found

As part of our effort to improve product usability, I decided to take a look at how other analysts and Treasure Data users write their SQL. Like any other language, you can develop your own style over the years, and we should design our query editor accordingly to make the query-authoring experience...

Customer Highlight: Bringing Data Science to Mobile Shopping at Wish

Treasure Data helps a growing e-commerce platform focus on products over infrastructure Wish needed scalable data infrastructure that worked right out of the box. Back in early 2012, the recommendations based shopping app had grown from a data science experiment at ContextLogic into a full web ...

Wrangling Huge .CSVs Made Simple (with a little help from SQL)

Let's say you have a very large .csv (containing more than 80k rows) that you want to analyze and visualize. Usually, given only Excel and Tableau (or Looker, Chartio, etc.), you would have one of two options...

25