Treasure Data Blog - Part 40

A Self-Study List for Data Engineers and Aspiring Data Architects

With the explosion of “Big Data” over the last few years, the need for people who know how to build and manage data-pipelines has grown. Unfortunately, supply has not kept up with demand and there seems t...

SQL is Not Dead and How to Make it Part of Your Toolbox

Even as SQL draws ever closer to being half a century old, it continues to be relevant for the majority of the business world. One reason for SQL's continued reign as the main data query language is its ease of use. Back when SQL was being built at IBM, their goal was to create a language that mirro...

Evaluating Analytics SaaS’s Raw Data Access Capabilities

Why Raw Data Access for Analytics SaaS? If you are a data analyst or data-driven product manager, you must have hit the limits of your analytics tools at one point. For example: You noticed that a particular customer's product usage spiked, and you wanted to track them event by event but your t...

Microsoft Offers a Faster, More Efficient R, But Is it Right for You?

In early 2015, Microsoft announced its successful acquisition of Revolution Analytics, which made R available as an enterprise ready statistical and data science solution. Initially, Microsoft stated that they would be using this acquisition to seamlessly integrate the power of the R language into M...

How to Succeed at Importing XML to Just About Anywhere (without converting to JSON first)

JSON is everywhere. Nowadays, almost any emerging data ingestion framework or REST API endpoint uses JSON as a data transfer format. In fact, many will argue that since data is stored in records and array...

February 28, 2016

Elastic 2016 and Fluentd FAQs

Last week, Elastic, the company behind Elasticsearch, Logstash, Kibana and Beats, put together their annual user conference in San Francisco. Because Elasticsearch is a popular backend for......

February 25, 2016

451 Revisits Treasure Data: What’s Changed This Year

A year ago, analysts at 451 Research took a close look at TD. Now, they’ve come back to see what’s changed. Since the data science space is constantly evolving, analysts are imperative to helping navigate the field......

February 19, 2016

The Magic of Presto: Petabyte Scale SQL Queries in Seconds!

If you've been in the data analytics field for even a short period of time, you've probably at least heard of Spark, Hive or maybe Cloudera Impala as a means of running SQL-type queries against large semi-str...

February 17, 2016

Elasticsearch, and How to Make it Faster for ALL Queries

With millions of downloads since launch, Elasticsearch has become the open-source tool of choice for full text search. Also, it has become increasing popular for analytics use cases thanks to its ease of setup and JSON-based RESTful API. Like any other technology, however, Elasticsearch excels i...

February 16, 2016

Build a Simple Recommendation Engine with Hivemall and Minhash

This is a translation of this blog post, printed with permission from the author. In this post, I will introduce a technique called Minhash that is bundled in Treasure Data's Hivemall machine learning library. Minhash is not usually thought of as a machine learning technique, but as you will see...

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