Will 2016 be the Year you Clean up your Dirty Data?
For ever it seems, we’ve been warning about the dangers of low quality data. Our warnings have been reinforced and echoed by some of the world’s biggest think tanks. ...
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Global Big Data Market to Develop Rapidly by 2018:
The global big data market is expected to develop rapidly by 2018, with major contribution from the North America regional market. In the past few years, there has been a...
Our Berkeley Data Science Capstone Project: Rap Analysis
Guest blog post by Tony Abraham, Nikhita Koul, Joe Morales. A data science exploration of rap lyrics and what it takes to make it onto the billboard charts. Originally ...
Statistical Significance and Its Part in Science Downfalls
In Discover Magazine this month is a really frightening article about the failure of psychologists to reproduce the results of 100 high profile psychology experiments pub...
From DevOps to DataOps
Written by Andy Palmer, CEO of Tamr Why It’s Time to Embrace “DataOps” as a New Discipline Over the past 10 years, many of us in technology companies have experienc...
The Data-Driven Weekly #1.6
Right on cue, this past week heralded in an announcement of OpenAI, a new non-profit started by a number of tech luminaries to spearhead AI research that is publicly acce...
5 Data Science Leaders Share their Predictions for 2016 and Beyond
First, we list the predictions from our data scientist in residence. Then we provide predictions from leading data scientists. We invite you to add your own predictions i...
As a Data Science Blogger Does Your Opinion Count?
Summary: If you want to make yourself heard as an author in data science, consider Google Author Rank. OK, if you blog you are by definition concerned about two things, 1...
Architecture of Data Science Projects
In this article, I summarize the components of any data science / machine learning / statistical project, as well as the cross-dependencies between these components. This...
5 Data Cleansing Tools
You need to analyze data to make more informed decisions. There are many tools to help you analyze the data visually or statistically, but they only work if the data is...