The Dataiku Blog

4 Big Challenges for Retailers, Solved with Predictive Analytics

The retail industry has always been one that’s focused on the vast amount of data it collects, looking at past data and general averages across wide swaths of customers to estimate future...

business, predictive analytics, retail | March 16, 2017 | Romain Doutriaux

5 Barriers to Churn Prediction and How to Address Them

Given that it costs five to 10 times more to acquire a new customer than to retain an existing one, it seems obvious that all businesses should be engaged in some level of churn prevention.

marketing, business, churn | March 15, 2017 | Lynn Heidmann

An Introduction to Key Data Science Concepts

Here at Dataiku, we frequently stress the importance of collaboration in building a successful data team. In short, successful data science and analytics are just as much about creativity as they...

data science, machine learning | March 09, 2017 | Robert Kelley

The Forrester Wave Names Dataiku a Strong Performer

We’re very pleased to continue the momentum and positive trajectory of 2017 and announce that we’ve been named a strong performer in “The Forrester Wave™: Predictive Analytics and Machine Learning...

Users, Corporate, announcement | March 07, 2017 | Carole Offredo

Predict (and Prevent) Customer Churn

It’s pretty simple: churn happens when your customers are customers no longer. For any business (even those gaining customers quickly), this can be a devastating problem; but fortunately...

data science, machine learning, churn | March 01, 2017 | Lynn Heidmann

Upcoming Webinar: How Dataiku works with Microsoft HDInsight

Dataiku’s integration with HDInsight, the fully-managed Hadoop platform from Microsoft, is a great example of the openness with which Dataiku was built. This versatility means that it is easy to...

Partnership, webinar, business | February 28, 2017 | Robert Kelley

Dataiku 4.0 Is Out Now: True Scalable Collaboration!

Today we are announcing the release of Dataiku DSS 4.0, which introduces new functionalities that improve the production, development, and management of large-scale data science projects. 

Product, Corporate, announcement | February 23, 2017 | Robert Kelley

Drive Revenue with Collaboration (Marketing + Data Experts)

In 2017, marketers expect customer experience to be their primary differentiator. And to win attention from customers, most brands are investing heavily in personalization technologies – using...

marketing, segmentation, business | February 22, 2017 | Caroline Martre

Dataiku Named a "Visionary" in Gartner Magic Quadrant

We’re incredibly excited and honored to announce that Dataiku has been named as a “visionary” in the Gartner 2017 Magic Quadrant for Data Science Platforms!

Users, Corporate, announcement | February 16, 2017 | Pauline Brown

Mapping Predicted and Real Rates of Crime in Greater London

Using ESRI and Dataiku Data Science Studio (DSS), here’s how to create an interactive map with Web AppBuilde for ArcGIS that will reveal the different levels of predicted and real crimes in...

data science, machine learning, Data analysis | February 13, 2017 | Nicolas Gakrelidz

Video: Dataiku and Spark, a Powerful Combination

Today is the first day of the Spark Summit East 2017 in Boston, and just in time, we have a brand new video showing why Dataiku and Spark are such a powerful combination.

spark | February 07, 2017 | Robert Kelley

Want to Make your Data Science Team Efficient? Focus on Production.

By "efficient" data science team, I mean "data science that brings maximum productivity."

Production, organization, business | February 03, 2017 | Alivia Smith

Marketing Analytics for a New Era

Today, the effectiveness of traditional marketing segmentation is limited by its reliance on fixed methodologies. Marketing teams that move to model-based segmentation, on the other hand, can...

marketing, segmentation, business | February 01, 2017 | Lynn Heidmann

Data Science at Scale: Make or Buy, In-House or Outsource?

In the world of big data, there is no shortage of open source and commercial tools available; at the same time, there is, in some ways, a shortage of human capital - many companies struggle to...

organization, business, collaboration | January 28, 2017 | Caroline Martre

Infographic: How Does Your Data Science Production Process Compare?

Deploying your data science models into production often requires complex processes and resources that can lead to the failure of your data project. How do companies handle this process?

Production, Data Engineering, Infographic | January 23, 2017 | Alivia Smith

Three Challenges to Address in Banking & Insurance Data Projects

We recently released a mesmerizing white paper on banking, insurance, and big data. Inside, you'll find use cases, methodology, and more. But we also asked a few experts to share their key...

Opinion, business, data | January 21, 2017 | Romain Doutriaux

Machine Learning Explained: Algorithms Are Your Friend

We hear the term “machine learning” a lot these days, usually in the context of predictive analysis and artificial intelligence. Machine learning is, more or less, a way for computers to learn...

Data Science Basics, machine learning, Data analysis | January 19, 2017 | Robert Kelley
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