The Dataiku Blog

Making Sense of Startup Ecosystem Data

When it comes to data on startups, Startup Genome is the gold standard - their yearly report on the startup ecosystem is well-respected (not to mention well-cited). But how are they able to find...

start-up, case study, data project | April 11, 2019 | Lynn Heidmann

Can AI Actually Be an Objective Judge?

The small nation of Estonia bet on the Internet when it was founded in 1991 and has since been a strong defender of digital technologies and internet connectivity as a universal right and tool for...

ai, ethics, Law | April 10, 2019 | Claire Carroll

GE Aviation: From Data Silos to Self-Service

Despite the hype of machine learning and AI, not many businesses today have actually managed to bring transformational change through data - GE Aviation is an exception. Since March 2017, the GE...

self-service analytics, Data Revolution, Innovation | April 09, 2019 | Lynn Heidmann

Planning & Forecasting in the Age of AI

Forecasting and planning are some of the very oldest use cases of modern statistics - businesses as far back as the 1950s used computer-based modeling to anticipate risks and make decisions. But...

data science, supply chain, forecasting | April 05, 2019 | Lynn Heidmann

AI Isn't Just for the Big Players: Why SMBs Need It Too

According to Forbes, as of 2018, only 11 percent of small and medium businesses (SMBs) use AI, and 41 percent feel that it’s too complex for their needs. But AI and machine learning don't need to...

strategy, SMB, Enterprise Ai | April 02, 2019 | Lynn Heidmann

Preparing for AIexit

Following a slew of incidents of AI gone wrong, governmental agencies are preparing contingency plans for an AIexit in case of extreme circumstances. According to increasingly more experts...

April Fool Joke, EnterpriseAI, data regulations | April 01, 2019 | Florian Douetteau

Predicting Taxi Fares Using Machine Learning in Real Time

Do you remember the days before Uber, Lyft, or Gett? Standing in the street trying to hail a taxi waiting for the moment a free cab might drive by and spot you? These days that world seems so far...

machine learning, predictive analytics, data project | March 28, 2019 | Greta Nasai & Alex Combessie

Executing Data Projects in the Age of Data Privacy

With some industry experts naming 2019 as the year of increased data regulation, it’s certainly true that at this point, there is no looking back - the use of data across roles and industry will...

data governance, gdpr, data project | March 26, 2019 | Lynn Heidmann

Insights from Data Professionals: Challenges & Misconceptions

Data science is a team sport that needs to be collaborative to be successful, but data leaders and practitioners often disagree on where exactly responsibility for data quality and data science...

Team, egg, Enterprise Ai | March 20, 2019 | Claire Carroll

Build A Recommendation Engine in One Day

The recommendation system topic in machine learning has been extensively documented; nowadays, you can find information ranging from the very basic to the cutting-edge (we’ve written our fair...

tutorial, recommendation systems, data project | March 19, 2019 | Liev Garcia

Addressing Fraud with Machine Learning: How & Why

For the financial services industry (as well as many others that deal with data security and other types of non-monetary fraud), anomaly detection is hands down the most important system in...

anomaly detection, case study, financial services | March 13, 2019 | Lynn Heidmann

PwC: On GDPR and the Future of Data Privacy Regulations

The effects of the European Union’s General Data Protection Regulation (GDPR) swept across the globe last year as the enforcement deadline came and went in May 2018. But GDPR is really just the...

organization, data privacy, data regulations | March 11, 2019 | Lynn Heidmann

Introducing Dataiku 5.1: Here's The Inside Scoop

Dataiku is always evolving and improving to better help our users, and the release of Dataiku 5.1 is no different, helping users collaborate and leverage data to drive success. 

Product, Corporate, announcement | March 06, 2019 | Claire Carroll

Why You Should Care About the Data Revolution

More than 90 percent of the data that exists was produced in the last two years, and we’re generating 2.5 quintillion more bytes every day.  The Data Revolution is here, regardless of how prepared...

Data Revolution, Data Leaders, Enterprise Ai | March 05, 2019 | Claire Carroll

Do More Machine Learning & AI (Without More Data Scientists)

Let’s face it - almost no business today can afford to hire the amount of data scientists it would take to go from producing one machine learning model to 1,000 (or for that matter, 1 million)...

organization, data science, scale | March 01, 2019 | Lynn Heidmann

The Path to Enterprise AI in APAC

Every business has a different path to Enterprise AI that’s necessarily affected by its industry, history, infrastructure, competitive environment, clientele, and more. That means that from region...

Corporate, announcement, APAC | February 24, 2019 | Lynn Heidmann

Choosing a Valuable Data POC

POCs often feel like a gamble. You're testing the boundaries of your business's technological capacity and your ability to change at the same time. If your POC is an anomaly or you're unprepared...

organization, Team, POC, operationalization | February 19, 2019 | Claire Carroll

How Tinder Ensures You Can't Help Falling in Love

Dating apps are changing the ways we meet new romantic partners. Whether you’ve succumbed begrudgingly or gleefully, millennials on average spend 10 hours a week swiping and chatting on online...

recommendation, Data Science Basics, Valentine, romance | February 14, 2019 | Claire Carroll

A Peek into the Regulatory Future of AI?

Whether you realized it or not, Data Privacy Day 2019 (yes, it exists!) has already come and gone. But this year, it was perhaps more significant than most not only because topics of bias,...

ethics, EnterpriseAI, interpretability | February 12, 2019 | Lynn Heidmann

Tackling the Cold Start Problem for Recommendation Engines

I recently moved to New York City, a true abundance of riches. I wanted to find “my coffee shop,” but sampling different locales is exhausting and disheartening. I cannot fathom trying a new cafe...

recommendation, machine learning, user experience | February 06, 2019 | Claire Carroll
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