The Dataiku Blog

Why AI Isn’t A Black Box (And Its Business Value)

Artificial intelligence (AI) is a powerful and growing field, but some are still hesitant to employ it, seeing it as a black box. However, if you take a second to step outside the box (see what we...

data science, ai, black box | July 17, 2018 | Megan Fang

I Can’t Afford to Hire a Data Scientist. Now What?

By now, it’s no secret that Harvard University named Data Scientist the sexiest job of the 21st century. Yet unfortunately, not every company can afford to hire one of these little superheros -...

data science, Academic, ngo | July 11, 2018 | Eva Neuner

Top-Down vs. Bottom-Up Approaches to Data Science

Data projects are generally organized in one of two ways: top-down (that is, starting with the business question) or bottom-up (starting with the data and working up to insights). But is there a...

data science, strategy, operationalization | July 10, 2018 | Alex Reutter

Data Science at Scale: Six Major Trends

Last week, Dataiku hosted an EGG-citing day of presentations and panel discussions from industry leaders and experts. The insights they provided tell us a lot about the current state of data...

data science, scale, egg | July 05, 2018 | Robert Jett

O16n On The House: Housing Predictions Made Easy

A big problem in machine learning (ML) is data scarcity, but operationalizing ML is an even bigger problem for enterprises (and is often overshadowed by the excitement for big data). Dataiku 4.3...

data science, machine learning, operationalization | June 25, 2018 | Megan Fang

5 Lingering Questions in 2018 + 5 Budding Trends to Watch for 2019

We’re now officially halfway to 2019 (or 2018 is half over, if you’re a glass-half-empty type), and this year was supposed to be the one where all kinds of companies made revolutionary strides in...

organization, data science, ai | June 20, 2018 | Lynn Heidmann

NLP In Under 5 Min

AI is the sexiest trend in tech, and NLP (Natural Language Processing) is one of its many branches. NLP is the ability of a machine to understand and “speak” (generate) the human language. 

data science, machine learning, NLP | June 18, 2018 | Megan Fang

Our 2018 FIFA World Cup Bet: Train It Like Beckham

The 2018 FIFA World Cup starts tomorrow, and we decided to use Dataiku to predict not only who will win overall but also how far France, England, and Germany will go (we tried to include Italy too...

data science, machine learning, predictive analytics | June 13, 2018 | Pierre Le Jeune

Dataiku comes with Visual AutoML (And You Didn’t Even Know About It!)

Inspired by the latest CDiscount tech post giving an overview of some MetaML solutions, we thought this would be the perfect time to also talk about MetaML. Because what could be more meta than to...

data science, machine learning, autoML | June 11, 2018 | Leo Dreyfus-Schmidt

Marketing for Data Scientists (Or: Make Sure People Know What You Do)

It is a bit ironic that the employees who are changing the world of marketing the most, data scientists, tend to have the greatest challenge marketing themselves to the companies in which they...

marketing, organization, data science | June 06, 2018 | Robert Jett

Disease Outbreak Assistance with Data: NATO ACT Innovation Challenge

For many organizations, the most difficult part of a data project is not the collection of the data, but rather the ability to extract actionable insights in a scalable way and in a specific time...

data science, machine learning, defense | June 05, 2018 | Remi Meunier

How To Build a Basic Website Based on Real-Time Predictions

I recently launched my latest little side project called Human or Company: a web page where anyone can enter a Twitter username and instantly determine whether that username belongs to a person or...

data science, predictive analytics, real-time | May 23, 2018 | Jeremy Greze

Best Practices: Encourage Collaboration And Reusability In Data Science

The ability for people to work together on projects and to reuse each others' work can make or break a data team, making the difference between one that's scalable and productive vs. stagnant....

organization, data science, scale | May 15, 2018 | Pauline Brown

Telecos Have Tons of Data ... but Not Tons of Data Value

Data analysis is already a big part of the telecommunications industry, and yet still, experts estimate that most companies have not yet seriously leveraged the data at their disposal to increase...

data science, ai, telecommunications | May 09, 2018 | Lynn Heidmann

From the Trenches: Transforming Organizations Around Analytics

Driving organizational change at any level is not easy, which is why so few enterprises - even in the midst of the current IoT, AI, and machine learning revolution - have managed to pivot to...

organization, data science, scale | May 07, 2018 | Pauline Brown

The Key to Getting Value from IoT? Organizational Change.

Thus far, most of the buzz surrounding the Internet of Things (IoT) movement has been one of niche (and often kooky) smart products. At least in the media, the industrial side - being used in...

data science, machine learning, iot | May 04, 2018 | Lynn Heidmann

Embarking The Data Crew For The Enterprise: Insights from Ubisoft at the EGG Conference

Building a data team that can efficiently and effectively deliver projects isn't easy, and it takes having not only the right technologies, but most importantly, the right people and processes. No...

organization, data science, scale | April 26, 2018 | Pauline Brown
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