The Dataiku Blog

Lynn Heidmann

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Recent Posts

What AI Can Bring to the Utility and Energy Industries

The drive to make utilities more efficient through AI, machine learning, and data science has resulted in major benefits for every actor in the energy sector, including generators, distributors,...

* Use Cases & Projects | October 15, 2019 | Lynn Heidmann

Best Practices for Operationalizing Data Science & Machine Learning

Roger Magoulas, VP of Radar at O'Reilly Media, Inc., asks: Why is the final mile such a challenge for so many organizations who are working on AI and machine learning? Dataiku Data Scientist Jed...

* Scaling AI | October 14, 2019 | Lynn Heidmann

Solving the Data Science Talent Shortage

Data and AI talent is notoriously hard to hire. Not only is there a general disparity between available and needed talent; there is also the fact that the fancy data scientists with the PhDs tend...

* Scaling AI | October 07, 2019 | Lynn Heidmann

Managing Risk in Data Projects

In 2018, O’Reilly conducted a survey regarding the stage of machine learning adoption in organizations, and among the more than 11,000 respondents, almost half were still in the exploration phase....

* Scaling AI | October 02, 2019 | Lynn Heidmann

Get Started with AI in Banking

Starting the path to AI can seem daunting for any business, and banking is no exception. But today's banks that have found success are able to start small and work their way up.

* Scaling AI | September 25, 2019 | Lynn Heidmann

Back to School: The Changing Role of Data in Education

With summer officially over and fall setting in, the back-to-school excitement abounds. I sat down with Josh Hewitt, Director of Academics at Dataiku, and Diane Igoche, Curriculum Development...

* Use Cases & Projects, * Dataiku Company | September 06, 2019 | Lynn Heidmann

Bringing the Human-Centered Touch to AI in Human Resources

AI will bring major benefits to HR, significantly broadening the reach of recruiters and allowing businesses to more effectively scour the Earth for high-quality job candidates. It offers the...

* Use Cases & Projects, * Scaling AI | September 05, 2019 | Lynn Heidmann

Top Use Cases for AI in Banking

Global business information provider IHS Markit predicts that the business value of artificial intelligence (AI) in banking will reach $300 billion by 2030. Here are some of the most promising use...

* Use Cases & Projects, * FEATURED | September 03, 2019 | Lynn Heidmann

Bringing AI Skills to the Classroom

Just in time for the new school year, Dataiku’s latest academic partnership with Teradata University Network (TUN) is set to bring AI tools and skills to the classroom. The program empowers...

* Dataiku Company | August 29, 2019 | Lynn Heidmann

AI Maturity Survey: Where Are We in the Path to Enterprise AI?

With all the media hype and coverage around AI, one might think that every company out there has Enterprise AI all figured out and is extremely mature in their data journey. However, we surveyed...

* Scaling AI, * FEATURED | August 28, 2019 | Lynn Heidmann

Building a Data Pipeline to Clean Dirty Data

A data pipeline is a series of steps that your data moves through. The output of one step in the process becomes the input of the next. Data (typically raw data) goes in one side, goes through a...

* Data Basics, * Use Cases & Projects | August 23, 2019 | Lynn Heidmann

AI vs. Machine Learning vs. Deep Learning

Talking about AI is increasingly complex because it’s often used alongside (or even interchangeably with) the terms machine learning (ML) and deep learning (DL). Why do people use these terms...

* Data Basics, * Scaling AI | August 19, 2019 | Lynn Heidmann

AI in Banking: An Inside Look

We released a white paper in mid-July about the challenges, solutions, and steps to get started with AI in banking, an industry that (like many others) has a lot of the essential ingredients...

* Scaling AI | July 29, 2019 | Lynn Heidmann

How AI is Transforming Banks & Banking

Data has always been the foundation of the banking industry. What has changed in recent years, of course, is the amount of data available and the speed at which it is processed as well as the need...

* Scaling AI | July 15, 2019 | Lynn Heidmann

5 Tips from GE Aviation for Starting a Self-Service Data Initiative

GE Aviation went from data silos to self-service data in just a few years, and now they have more than 1,800 users empowered to use data in their day-to-day work. Here are their top five tips for...

* Use Cases & Projects, * Scaling AI | June 12, 2019 | Lynn Heidmann

Practical Deep Learning

If this month’s Google I/O conference is any indication, then incorporating machine learning (and deep learning) into existing products and processes to make them more efficient or useful is the...

* Data Basics | May 21, 2019 | Lynn Heidmann

How to Create a Data Team

Hype around AI means that more and more, businesses are dedicating huge sums of money to assembling large data teams and setting them loose, hoping they produce results on their own. Often, they...

* Data Basics, * Scaling AI | May 17, 2019 | Lynn Heidmann

How AI Will Change Marketing (and Marketers)

It's no secret that introducing data science, machine learning, automation, and (eventually) AI into the world of marketing will be a critical factor to success. Yet it also means a fair bit of...

* Use Cases & Projects, * Scaling AI | May 13, 2019 | Lynn Heidmann

How Will Machine Learning and AI Change My Organization?

Whether businesses have a specific aversion to change or they simply find change too difficult to manage, the bottom line is that it holds companies back. Yet in the age of machine learning and...

* Scaling AI | May 09, 2019 | Lynn Heidmann

Data Scientist vs. Data Analyst - What’s the Difference?

Whether you’re a student deciding on a career path, a data analyst looking for a change, or a business owner looking to hire data talent, the question of data scientist vs. data analyst (or...

* Data Basics, * Scaling AI | May 03, 2019 | Lynn Heidmann
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