How industries are using data analytics to accelerate the digital transformation
The secret sauce for survival relies on extracting the value of data analytics.
Ideas and resources for building a data culture.
The secret sauce for survival relies on extracting the value of data analytics.
Merging the gaps between data science and engineering, and what each side can learn from the other.
4 questions to spark ethical decisions about data.
O'Reilly Podcast: Qubole founder Ashish Thusoo on the importance of self-service data.
The destination and rules of the road are clear; the route you choose to get there makes a huge difference.
Katie Kent and Jonathan Dinu discuss topics you may be asked about in data science interviews, depending on the types of data science jobs you interview for.
In this report, you will learn practices for making good decisions with missing or sketchy information, and advice for surviving (and even thriving) as a data scientist in your organization.
No hype. No fluff. Just skills.
Techniques to tackle data science challenges to future-proof your business.
Prioritizing and evaluating data sources for ROI.
Bob Filbin covers techniques—and failures and successes—in driving behavioral change with data.
Identifying the essential skills for data scientists.
David Boyle argues for a negotiated settlement in the war between data and creative, and he shows how long-term and mutually beneficial peace can work.
Unusual collaborations can often lead to new ways of taking and analyzing data. AnnMarie Thomas looks at lessons learned from working with chefs, circus performers, and preschoolers.
Dinner conversation turns into a career retrospective. Food for thought for leaders and leaders-to-be.
Does Big Data represent an existential threat to CIOs? Yes, quite possibly.
Big data is not just a technology phenomenon. It has a cultural dimension.
To succeed with data, businesses must develop a data culture.
Google requires quid for its quo, but it offers something many don’t: user data access.
This webcast examines a framework for incorporating ideas from other fields (like design, argument studies, and consulting) into Data Science.
Data is here, it's growing, and it's powerful.