O'Reilly on Data
AUGUST 24, 2018
Carol Willing shows how Jupyter's challenges can be addressed by embracing complexity and trusting others. Continue reading Sustaining wonder: Jupyter and the knowledge commons.
IBM Big Data Hub
AUGUST 21, 2018
On September 13, Rob Thomas together with ESPN anchor Hannah Storm, will lead a discussion around the transformative potential of AI, the importance of a multi-cloud architecture — and how companies representing a range of industries – from manufacturing to health care — are winning with AI. Attend in person in NYC and enjoy intimate networking and learning sessions – or alternatively catch the Livestream from your home or office.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Birst BI
AUGUST 23, 2018
How many times have you wished for more hours in the day so you can complete more tasks? A key goal of AI or machine learning automation is to have machines complete tasks for you, freeing up time so you can focus on the more complex, higher-value tasks. However, there are simply not enough data scientists in the world to deliver on the AI potential.
Peter James Thomas
AUGUST 18, 2018
No this article has not escaped from my Maths & Science section , it is actually about data matters. But first of all, channeling Jennifer Aniston [1] , “here comes the Science bit – concentrate” Shared Shapes. The Theory of Common Descent holds that any two organisms, extant or extinct, will have a common ancestor if you roll the clock back far enough.
Advertisement
Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.
O'Reilly on Data
AUGUST 24, 2018
Julia Meinwald outlines effective ways to support the unseen labor maintaining a healthy open source ecosystem. Continue reading Why contribute to open source?
IBM Big Data Hub
AUGUST 21, 2018
The forces of nature can be unpredictable. Businesses & organizations can pull substantial value our of weather data through advanced analytics, machine learning & AI.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Peter James Thomas
AUGUST 22, 2018
The interviews that I conduct with leaders in their fields as part of my “In-depth” series have hopefully brought a new and interesting aspect to this site. However, often the boot is on the other foot and I am the person being interviewed about my experience and expertise in the data field and related matters [1]. Maybe interviewing other people helps me when I am in turn interviewed, maybe it’s the other way round.
O'Reilly on Data
AUGUST 24, 2018
Mark Hansen explains how computation has forever changed the practice of journalism. Continue reading The reporter’s notebook.
Hurwitz & Associates
AUGUST 23, 2018
By Jean S. Bozman. IBM is targeting multicloud storage as a growth area for its IBM Storage systems and IBM software-defined storage products. On Aug. 14, 2018, the company expanded multicloud support across its portfolio of software-defined infrastructure (SDI) solutions. The announcements build on earlier IBM Storage announcements for products, features and solutions for simplified backup and recovery, object storage through IBM Cloud Object Storage, and support for scalable clusters in cloud
Nutanix
AUGUST 21, 2018
The heartbeat of a company is its people. With greater diversity, comes greater opportunity too, as was famously said by Malcolm Forbes, the American entrepreneur, “think independently together,” and attack business challenges from a variety of valuable perspectives.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
Peter James Thomas
AUGUST 22, 2018
© Randall Munroe of xkcd.com – Image adjusted to fit dimensions of this page. Work by the inimitable Randall Munroe, author of long-running web-comic, xkcd.com , has been featured (with permission) multiple times on these pages [1]. The above image got me thinking that I had not penned a data visualisation article since the series starting with Hurricanes and Data Visualisation: Part I – Rainbow’s Gravity nearly a year ago.
O'Reilly on Data
AUGUST 24, 2018
Luciano Resende explores some of the open source initiatives IBM is leading in the Jupyter ecosystem. Continue reading Jupyter in the enterprise.
Jedox
AUGUST 20, 2018
Whether you work for a government agency, a high-tech company or a service provider, your organization must plan its annual budget. While many members of your organization might be familiar with planning or budgeting software, the set of activities to create, control and update the budget is known as the budget process. Digitalization is tactical – automating activities, for example, while Digital Transformation is strategic – focusing on improving overall business processes and increasing busin
O'Reilly on Data
AUGUST 24, 2018
Watch keynotes covering Jupyter's role in business, data science, higher education, open source, journalism, and other domains, from JupyterCon in New York 2018. People from across the Jupyter community are coming together in New York for JupyterCon. Below you'll find links to keynotes from the event. All the cool kids are doing it, maybe we should too?
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
Expert insights. Personalized for you.
101 
Let's personalize your content