Entries by dbeyer@chart.io

Big Data is all the rage these days, judging from the press, analyst reports and the endless webinars in my spam folder. Just as with every other mega-trend in technology, the hype is partly justified and partly not.

What is Big Data?

Sprawling amounts of data are being generated across quite a range of sources and media: financial transactions, weather data, health data, social data, sensor data, mobile data, geo-location data, search data, and the list goes on.

Some of this data, particularly the unstructured kind, is not very suited to traditional tools, mainly, the relational database. But as certain ...

We're incredibly pleased to announce that Dave Fowler, Chart.io's Co-founder and Chief Technology Officer, has been selected as part of Forbes Magazine's 30 Under 30. The full list is available here.

The various top 30 lists were broken down into categories, including Technology, Science, Entertainment and others. In technology, the finalists ranged from startup co-founders to Quantum computing experts.

It is really an honor to be selected as part of such a talented and accomplished group, which includes Jeff Hammerbacher, Chief Science Officer of Cloudera (and Chart.io investor), as well as fellow Y Combinator Alumni ...

Today we're announcing permissioning, a new feature that will give our customers more granular control over what their teammates can and can't do with Chart.io.

With permissioning, Chart.io project administrators can now assign teammates to one of three roles:

Admin

Admin users can do, well, everything. That includes creating dashboards, adding datasources, determining access for other users -- basically anything that's possible with Chart.io.

Creator

Creators have a medium level of access. They can add new charts, modify existing ones, edit schema and add new dashboards. But unlike admins, they can't add new datasources ...

_This past week, we sat down with Monica Rogati, one of the founding members of the LinkedIn Data Science team. Monica obtained her PhD in Computer Science from Carnegie Mellon, where she focused on text mining and applied machine learning. At LinkedIn, she is pioneering data driven products with multi-million dollar business impact, and is currently building mathematical models that power LinkedIn’s personalized recommendations.

Please note: because we weren't able to record the conversation, this interview represents my recollection and paraphrasing of what Monica said. None of these quotes are direct.

Chart.io: So how’d you get ...

Yesterday may have been a holiday, but we sure haven't been resting here at Chart.io. In fact, we spent a good chunk of the summer squashing bugs and streamlining our code to make Chart.io faster and more stable than ever.

Some improvements you might notice right away, while others reside under the hood. Highlights include:

• Design unification. We've made interface tweaks throughout the site to ensure a consistent look and feel.

• Better error handling. We've greatly improved our inline error reporting, showing you details about snafus like SQL errors as they happen, so you can ...

The landscape of Business Intelligence solutions is changing.

While BI used to be the domain of a few large technology companies offering one-size-fits-all solutions, customers are increasingly turning to lighter-weight, more customizable software for their BI needs.

In a recent interview, Donald Farmer, the former program manager of Business Intelligence at Microsoft, noted that the "megavendors" in the space -- IBM, Oracle, and the like -- simply aren't interested in selling standalone BI solutions.

"They are selling an entire stack of software," Farmer told Computer Business Review. "It's not about selling BI. It's about selling the entire infrastructure that ...

Here at Chart.io, we know that good design is crucial.

That's why we're particularly excited to launch our fully-redesigned, dare-we-say-beautiful homepage, which elegantly and effectively conveys what we're all about.

Some highlights of the new site include:

One-page design

No need to navigate from page to page -- all the information you want is right here. Just click any of the top menu items, and the homepage quickly and fluidly scrolls to your chosen topic.

Chart.io is committed to making the content you want as accessible as possible, and now our homepage is no exception.

Clean ...

Anita Lillie is a data visualization designer at LinkedIn. Before LinkedIn, she spent time at the Nokia Research Center in Palo Alto for the Data Insight group. Her masters thesis work at the MIT Media Lab (in the Hyperinstruments group) looks at music as data in order to create maps of music libraries. We had the opportunity to sit down and speak with her about her work and her thoughts about the world of data visualization.

Chart.io: If you took a snapshot of the data visualization industry right now, what would you see?

Anita: It's both an exciting ...

The following post is guest written by Nick Diakopoulos, a data viz whiz who graduated from the School of Interactive Computing at the Georgia Institute of Technology in 2009 with a PhD in Computer Science. His interests currently lie at the intersection of human computer interaction (HCI), information visualization, and automatic content analysis with themes from media including journalism, collaborative authorship and annotation, and games. Check out some of his recent projects.

Visualizations are typically used to serve one of two basic purposes. They either help us explore and understand our own data, or they help communicate the meaning of ...

Amid all the generalizations and prescriptions about how executives, their analysts and others in a company should produce and consume reports about their company's metrics/data, I was naturally curious to find a more scientific take on the matter. To shed some light on this matter, I explored research done by Peter Pirolli and Stuart Card. They have studied information gathering and consumption in the high stake setting of national security and intelligence activities. Their insights can effectively be applied to more traditional business settings. Pirolli and Card model the information lifecycle as beginning with the gathering stage, then ...