May 30, 2017 Comments Off on Speaking at Graph Day 2017 in SF
I’ve been a database technologist for more than 25 years. During that time, I’ve been fortunate to observe the rise (and longevity) of relational database platforms, along with the more recent advent of NoSQL solutions. I’m particularly excited about the potential for graph databases: I believe that they’re going to transform the way information is processed. In fact, WiseClouds will shortly be announcing a series of training courses dedicated to the highly capable OrientDB multi model database.
If you’re in the San Francisco Bay Area, and would like to learn more about what graph databases can do for you, be sure to attend Graph Day 2017. I’ll be joining many other speakers to help you explore the full range of fascinating applications built on graph databases. You can register here.
March 4, 2017 Comments Off on Helpful article on Apache Spark with use cases
I recently wrote Spark for Dummies in partnership with IBM. For those curious about this highly interesting and innovative technology – and the numerous scenarios where it can add value – there are increasing numbers of helpful online resources. A good example of what I mean is a recent article by Radek Ostrowski from Toptal. He provides a concise Spark overview, along with some sample use cases.
I’ll continue to cross reference online resources like this as I run across them. If you’d like to read more about all things Big Data, be sure to check out some of my other related postings.
July 18, 2016 Comments Off on Presenting a Webinar on Delivering Data Security with Hadoop and the IoT
On August 9, I’ll be teaming with Reiner Kappenberger from Hewlett Packard Enterprise to explore some of the most pressing security implications of Hadoop and the Internet of Things (IoT). Hosted by the IT GRC Forum, here’s what we’ll be covering:
The Internet of Things (IoT) is here to stay, and Gartner predicts there will be over 26 billion connected devices by 2020. This is driving an explosion of data which offers tremendous opportunity for organizations to gain business value, and Hadoop has emerged as the key component to make sense of the data and realize the maximum value. On the flip side the surge of new devices has increased potential for hackers to wreak havoc, and Hadoop has been described as the biggest cybercrime bait ever created.
Data security is a fundamental enabler of the IoT, and if it is not prioritized the business opportunity will be undermined, so protecting company data is more urgent than ever before. The risks are huge and Hadoop comes with few safeguards, leaving it to organizations to add an enterprise security layer. Securing multiple points of vulnerability is a major challenge, although when armed with good information and a few best practices, enterprise security leaders can ensure attackers will glean nothing from their attempts to breach Hadoop. In this webinar we will discuss some steps to identify what needs protecting and apply the right techniques to protect it before you put Hadoop into production.
If you’d like to join us, register here.
August 27, 2015 Comments Off on Not scared of algorithms? Perhaps you should be.
A while back, I wrote about a run-in I had with a rental car company, or to put it more accurately: a rental car company’s algorithm. It’s quite frightening to think about the implications of “lights-out” algorithms making important decisions that can affect all aspects of your life. And as someone who witnesses – first hand – the often abysmal job that enterprises do when testing their APIs (which frequently have algorithms running beneath the covers), I’m particularly concerned about what this will spell for the future.
If you’d like to learn more about these possible repercussions, check out the extremely well written article by Frank Pasquale on aeon.co.
Cyberspace is no longer an escape from the ‘real world’. It is now a force governing it via algorithms: recipe-like sets of instructions to solve problems. From Google search to OkCupid matchmaking, software orders and weights hundreds of variables into clean, simple interfaces, taking us from query to solution. Complex mathematics govern such answers, but it is hidden from plain view, thanks either to secrecy imposed by law, or to complexity outsiders cannot unravel.
If you’d like to read more of my posts about Big Data, click here.
July 11, 2015 Comments Off on Poshly – one of Fast Company’s 10 Most Innovative Big Data Companies – is growing
I’ve long been a fan of practical usages of Big Data: applications that aggregate raw information – and lots of it – to address real-world business challenges. I’ve already written about Poshly (disclosure: I’m an investor), and I continue to be impressed with their progress.
Poshly is expanding their team by hiring a lead front-end engineer and deployment specialist, so if you – or someone you know – is interested in joining a winning team in a hot space, I encourage you to check out these opportunities.
February 17, 2015 Comments Off on Fast Company names Poshly one of the Top 10 Most Innovative Companies in Big Data
I blogged about Poshly some time ago. One reason that I invested in them was that they’re a great example of employing Big Data to answer real-world questions, rather than just vacuuming up a bunch of information and trying to find a use for it.
Bradley Falk, Poshly’s CTO and co-founder states:
The great thing about beauty and personal care data is discovering how unique everyone is. We can create a portrait of a user in near realtime and discover how the small details can vary so much. We can react to trends, interests and sentiment to create value for both the consumer and the industry while protecting the user’s personal information.
As I’ve watched Poshly’s meteoric growth, I’ve been interested about the approach they would follow to maintain scalability. According to Matthew Drescher, Poshly’s Head of Data Engineering:
We are aggressively utilizing high performance, distributed in-memory computing techniques to vectorize our data, perform in-place analytics, and paint a landscape of insights for our customers to enjoy.
With the quality of data Poshly gathers, it is possible to take a very geometric approach to generating insights. It’s less like scraping through a haystack in search for a diamond than it is trying to realize the maximum realistic photo resolution.
If you’re interested in all things Big Data, stay tuned for a series of blog posts I’ll be writing on critical algorithms that should be part of your toolkit.
August 31, 2014 Comments Off on Poshly: a great practical example of Big Data in action
With any new innovation, hype can often outstrip results, especially in the early days. A few years back, we saw this with Service Oriented Architecture (SOA): it had lots of promise, but there were relatively few examples of successful implementations. Nowadays, SOAP and REST services – supported by the principles of service orientation – are the primary techniques that distributed applications use to communicate. This has led to all sorts of innovative solutions, especially when pairing these services with mobile devices.
The same things are happening in Big Data: you hear about it all the time, but it’s natural to wonder how it’s being used to add value. Unsurprisingly, new technologies are often viewed as solutions in search of problems, and this is particularly relevant for Big Data since it’s such an all-encompassing discipline.
For Big Data, it’s always useful to look for practical applications: first define the problem, and then use Big Data to supply the solution. Poshly is a textbook example of what I mean: Big Data technologies and practices are being applied to meaningful problems, thereby helping customers answer questions that were very difficult to resolve prior to these advances.
Disclosure: I’m an investor in Poshly through my participation in Astia Angels, an organization I encourage you to check out. Poshly recently closed a $1.5MM investment, which you can read about here at TechCrunch.
Poshly’s website offers a variety of beauty product giveaways which consumers can compete to win by answering personal questions about their beauty routines, habits, interests, and more. The data these questions generate is highly personalized, but only shared with Poshly’s brand customers after being anonymized – meaning users’ personally identifiable information is removed, like their name, email or address. This “hyper-personal data,” as CEO Doreen Bloch calls it, helps brands better understand their customer base in general, or influence larger decisions, like what retail channel to roll out to next, for example.
I’m increasingly learning about dynamic startups like Poshly that are finding realistic uses for Big Data. As time goes by, I suspect that eventually we’ll stop using the term Big Data, and depict it instead as just plain “data” as we portray the exciting ways that information is being put to work.