B23 Data Platform: Enabling Data

February 12th, 2016 I’ve spent my career working on data problems and building data products. During this time, I’ve spent a lot more time fumbling with infrastructure and moving data than I’ve spent performing value-add data science or data analytics. I learned to live with those frustrations, and my customers learned to live with the amount of time it took to ask a question of a new dataset. As a result of these experiences, I’m very excited to introduce B23 Data Platform to people like me and stakeholders like mine. In our previous post (Welcome to B23 Data Platform, the Next Big Thing in Big Data) we introduced several of the main concepts for the rationale of why we built B23 Data Platform. In this blog, I’ll show you you how we use them. As a data scientist, I should not have to have to worry about arcane items like private subnets, bastion hosts, and internet gateways. However, somebody in my enterprise does worry about those things. With B23 Data Platform, I have the confidence that I’m protecting my resources without getting in the way of completing productive work. A Space embodies the set of secure infrastructure resources within your preferred cloud provider. These secure cloud resources will host your data pipeline(s). We use industry best practices to lock down these assets, and we create these assets in your cloud account. You have complete control and transparency over your resources and data. To create a Space you simply login, choose your cloud provider, give the Space a name, and enter your credentials. A few minutes later, you have a running Space. It is that simple. Steps to Create a Space The big data and data science ecosystem has become very crowded with tools. Tools exists for a reason. Some are easy to differentiate, while the distinction between others is much more nuanced; this offers both challenges and opportunity. The challenge stems from the paradox of choice. However, the opportunity exists to build a data application that is tailored exactly to your business needs. We enable data scientists by...

Welcome to B23 Data Platform, the Next Big Thing in Big Data!

January 28th, 2016 B23 Data Platform is a new and innovative software solution that allows end-users to launch complex “Big Data” distributed processing clusters with a few clicks of the mouse. We call these distributed processing systems Stacks. Examples of Stacks include Hadoop, Kafka, Storm, Spark, Zeppelin, Metron, Elasticsearch, H2O, etc. Using B23 EasyIngest capability, these Stacks can be automatically populated with user-selected data sets during the provisioning process, eliminating the need to manually build a data pipeline. The entire process from start to finish is a few minutes long. B23 Data Platform can launch one or many different stacks simultaneously, all ingesting similar or different sets of data in a secure Space in the Cloud. Terminating Stacks is just as easy. During a recent sales meeting demonstrating B23 Data Platform, a potential enterprise customer told us that he was having an emotional experience and that he had “dreamed of something like this for a long time.” Well, we’ve been dreaming about this for a while too! This is one of many positive reviews since we launched our private beta only a few weeks ago. We are so excited to launch B23 Data Platform to a broader audience to share what makes this software solution so special. Along our journey over the past several years almost every one of our customers expressed a common desire which was “We hired really talented analysts/data scientists/quants to analyze our data to derive strategic insight, and too often they are stuck in the Hadoop cluster fixing some configuration or system setting. How do we fix this?” B23 Data Platform was designed and built by analysts for analysts. Ironically, very few of our “developers” are traditional computer scientists although we all share a passion for software development and data. Customers have been asking for a repeatable deployment methodology, consistent “look and feel”, and a user interface that “boiled down” a seemingly endless number of configuration parameters to choices that intuitively made sense to...