Big Data LDN is right around the corner and this year’s event (November 13-14 in London) boasts an impressive roster of speakers including big data visionaries, experts, and real-world data pros sharing insight and tips on how to build dynamic, data-driven enterprises.
It's always great to attend the Strata NYC conference to see what people are working on across the industry. Cazena attended in force this year, with colleagues, partners, customers and friends. We debuted several solution demos, cheered as one of our customers won a notable award and attended sessions. We had a cool booth on the expo floor keeping attendees headache-free with our handy giveaways. Here are my takeaways -- the fun and interesting technical concepts and trends. A few things really stood out this year. As always, there was that one technology that everyone kept asking about.
As Cazena marks the end of our first year post-GA, I am excited that we are seeing over 300% annual growth with our Big Data as a Service. We are seeing interesting patterns across these enterprises.
While the Big Data Hadoop ecosystem has established itself as an production-grade data stack, extracting intelligence from all of this data can also be extremely daunting. Cazena’s VP of Engineering John Piekos discusses the three primary reasons that Cazena’s Data Lake as a Service helps enterprises.
Part our job within Cazena Engineering is to track technology and trends in data science and analytics. We especially enjoy conferences like the recent ODSC East, where we can talk with data scientists and engineers about ways in which the Cazena’s fully-managed cloud stacks for analytics and big data could help them work more efficiently. It’s also a good time to connect with peers. Data science and AI companies are natural partners for Cazena - they build tools and algorithms that leverage our distributed computing system. Conferences are a great opportunity to find out about what’s new, what’s working and what’s on the horizon.
As enterprises seek to drive faster big data outcomes, cloud offers a promising solution for agility. Indeed, public cloud infrastructure is, in many cases, far cheaper and faster to deploy than on-premises alternatives. Yet cloud big data deployments have proven complex for many enterprises, and few companies are ready to call systems officially in production. Reasons range from compliance concerns to integration issues, but there’s a much bigger problem lurking. The real challenge holding back production big data cloud deployments has less to do with the infrastructure or PaaS capabilities: It is the pervasive lack of DevOps skills for big data.
Read our takeaways from a recent Gartner Insight report titled "What CIOs Should Do About Strategic Chief Digital Officers." The Chief Digital Officer title is relatively new, but growing quickly, so it’s worth reviewing the report to get familiar with the emerging definition of the role. We’re offering the research because we’re hearing about more projects with the ‘digital transformation’ label. Several of these projects seem to look a lot like advanced analytics projects, but with ‘transformational’ new branding. Is it just a new label? As the report explains, digital transformation is a big deal, and Chief Digital Officers have different goals than the CIO. The full report is available, complements of Cazena, until March 31, 2018.
At AWS re:Invent today, Cazena announced a concept called AppCloud that allows enterprises to attach innovative analytic or machine learning applications to their enterprise data in the cloud.