When you deliver product incrementally, in an agile fashion, it is often hard to see, week to week, sprint to sprint, all the great progress made throughout the year. That’s why, at the end of every year, I enjoy looking back at what my teams and company have accomplished the past twelve months. For Cazena it was an exceptional year with triple-digit growth of our customer subscriber base. Behind the curtain, the data paints an interesting picture of what it means to provide this growing customer base with a fully-managed, secure, highly-available big data platform.
We are pleased to announce a new partnership between Cazena and Eden Smith, the leading UK big data consulting and staffing specialist. The companies share a strategic mission of empowering data leaders and accelerating analytic impact. Eden Smith is known for deep market knowledge, strategy expertise and a vetted roster of data and analytics talent, with a specific focus on Chief Data Officers. Cazena’s Big Data as a Service solutions are fully-managed, secured and automated, offering enterprise data lakes, analytics and data science platforms at ½ the cost of alternatives.
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.