Blogs

Sr. Technical Marketing Analyst

In this post, I will explore the most important of the golden rules of appliances - appliances are easy to use. For my discussions of the first two rules, see my previous posts appliances are Plug and Play and appliances are purpose-built.

Sr. Technical Marketing Analyst

In my previous post, I defined a framework by which to evaluate the appliance claims of data warehouse and analytic vendors. These truisms, which I have come to refer to as the golden rules of appliances are:

Sr. Technical Marketing Analyst

The term "appliance" is liberally used by many vendors in the big data space these days. It seems that almost everyone has latched onto the term and it is being used not only to define data warehousing and analytic product offerings, but also to subtly (or not so subtly in some cases) set customer expectations about the underlying ease of deployment and ongoing cost of ownership associated with the product.

VP Product Management & Marketing

This morning, I’m posting from the floor of Oracle Open World at the Moscone Center in San Francisco – and no, this is not yet another blog about Mark Hurd teaming up with Larry Ellison. Rather, it seems pretty safe to assume that if you’re reading this today, you’ve already heard some bit of the news of announcement by IBM and Netezza to enter into a definitive agreement for IBM to acquire Netezza. If not, then I’ve just “broken” some news to a small subset of my readers.

This is a watershed day for Netezza. I think both IBM and we look to this prospective merger as a way to take analytics mainstream by extending the IBM portfolio of workload optimized offerings. The complementary nature of IBM’s and Netezza’s existing relationship makes this ideal for our employees, customers and shareholders. Netezza appliances are developed on IBM’s systems technology and combined with IBM software they power hundreds of clients’ enterprise applications around the globe. Quoting our CEO Jim Baum, Netezza’s, “appliances have set the standard for performance and simplicity in data warehousing and analytics.”