The IBM Integrated Analytics System (IIAS), is a unique, cloud-ready appliance and machine learning platform wields the power of an in-memory, massively parallel processing database engine with embedded Spark. It also runs on market-leading IBM Big Data Servers and IBM FlashSystem 900 storage
Information analytics has never been a “one size fits all” proposition. That applies to the hardware and software technologies organizations employ, the information being parsed and the goals of specific projects.
Upon reading his own obituary in the newspaper, famed author Mark Twain is said to have remarked that reports of his death were greatly exaggerated. I can only imagine that if the data warehouse appliance were a 19th century American novelist, it might say the same thing. For a while now,
Dealing with slow technology is a major concern for anyone who needs quick access to analytic insights. For this reason, it’s vital to have a data warehouse appliance with sufficient speed that allows all users to make the most of its analytic power.
According to several research firms, 70% of traditional data warehousing/Business Intelligence projects were considered failures. Fundamental to every data warehousing project is a basic and simple concept – “data integration.” Data integration technology became fundamental as data complexity,
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.
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:
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