In our previous blog, we talked about the four paths to Cloudera Data Platform. If you haven’t read that yet, we invite you to take a moment and run through the scenarios in that blog. The four strategies will be relevant throughout the rest of this discussion. Today, we’ll discuss an example of how you might make this decision for a cluster using a “round of elimination” process based on our decision workflow.
With hackers now working overtime to expose business data or implant ransomware processes, data security is largely IT managers’ top priority. And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. Requirements, however, have changed significantly in recent years.
Historically, maintenance has been driven by a preventative schedule. Today, preventative maintenance, where actions are performed regardless of actual condition, is giving way to Predictive, or Condition-Based, maintenance, where actions are based on actual, real-time insights into operating conditions. While both are far superior to traditional Corrective maintenance (action only after a piece of equipment fails), Predictive is by far the most effective.
January 2020 is a distant memory, but for most, the early days of the pandemic was a time that will be ingrained in memories for decades, if not generations. Over the last 18 months, supply chain issues have dominated our nightly news, social feeds and family conversations at the dinner table. Some but not all have stemmed from the pandemic.
Recently, I worked with a large fortune 500 customer on their migration from Apache Storm to Apache NiFi. If you’re asking yourself, “Isn’t Storm for complex event processing and NiFi for simple event processing?”, you’re correct. A few customers chose a complex event engine like Apache Storm for their simple event processing, even when Apache NiFi is the more practical choice, cutting drastically down on SDLC (software development lifecycle) time.
With this first article of the two-part series on data product strategies, I am presenting some of the emerging themes in data product development and how they inform the prerequisites and foundational capabilities of an Enterprise data platform that would serve as the backbone for developing successful data product strategies.
My name is Shanmukha Kota and I am a recent graduate from University at Buffalo. I interned with Cloudera last summer and joined Cloudera as a software engineer a couple of weeks ago and this is my first experience with CDP and CDP Operational Database. For a new hire college graduate in the industry with only academic experience with HBase, I can only say it is very simple and easy to set up and work with CDP Operational Database.
Most businesses, whether you are in Retail, Manufacturing, Specialty Chemicals, Telecommunications, consider a 10% market capitalization increase from 2020 to 2021 outstanding. But what would you say to your shareholders when they found out your competitors’ market capitalization grew 35%?
