According to a recent press release by the National Retail Federation, “nearly seventy-three percent of consumers celebrating Valentine’s Day this year feel it’s important to do so given the current state of the pandemic.” The release also states that “consumers still feel it’s important to spoil their loved ones in light of the pandemic.” We couldn’t agree more on the importance of celebrating the day.
As your organization begins planning and budgeting for 2021 initiatives, it’s time to take a critical look at your cloud migration strategy. If you’re planning to move your on-premises big data workloads to the cloud this year, you’re undoubtedly faced with a number of questions and challenges.
CDO Battlescars is a podcast series hosted by Sandeep Uttamchandani, Unravel Data’s CDO. He talks to data leaders across data engineering, analytics, and data science about the challenges they encountered in their journey of transforming raw data into insights. The motivation of this podcast series is to give back to the data community the hard-learned lessons that Sandeep and his peer data leaders have learned over the years.
Are you familiar with the emerging discipline known as DataOps (data operations)?
Unravel Data is a leader in the emerging field of DataOps, going beyond application performance monitoring (APM) to provide AI-powered recommendations for big data and streaming data applications. Now Unravel is being recognized by banking technology innovator Credit Suisse AG in their prestigious Disruptive Technology Recognition (DTR) program.
One of the highly anticipated events every year is the keynote from Dr. Werner Vogels at the annual AWS Reinvent conference. As CTO of Amazon, Dr. Vogels has considerable influence on product and engineering innovation that directly impacts hundreds of millions of users and developers. Here are three takeaways from Dr. Vogels’ keynote this year.
Unravel Data recently held its first-ever customer conference, Untold 2020. We promoted Untold 2020 as a convocation of #datalovers. And these #datalovers generated some valuable data – including the interesting fact that more than 60% of surveyed customers have SLAs for either “more than 50% of their pipelines” (42%) or “all of their pipelines” (21%). All of this ties together.
Apache Spark is a fast and general-purpose engine for large-scale data processing. It’s most widely used to replace MapReduce for fast processing of data stored in Hadoop. Designed specifically for data science, Spark has evolved to support more use cases, including real-time stream event processing. Spark is also widely used in AI and machine learning applications.