Systems | Development | Analytics | API | Testing

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.

In traditional data warehouses, specific types of data are stored using a predefined database structure. Due to this “schema on write” approach, prior to all data sources being consolidated into one warehouse, there needs to be a significant transformation effort. From there, data lakes emerge!

Over the past two decades, marketers have faced an uphill battle in trying to turn marketing into a fully data-driven discipline. Our challenge is not that we don’t have enough data but that data has been difficult to access and use. Marketing, sales, and product data is scattered across different systems, and we can’t get a complete picture of what is going on in our businesses.

Business intelligence (BI) is the art of extracting actionable insights from your datasets. There’s a whole stack of technologies under the hood.

Every day, hundreds of thousands of residents and commuters in San Francisco, California, use the public transportation services of the San Francisco Municipal Transportation Agency (SFMTA). In addition to the city’s buses, subway system, and famous cable cars, the SFMTA manages comprehensive services including bicycle and e-scooter rentals, as well as permits for road closures.

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.

Earlier this year at Snowflake Summit 2021 , we announced Snowpark Accelerated , a new program for partners who integrate with Snowpark. It provides them with access to technical experts and additional exposure to Snowflake customers. It’s been incredibly exciting to watch what our partners have been building with the help of our new developer experience, which brings deeply integrated, DataFrame-style programming to the languages developers like to use.