Aiven for Apache Kafka® Moving the data infrastructure of your service or app from an on-prem model into a managed cloud service comes with risks. These ones you can't ignore.
Prescient Devices focuses on changing the way businesses think about and use edge data and industrial IoT. The company built Prescient Designer, an edge data solutions platform that gives organizations the boost they need to transform their IT/OT processes. Prescient’s products empower data engineers, system integrators, and innovators to easily design and orchestrate edge-to-cloud data solutions.
There are few organizations left today without some of their business operating in the cloud. A recent IDG Cloud Computing Study found that 92% of businesses globally moved to the cloud. According to Gartner, cloud adoption spending will surge to about $482 billion by the end of 2022. Most companies make the move to take advantage of the speed, innovation, and flexibility offered by cloud computing solutions. Operating in the cloud can also provide cost savings and improved productivity.
Wherever your move to a managed cloud database service starts, the big questions are pretty similar. Start figuring it out right here.
At this point we are well past the third installment of the trilogy, and at the end of the second installment of trilogies. You might be wondering if the second set of trilogies was strictly necessary (we’re looking at you, Star Wars) or a great idea (well done, Lord of the Rings, nice compliment to the books). Needless to say, detecting anomalies in data remains as important to our customers as it was back at the start of 2018 when the first installment of this series was released.
Although both data lakes and data warehouses are commonly used to store large amounts of data, the phrases are not interchangeable. A data lake is not a straight substitute for a data warehouse; rather, they are complementary technologies that serve a variety of use cases, some of which overlap. Most companies that have a data lake also have a data warehouse. The two methods of data storage are sometimes mistaken, yet they are vastly different.
