A good database schema is indispensable for making data warehouses work. Get it wrong, and you’ll be in a world of hurt.
Follow these tips to ensure that your database schema delivers maximum utility for data warehouse users, data analysts, and data scientists.
We constantly hear about UX Analytics. Analytics must always be a part of the design process of an app from the very beginning. We also hear tons about UI/UX design. However, and definitely during a redesign, UI and UX changes based on product analytics need to run parallel processes. So how come we never hear about UI Analytics?
We’re excited to announce that we’ve teamed up with Rivery to offer our data pipeline and monitoring solutions in one. Our one-click Data Kits streamline the analytics process, saving teams valuable time so they can act on business incidents fast. To kick things off, we’re releasing the Anodot Marketing Analytics Monitoring Kit. Now you can start tracking your marketing campaigns instantly, and make the moves that will make the most of your ad spend.
With the general availability of Cloudera DataFlow for the Public Cloud (CDF-PC), our customers can now self-serve deployments of Apache NiFi data flows on Kubernetes clusters in a cost effective way providing auto scaling, resource isolation and monitoring with KPI-based alerting. You can find more information in this release announcement blog post and in this technical deep dive blog post. Any customer willing to run NiFi flows efficiently at scale should now consider adopting CDF-PC.
At Snowday 2021, Snowflake announced exciting new product capabilities that expand what is possible in the Data Cloud. In addition to announcing Python support in Snowpark (currently in private preview), these latest innovations make it easier for organizations to maintain business continuity across clouds and regions; help data engineers and data scientists build pipelines, ML workflows, and data applications faster; and remove the complexity of getting the right data into the hands of customers.
