Ringing in the new year with new goals for data literacy? The right data management strategy can help democratize access to analytics across your entire team, without the need for a data scientist or data engineer to act as an intermediary or bottleneck. As you examine your people’s data skills and related data literacy training processes, it might be time to consider a new approach to data analytics technology that facilitates data democratization in 2022. That’s right, your platform.

When using Heroku, it is common practice to transfer or back up data to external locations. While there are many steps in this process, creating an efficient pipeline is relatively simple once you understand all the moving parts. In this article, we show you how to migrate data from Heroku to Amazon S3. In this particular case, we will be connecting and transferring Salesforce data.

In the ever-changing world of business, data is becoming more important than ever before. As data earns a more prominent role in business, the way in which organizations handle their data also becomes a bigger concern. If your organization has been looking for a better way to move, transform, and interact with data, then you need to check out the cloud-based data integration solutions of Dell Boomi and Integrate.io.

Simply put, data migration is the process of moving data from one location to another. While the concept is easy to understand by itself, things become a bit more complicated when actually trying to implement data migration within a business. In the ever-changing business landscape, data is becoming more important than ever. In fact, in the new data-driven business world, understanding data migration and learning how to implement it is becoming vital among businesses.

As digital ecosystems become more complicated, some organizations assume that they need expensive ETL (extract, load, transform) platforms to unify data sources. While an ETL platform can offer robust features, you probably don’t need an entire system dedicated to unifying data from diverse CRMs. The right API solution can simplify your approach to real-time data unity. Plus, you don’t have to spend extra money on a high-cost platform.

When companies realized data was a resource and not just the by-product of sales, they began to offer customers additional value: free products, savings, money back, even a club-like exclusivity. They often did it, and still do it, with customer loyalty programs, which were frequently expressed in the form of a physical card, such as Starbucks Rewards and MyPanera. But the very biggest companies have changed the loyalty game.

My grandmother used to say, ‘There’s more than one way to bake a cake.’ It’s a softer version of the more famous idiom involving feline taxidermy, but for our purposes, it’s a better metaphor. You can bake a cake without some of the key ingredients like sugar or eggs and it is still technically a cake. It just won’t taste as good as my grandmother’s cake did.

I have written many a post about the importance of keeping your data moving. As Mathew Wilder sang in “Break My Stride,” it’s “got to keep on moving” to enable you to act within the business moment. Real-time data analytic pipelines are the solid foundation to achieving the state of Active Intelligence, and you can only start that when you work on the freshest data available to you.

Here at CodeZero we know that our developer platform for Kubernetes can lead to a 10x increase in productivity, and so we promote that fact proudly. "But wait!" you say. It's one thing to make that claim, but another to demonstrate exactly how this boost in productivity is achieved.