In this series of blog posts, we will showcase an end-to-end hybrid cloud ML workflow using the Iguazio MLOps Platform & Feature Store combined with Azure ML. This blog will be more of an overview of the solution and the types of problems it solves, while the next parts will be a technical deep dive into each step of the process.

Read this hands-on guide to learn how to use the Bitrise Test Report add-on to visualize your test results for your development team!

Choosing the right data warehouse is a critical component of your general data and analytic business needs. One of the biggest questions that businesses ask when choosing their data warehouse providers is this: Should you use Snowflake, Amazon RedShift, or Google's BigQuery data warehouse for your business needs? We've already covered Amazon RedShift vs. Snowflake and Google BigQuery vs. Snowflake, but what about Amazon RedShift vs. Google BigQuery?

When it comes to cloud data integration there are many benefits. However, although there are many benefits of cloud data integration for your company, it also comes with its own set of challenges. In the business world of today, cloud technologies have become increasingly more important in the evolving business and IT landscapes. Cloud technologies are used more and more because of the convenience, performance and cost-effectiveness they provide to companies compared to on-premises solutions.

In this article, we give you some tips to successfully transform Mobile DevOps processes in your e-commerce app and to minimize your revenue loss.

Communication is the key to managing the stakeholders. Many times, not enough efforts are made to communicate clear details, status, risks on the ongoing projects. On the other hand, not everyone can detail every important aspect or gauge what’s important to communicate without being subjective and setting aside all emotions during communication.

In 2021, many organizations on a digital transformation journey sought cloud-native data management and analytics solutions that could facilitate search and analytics on their data in the cloud. Many of them are already running on the AWS cloud, so naturally, they turned to the AWS Partner Network to find technologies that could easily plug into their cloud stack, solve tactical pains, and deliver value quickly.

Most data science projects don’t pass the PoC phase and hence never generate any business value. In 2019, Gartner estimated that “through 2022, only 20% of analytic insights will deliver business outcomes”. One of the main reasons for this is undoubtedly that data scientists often lack a clear vision of how to deploy their solutions into production, how to integrate them with existing systems and workflows and how to operate and maintain them.