Systems | Development | Analytics | API | Testing

In 2022, retailers are still dealing with the lasting impacts of the global pandemic, including a decreased workforce, supply chain disruptions, and surging inflation. At the same time, now is the chance for a “long overdue great retail reset” that could promote stability and profitability, according to a recent Deloitte report.

At the DataOps Unleashed 2022 conference, Google Cloud’s Head of Product Management for Open Source Data Analytics Abhishek Kashyap discussed how businesses are using Google Cloud to build secure and scalable data platforms. This article summarizes key takeaways from his presentation, Building a Scalable Data Platform with Google Cloud. Data is the fuel that drives informed decision-making and digital transformation.

Businesses and organizations of all types have embraced cloud integration to transform data into business intelligence. The reason for this is simple: more and more business operations are happening in hybrid cloud — or even fully cloud-to-cloud – environments, and without proper tools to manage data in the cloud, data can become siloed, overlooked, or lost altogether.

Five things you should know about Azure Synapse Analytics: Azure Synapse Analytics is a scalable, cloud-based data warehousing solution from Microsoft. Upon its launch, Microsoft described it as “the next iteration of Azure SQL Data Warehouse.” In addition to offering all of the technology and features of that platform, Azure Synapse also incorporates business intelligence, data analytics, and machine learning tools for both relational and non-relational data.

Experts from Microsoft, WANdisco, and Unravel Data recently outlined a step-by-step playbook—utilizing a data-driven approach—for migrating and managing data applications in the cloud.

Many companies find that it is not enough to simply keep up with the competition in their industry. Such well-known organizations as Amazon and Microsoft continually expand their service offerings, making it hard to compete. Innovation continues to be a huge buzzword in the software industry. Tech companies need a reliable way to provide clients with what they need most, which is service wherever and whenever they need it. One industry that does this best is the SaaS (Software as a Service) space.

SQL is one of the most widely adopted domain languages (i.e., used by over 65 percent of data scientists and analysts), which can help you access and interpret valuable data from AWS Redshift. As a modern-day decision-maker, AWS Redshift and SQL are vital components that drive your SDK. Through PostgreSQL, you can make data-based decisions with Amazon Redshift while minimizing the overall cost of your operations.

AWS Redshift and RDS are two different database products that AWS offers. If you're not sure which one is right for you, there are a few essential questions to answer before making your decision. This article will explore the differences between these two products and help determine which one would be best for your needs. We'll also take a look at how much it costs to use each product so that you can compare them side-by-side and see what's most affordable for your business.