Últimas publicaciones en los blogs

10 Tips for a Successful Cloud Migration

"Paradisiac cloud migration"

Migrating applications, data, and other workloads to the cloud is now commonplace among businesses of all sizes. A 2018 report on cloud computing trends revealed that 92 percent of companies now use public cloud services.
However, cloud migration remains a complex undertaking with several challenges, and getting it right is important. Read on to find out the challenges of cloud migration and ten tips for building a smart cloud migration plan..

Understanding Database Cloud Migration

Cloud computing is the new normal. Every time you are using a service or an application through an internet connection, you are using the cloud. Since most companies nowadays have part or all their databases hosted on the cloud, you ask how is the best way to do it. Migrating your database to the cloud can help you manage your workload by making your data available and easily scalable. Read on to learn about database cloud migration and tips to do it right..

Using Machine Learning/AI to Boost the Supply Chain: 5 Use Cases

Industry - AI to boost the Supply ChainThis article will discuss how supply chains are being improved through the use of innovative technologies before highlighting five uses of artificial intelligence and machine learning in supply chains.

When you finish reading, you’ll understand why many industry analysts have described A.I. technologies as disruptive innovations that have the potential to alter and improve operations across entire supply chains..

Open Source for Big Data: An Overview

Software Open SourceThis article will describe the relevance of open source software and big data before describing five interesting and useful open source big data tools and projects.

Big data workloads are those that involve the processing, storage, and analysis of large amounts of unstructured data to derive business value from that data. Traditional computing approaches and data processing software weren’t powerful enough to cope with big data, which typically inundates organizational IT systems on a daily basis.

The widespread adoption of Big Data analytics workloads over the past few years has been driven, in part, by the open source model, which has made frameworks, database programs, and other tools available to use and modify for those who want to delve into these big data workloads..