Amazon Web Services (AWS) offers dedicated cloud computing services. Their Artificial Intelligence (AI) services are fully managed and require no machine learning (ML) skills.
This article explains AI and ML concepts and provides a review of the AI services offered on AWS..

When you’re building a big data solution, there are many open source components you can choose from. Everything from whole platforms to individual libraries are available, depending on your needs and expertise.

Many of these tools can be freely used regardless of your end product or organizational structure. However, some are restricted by team size, organization type, and purpose..

Most companies have a wealth of user data at their fingertips. This data can provide insights to inform marketing strategies, boost customer satisfaction, retain and attract customers. The key, however, lies in the way marketers collect, analyze, and leverage that data to reach desired goals. Marketing analytics enables marketers to gain actionable insights that drive results.
This article reviews the basic concepts of marketing analytics, including best practices and tools..

Kubernetes provides the automation, orchestration and scalability necessary to maximize cloud ecosystems and productivity in modern companies. More than 5000 companies are now running Kubernetes in production. This article walks you through the main components of Kubernetes and gives you some tips on how to use it in production.

As more developers shift to cloud-native practices, more applications are developed and deployed using containerization. The goal is typically to to enable micro-services architecture, which is highly scalable.

To manage containerization, developers use container orchestration platforms, like Kubernetes. However, it is not only developers who can make use of Kubernetes. Read on to learn how to use Kubernetes for big data.

Endpoints are devices connected to your network, such as smartphones, laptops, routers, and Internet of Things (IoT) sensors. Endpoints enable users to access the network from different physical locations and devices. However, this benefit can turn into a risk when attackers take advantage of endpoints to breach the network. Read on to learn how to secure endpoints with EDR practices and tools..

Backup and recovery are two important mechanisms designed for the purpose of ensuring the continual health of your data. Backups are typically divided into categories that measure level of usage, such as cold storage for archives. The purpose of recovery is to ensure that you have a backup to restore if and when your data is lost. This article offers a review of key Azure backup and recovery services..

Azure provides several services to help companies easily migrate to the cloud. This article offers a review of key tips and tools you can use to ensure a successful migration to Azure. 

Before you start migrating your data..

DB2, from version 9.7, allows to know easily what indexes are not being used in a Database. The query is also for tables and packages.

This is a useful tool for tuning indexes and detecting problems in their use.

After version 9.7 DB2 includes a new LASTUSED field in the SYSCAT.INDEXES, SYSCAT.TABLES and SYSCAT.PACKAGES tables.

This field indicates the date of last use of indexes, tables or packages.

For example, to query unused indexes since 1/1/2019, you could use this simple query:

High-Performance Computing (HPC) enables you to leverage cloud-based supercomputing with the scalability of the cloud. Most major cloud vendors offer HPC services, including Azure, Google, and AWS. In this article, you’ll learn what HPC is and how it works on Azure. You’ll also learn how to deploy and manage Azure-based HPC.