Articles

In the last post of this multi-part series, we introduced methodologies and technologies for the various compliance personas to collaboratively author compliance artifacts such as regulation catalogs, baselines, profiles, system security plans, etc. These artifacts are automatically translated as code in view of supporting regulated environments enterprise-wide continuous compliance readiness processes in an automated and scalable manner. These artifacts aim to connect the regulatory and standards’ controls with the product vendors and service providers whose products are expected to adhere to those regulations and standards. The compliance as code data model we used is the NIST Open Security Controls Assessment Language (OSCAL) compliance standard framework.

Our compliance context here refers to the full spectrum of conformance from official regulatory compliance standards and laws, to internal enterprise policies and best practices for security, resiliency, and software engineering aspects.

Source de l’article sur DZONE

NoSQL data sets arose in the latter part of the 2000s as the expense of storage drastically diminished. The days of expecting to create a complicated, hard to-oversee data model to avoid data replication were long gone and the primary expense of programming and development was now focused on the developers themselves, and hence NoSQL databases were brought into the picture to enhance their productivity.

As storage costs quickly diminished, the measure of data that applications expected to store increased, and the query expanded as well. This data was received in all shapes and sizes — organized, semi-organized, and polymorphic — and characterizing the schema ahead of time turned out to be almost incomprehensible. NoSQL databases permitted the developers to store colossal measures of unstructured data, providing them with a ton of flexibility. 

Source de l’article sur DZONE


Introduction

If selling products online is a core part of your business, then you need to build an e-commerce data model that’s scalable, flexible, and fast. Most off-the-shelf providers like Shopify and BigCommerce are built for small stores selling a few million dollars in orders per month, so many e-commerce retailers working at scale start to investigate creating a bespoke solution.

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