Michael Grover

HTML, short for HyperText Markup Language, is the simple language at the heart of the World Wide Web. Created in 1989 by computer scientist Tim Berners-Lee, HTML was originally considered to be a solution to help scientists at the CERN Laboratory in Geneva, Switzerland.

The first website went live in August 1991. It was a page written by Berners-Lee explaining how to write HTML. To say it caught on rapidly is an understatement. Within just a few years of that first HTML document being published, there were already millions of sites, each of them written in HTML.

HTML’s simplicity is not all it has going for it. Where many languages crash when they hit an unrecognized tag, HTML simply ignores anything it can’t understand. Beyond that, HTML has been able to evolve over time to embrace the design values of CSS and morph into a Semantic language designed to be read and understood by machines and humans alike.

The shift to remote and hybrid work over the past year and a more mobile workforce has made the matter worse, as attacks rose and workers became more susceptible. More than half (51%) of respondents to The State of Email Security 2021 report (SOES) reported an increase in BEC attacks that exploited brand impersonation, and 63% reported an increase in phishing attacks that targeted their employees. SOES research also discovered that employees were clicking on unsafe URLs in emails three times more often than they were before the onset of the COVID pandemic. This is significant because it means that cybercriminals are getting more opportunities to worm their way into company systems.

In the data mart model, marketing, sales, finance and each operational business unit has access to the segment of the data warehouse and the information that is most relevant to them. Instead of live queries run against mammoth tables, queries run through a data mart are tight and targeted — and fast. Just as important, data marts provide frameworks to deliver actionable reports more rapidly.

The result: groups within a business can make more efficient use of the data that helps them run.

Take, for instance, the complex but necessary issues of globalization. Growing companies that have international markets in their sights will need their accounting software to seamlessly integrate multiple currencies, multiple tax jurisdictions, and multiple languages.

But the key to the difference between ERP and simple accounting software goes well beyond features which can come and go. The true value of ERP over simple accounting software lies in the comprehensive nature of ERP: resource planning for the entire enterprise.

...structured data can be defined as a controlled and hierarchically organized vocabulary used to describe and classify entities, be they news articles or a business’s products and services.

In organizations, structured data helps make information more accessible and easier to analyze, leading to deeper insights.

On the internet, it helps make information and web pages become more discoverable.

Structured data can be used to aid in content analysis, speed up on-site searching, improve search engine optimization (SEO) and generate new ways to display content.

Metadata is frequently described as “data about other data.” Whether describing the contents of a web page, providing the technical details of the kind of camera used to capture an image, or the administrative information of usage rights, among many examples, metadata provides additional information that helps assets get found and used more efficiently. In fact, metadata is mainly designed to be machine-readable and isn’t visible to the casual site visitor.

For example, metadata for a web page is designed to help search engines understand and categorize pages. Likewise, the metadata in a photograph can be used by a digital asset management (DAM) system for proper categorization to promote discovery and use. Metadata also has major implications in the universes of information-sharing, usage rights and content reuse.

When the first bits were dropped on the first hard-disk drive, it’s not likely that computer scientists imagined the onslaught of data just 50 years would bring. But those pioneers probably recognized that data management was going to become a challenge. Part of meeting that challenge is data modeling: the practice of developing data storage and retrieval solutions that fit the requirements of a particular business.