Curated for content, computing, data, information, and digital experience professionals

Category: Computing & data (Page 90 of 99)

Computing and data is a broad category. Our coverage of computing is largely limited to software, and we are mostly focused on unstructured data, semi-structured data, or mixed data that includes structured data.

Topics include computing platforms, analytics, data science, data modeling, database technologies, machine learning / AI, Internet of Things (IoT), blockchain, augmented reality, bots, programming languages, natural language processing applications such as machine translation, and knowledge graphs.

Related categories: Semantic technologies, Web technologies & information standards, and Internet and platforms.

Unstructured data

Unstructured Data (or unstructured information) refers to information that either does not have a predefined data model and/or does not fit well into relational tables, such as narrative text, audio, or visual data.

In the early days of information technology (1950s -1970s), information systems focused on structured data. Until the late 1970s there was little interest in managing unstructured data. In the 1980s computerized publishing systems were built to process unstructured information for creating, formatting, editing, and printing documents. And SGML was created to add structure to document information for computer processing. Electronic publishing and document management systems grew steadily until the early 1990s when the Web produced an explosion of unstructured data.

Unstructured data is also the main ingredient to most of today’s machine learning applications, which involve natural language processing, and image and streaming pattern recognition.

Modern data management strategies need to include a variety of structured and unstructured data types. PostgreSQL, MongoDB, Cassandra, Neo4j, Snowflake, and DataStax are some examples of modern database products. Many current versions of traditional SQL-based database products can also support NoSQL (non-SQL or not-onlySQL) data.

Gilbane Advisor 7-29-19 — Enterprise ML risk, web contract, web 3.0, news & scale

Managing ML in the enterprise

Regulated industries are often among the first to figure out how to implement new technologies in complex, high risk environments. This O’Reilly article looks at how finance (mostly) and health care model risk in the context of machine learning. There are useful and important lessons for enterprises in general. Read More

 

Model risk management

A contract for the Web

We all know the web has a boatload of challenges coming from a collection of commercial and national sources intent on subverting or replacing it. But organizations and consumers of the web have also been too complacent as these threats have grown. The World Wide Web Foundation’s mission is to “advance the open web as a public good and a basic right.” by changing government and business policies. The foundation has just published a draft “Contract for the Web” and is asking for input from governments, businesses, and citizens. That’s right, they want your opinion. Read More

Is Web3.0 the next lifestyle brand?

Web 3.0 does not, and will likely never have, a canonical definition. Web 3.0 refers to a collection of aspirations, similar to those of the Web Foundations’, and new technologies to support those aspirations and a decentralized web, such as blockchain and crypto. Since these technologies are not widely understood, marketing Web 3.0 etc. is a problem. Jeremy Epstein has some “half-baked” (his words) ideas on relating it to modern intentional lifestyle choices as away to build support. Read More

By running unwitting PR for Jeffrey Epstein, Forbes shows the risks of a news outlet thinking like a tech platform

If journalists want to criticize the anything-goes ethos of Facebook, it’s only fair to note when news organizations’ hunger for scale leads them down the same problematic path. Read More

Also…

The Gilbane Advisor curates content for content, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December.

content management

Content management, or CM, is the set of processes and technologies that support the collection, managing, and publishing of information in any form or medium. When stored and accessed via computers, this information has come to be referred to as content or digital content. Digital content may take the form of text, multimedia files (such as audio or video files), or any other file type that follows a content lifecycle requiring management. Content management can be found in both dedicated systems and as a component of information technology systems. 

The term ‘content management’ became popular when ‘web content management’ systems emerged to differentiate them from ‘document management’ systems which were associated with paper documents. ‘Content management’ then quickly evolved to cover all kinds of unstructured or semi-structured content. Common types of content management systems (CMS) include Enterprise Content Management (ECM), Digital Asset Management (DAM), Multichannel Content Management (MCM), Component Content Management (CCM), and web content management (WCM). The latter are now widely marketed as Digital Experience Management’ (DEM or DXM, DXP), and ‘Customer Experience Management’ (CEM or CXM) systems or platforms, and may include additional marketing technology functions. 

For an extensive collection of content management news and blog posts see https://gilbane.com/category/content-management-strategy/

For more historical background see What is Content Management?

Gilbane Advisor

The Gilbane Advisor newsletter, published by Bluebill Advisors Inc., curates content for our audience of content, computing, and digital experience professionals throughout the year, and includes Gilbane Conference news. We focus on strategic technologies and strategies.

We’ve been a trusted advisor to all stakeholders on content and information technologies and applications for decades. We only publish what we’ve written or what we’ve read and believe will be valuable to our subscribers.

Gilbane Advisor 6-4-19 — Martech metrics, B2C AR, B2B AR, machine talking

Martech stack metrics

Scott Brinker: “Martech stack utilization is a misguided metric… (when it’s disconnected from value)”. This is certainly true. Products/tools in your stack usually have many features, only a subset of which actually provide value for your needs. Identifying and

Martech stack value

focusing on those features can save resources and provide more accurate ROI calculations. Read More

4 questions retailers need to ask about augmented reality

It seemed like AR was poised for rapid adoption (beyond Pokémon Go) a couple of years ago when apps started appearing from Ikea and others. Indeed I thought so. There has certainly been a lot of activity and some very useful applications, but as usual the use-case specifications, cost justifications, integrations, and learning curve take a time-toll. Bain & Company has some good advice for execs creating or reviewing a plan. Read More

Google announces a new Glass augmented reality headset for B2B

Much of the advice in the Bain article we reference above is also relevant to non-consumer AR applications. Whether B2B AR deployments are ahead of B2C or not, project planning should be informed by research into both. ROI calculations will be very different, but technologies and user experience design considerations largely overlap. Google Glass was a consumer flop but their Enterprise Edition is making some progress and what they are learning is valuable. After all, employees and professionals are consumers too. Read More

Can we trust machines that sound too much like us?

David Weinberger raises a good point. He is not asking whether we can trust machines. He is asking whether we want to loose the trust signals we get from talking with humans when we can’t tell the difference between machine and humans voices. He also wonders about the efficiency and how our preferences will evolve. Human sounding machines will not always be the right choice. Read More

Also…

The Gilbane Advisor curates content for content management, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December.

Gilbane Advisor 4-16-19 — Rules & data, ad blocking, use metadata, journey mapping

The Guardian’s old-article trick

“… this is a great idea, one worth replicating elsewhere. But it’s also a reminder of the power publishers have to use their article metadata to improve public understanding — and how little they use it. When one of your old stories is floating around social media in a way that causes confusion, you can do something about it.” Read More 

The Guardian metadata trick example

Is ad blocking past 2 billion worldwide?

Doc Searls: “The answer is, we don’t know. Also, we may never know, because”… Read More

Journey mapping: 9 frequently asked questions

Journey maps are useful for building common ground in an organization, but practitioners often have questions and misunderstandings about their scope and how to create them. Read More

Bitter lesson + better lesson = lesson

Many of you will remember the rules vs data debates from the early days of machine translation and image recognition. There is a similar debate currently going on in AI research. The main differences are the dramatic improvements in deep learning, facilitated by the availability of massive computing power. The current discussion seems more secular, and concerned with relative costs and efficiencies. This post, “Better lesson” is by Rodney Brooks, but also checkout Rich Sutton’s “Bitter Lesson”, which Brooks links to. Both posts are short and very accessible. Read More


Just 2 weeks until…

Gilbane’s Digital Experience Conference

Reserve your seat today – use code FG19 for best price


Also…

 

The Gilbane Advisor curates content for content management, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December.

Gilbane Advisor 3-19-19 — Federated ML, ephemeral messaging, search for humans

Google releases federated machine learningTensorFlow summit 2019

Federated learning is going to be a thing. Health care is just one example… “TensorFlow Federated will provide distributed machine learning for developers to train models across many mobile devices without data ever leaving those devices. Encryption provides an additional layer of privacy, and weights from models trained on mobile devices are shared with a central model for continuous learning.” Read More

A warning on the dangers of ephemeral messaging

The Information’s Sam Lessin is bullish about Facebook’s moving to full encryption, but thinks a reliance on ephemeral messaging is a big mistake. He makes a good case and the issues he raises need broader consideration. (Firewall – but you can get access by providing an email.) Read More

Search engines: a human perspective

Wise words on search applications from Daniel Tunkelang.

The foundation of human-computer information retrieval (HCIR) is that search engines help searchers who help themselves. The best search engines reward searchers’ incremental effort with a higher return on investment. … But searchers have been trained by simple search interfaces, and their laziness is compounded by a skepticism of anything that violates their expectations. In order to earn searcher effort, search engines have to provide simple, incremental, and effective steps that guide searchers — and that teach them through experience that the return justifies the additional effort. Read More

Facebook’s News Feed era is now officially over

It’s anyone’s guess where Facebook will end up after the strategic shift announced last week. The new direction impacts all parts of the company and raises questions about their business model, growth, and of course, organization. Read More


Join us at Gilbane’s Digital Experience Conference

Digital experience strategies, technologies, and practices, for marketing and the workplace

Also…

The Gilbane Advisor curates content for content, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December.

Gilbane Advisor 7-11-18 — No-hype blockchain, ML, mobile dev, publishing

Blockchain beyond the hype: What is the strategic business value?

Excellent measured piece to share with senior management, from McKinsey. “Our research seeks to answer this question by evaluating not only the strategic importance of blockchain to major industries but also who can capture what type of value through what type of approach. To see the original interactive version of the graphic… Read More

Ways to think about machine learning

Benedict Evans looking at the fundamentals of ML, minus the often unhelpful ways it is often discussed.

So, this is a good grounding way to think about ML today – it’s a step change in what we can do with computers, and that will be part of many different products for many different companies. Eventually, pretty much everything will have ML somewhere inside and no-one will care. Read More

A deeply detailed but never definitive guide to mobile development architecture

“Native, Web, PWA, hybrid, Cross-Compiled… what is “the best” way to develop for Android and iOS platforms? What looks reasonable? And how are you supposed to choose among the options?” Long enough to be really useful… Read More

The promises and perils of blockchain technology in publishing

Bill Rosenblatt looks at the practicality and unknowns of the “Three general types of blockchain applications in publishing are being discussed nowadays: rights licensing and royalty processing, print supply chain management and piracy tracking, and e-book ownership transfers.” Read More

Goodbye, Denver Post. Hello, Blockchain & Colorado Sun

The new publication will have a conventional website whose data will be written permanently into the secure digital ledger known as the blockchain. Expenses for the fledgling outlet will be covered by a grant from Civil, whose sole investor, for now, is ConsenSys, a Brooklyn-based blockchain software technology company founded by Joseph Lubin… a co-founder of Ethereum. Read More

Also…

The Gilbane Advisor curates content for content, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December. See all issues

« Older posts Newer posts »

© 2026 The Gilbane Advisor

Theme by Anders NorenUp ↑