The AI Vegan – A real use case for NFT/ Blockchain?
Blockchain has a chequered history.
I am not optimistic about blockchain because, in my view, its a technology looking for a use case that can be uniquely addressed by it.
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Reaping the Benefits of Having a Data Backup and Recovery Plan
In today’s data-driven economy, any business needs to make sure that their data is easily recoverable and secured in an emergency. The National Archives and… Read More »Reaping the Benefits of Having a Data Backup and Recovery Plan
Data Storytelling: Meshing Narrative Techniques with Data Science Smarts
Alongside the explosion in enterprise data analytics is the growing realisation that insights, without action, are not enough.
Reengineer Business Decisions Granularly with Automated Data Collection
Businesses, whether big or small, know that understanding data is essential to making informed decisions that impact the organization’s bottom line.
VM backup with Hyper-V Changed Block Tracking (CBT)
When it comes to backup efficiency and copying only the needed data between a full backup and any incremental backups, changed block tracking technology is… Read More »VM backup with Hyper-V Changed Block Tracking (CBT)
15 Data Issues and How to Fix Them – Second Part
In the first part here, I discussed missing, outdated and unobserved data, data that is costly to produce, as well as dirty, unbalanced and unstructured… Read More »15 Data Issues and How to Fix Them – Second Part
DSC Weekly 30 August 2022 – Metaverse Misfires
One of the central concepts of the metaverse is the notion that every person has a single sign-on controlled by the vendors, which can, in turn, be used to track users as they move from one virtual world to another.
Semantic Graph as the Next Step for Web Data Architecture
Webby data architects and modelers–the spider-like ones who use intelligent graph design and a bit of glue or another sticky substance to achieve their objectives–are focused on making joinery much more efficient and scaling a lot more useful with the help of more contextualized data.
How to Make Black-box Systems more Transparent
This article is intended to users relying on machine learning solutions offered by third party vendors. It applies to platforms, dashboards, traditional software, or even external pieces of code that are too time consuming to modify. One of the goals is to turn such systems into explainable AI.
A Model For Technical Debt In Machine Learning Systems
Technical Debt describes what results when development teams take conscious actions to expedite the delivery of a piece of functionality or a project which later needs to be remediated via refactoring.