This week, we begin with a piece on data privacy compromises done by big techs to fuel monetization based on ad impressions & the exigency of building standards for protecting users against abuse. Next, is an analysis of dirty data cybersecurity concerns based on the predictions of the Information Security Forum (ISF) and some recommendations to mitigate the emerging threats. Then, we have an essay about ways of realizing the value of data by organizations to become more productive, efficient & responsive. Following that, we have an article describing the hub-and-spoke model that is an alternative to the data mesh architecture and provides advantages of both centralized & decentralized. Next, is an article narrating the widespread use of facial recognition technology, the controversies & opposition about it & the need for appropriate regulations. Lastly, we have a bill proposed by the US House Committee on Financial Services that will offer customers more control over who may access their data and how it is used.
Toward Data Dignity: Let’s Find The Right Rules And Tools For Curbing The Power Of Big Tech
If you’ve spent even a modicum of time scrolling through our biggest social media platforms in 2022, you’ve probably seen those funky looking, seemingly inexplicably popular images of apes as profile pictures. Non-fungible tokens, cryptocurrencies, and other high-minded reinventions of how we carry out transactions and function on the web have been a theme of the last year. Super Bowl ads vaulted these concepts onto our TV screens and into our minds.
3 Threats Dirty Data Poses To The Enterprise
Data drives the modern enterprise. From making product and service recommendations based on past consumer choices to determining market opportunities and business risks to testing how a product or service will perform, data is embedded into almost every enterprise decision, interaction and process. It’s nearly impossible to assure integrity and quality of data in real time, however. In fact, most organizations believe a third of their data is inaccurate in some way.
Maximize Business Value With Data-Driven Strategies
Every company is collecting data, whether it’s consumer buying habits, demographic data from third-party sources or insights from weather patterns. That’s good news—it wasn’t long ago that this kind of critical information was mostly ignored. But it’s not enough: companies must now start using that data to run every part of their business. There’s more progress to be made: just 34% of executives in a recent PwC U.S. Cloud Business Survey say they’re achieving their target business outcome when it comes to improved decision-making through better data analytics.
The Hub-And-Spoke Model: An Alternative To Data Mesh
Data mesh is a hot topic in the data and analytics community. Introduced in 2020 by Zhamak Dehghani in her paper “Data Mesh Principles and Logical Architecture”, data mesh is a new distributed model for organizing analytics teams to deliver data products and is meant to address the challenges of both centralized and decentralized data. But is this approach truly the best approach for today’s enterprises?
Facial Recognition Is On The Rise – But The Law Is Lagging A Long Way Behind
Private companies and public authorities are quietly using facial recognition systems around Australia. Despite the growing use of this controversial technology, there is little in the way of specific regulations and guidelines to govern its use. We were reminded of this fact recently when consumer advocates at CHOICE revealed that major retailers in Australia are using the technology to identify people claimed to be thieves and troublemakers.
Proposed Financial Data Privacy Bill Tightens Customer Data-Sharing Rules
The House Financial Services Committee’s ranking member, Patrick McHenry, released a draft bill on June 23 that seeks to modernize financial data privacy laws and give consumers more control over how their personal information is collected and used. “This proposal will modernize the current framework to better align with evolving technology and protect against the misuse or overuse of consumers’ personal information,” said McHenry.