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DataScan: Issue #73

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Blockchain and data management myths. Are silos are the greatest stumbling block to effective data us
 

DataScan

August 5 · Issue #73 · View online
Curated digest on the world of data.

Blockchain and data management myths. Are silos are the greatest stumbling block to effective data use? Why you aren’t as anonymous as you think online. Watch a human-like robot hand learning dexterity.
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Blockchain and data management myths. Gartner’s Susan Moore deep dives on why blockchain is not the future of databases, by debunking the three common myths with Nick Heudecker, research vice president at Gartner:
  1. Blockchain will replace existing data management technologies -> they are just another data source to integrate.
  2. Blockchains are inherently more secure -> they are a mechanism for distributed consensus, not a magical security or encryption solution.
  3. Vertical-specific blockchain platforms simplify vendor selection -> through 2021, 90% of blockchain platform implementations will require replacement within 18 months.
As put by Heudecker:
Many of the proposed uses for blockchain are described broadly as shared databases. This oversimplifies the complexity of blockchain-based systems, while overstating the data management features available in today’s blockchain implementations.
Are silos the greatest stumbling block to effective data use? Writing for LSE Business Review, Gaurav Dhillon discusses the impact of disconnected data, based on SnapLogic’s recent Data Value Report:
Only 2 per cent of our respondents considered their business to be completely effective at data sharing – for the rest, data silos are a real problem.
The causes for this are numerous, and span inconsistency of systems being used (42 per cent), different data formats (38 per cent), and a lack of coordinated data strategy (37 per cent).
On top of this, over a third highlight a lack of technology integration (36 per cent) and/or legacy technology barriers (36 per cent) as blocking attempts to effectively share data.
As a solution, Dhillon argues that businesses need to create a “unified, integrated approach” to data collection and management, and “create a business wide culture and strategy for better data sharing”. –> New research by Dentsu Aegis revealed that “61% of chief marketing officers still struggle to extract insights from the deluge of information”.
Why you aren’t as anonymous as you think online. Excellent article by Olivia Solon explaining how easily anonymised data can be reverse-engineered to expose people’s identities and how it’s “only getting worse” as more people “sprinkle digital breadcrumbs” online. Although data may look anonymous, as the “obvious identifiers” have been removed, this does not necessary make it anonymous:
Yves-Alexandre de Montjoye, a computational privacy researcher, showed how the vast majority of the population can be identified from the behavioural patterns revealed by location data from mobile phones.
By analysing a mobile phone database of the approximate locations (based on the nearest cell tower) of 1.5 million people over 15 months (with no other identifying information) it was possible to uniquely identify 95% of the people with just four data points of places and times. About 50% could be identified from just two points.
The four points could come from information that is publicly available, including a person’s home address, work address and geo-tagged Twitter posts.
De Montjoye iterates the “enormous potential” of big data, but argues that instead of releasing anonymised data, we should “develop interfaces that allow others to ask questions without accessing the raw files.”
–> A ML algorithm was able to identify users with 96.7% accuracy by using publicly available Twitter metadata. Check this new research on how you are your metadata.
Miscellaneous
🙌 It’s time for Silicon Valley to get behind a national privacy law.
☎️ Dixons Carphone says data breach affected 10 million.
⚖️ 23andMe is sharing genetic data with drug giant.
⛔ Facebook blocks access to data for “hundreds of thousands” of apps.
📊 Google search will now highlight useful data journalism from stories.
💯 M&S to train staff as data scientists in overhaul drive.
🤖 Learning dexterity: Human-like robot hand manipulating objects. 
🏫 What happens what you let computers optimise floor plans.
🚀 Want less-biased decisions? Use algorithms.
🌎 How a booming population and climate change made California’s wildfires worse than ever.
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