Monetization, War, Credit, EU, Breach, AI

This week, we begin with an article on how companies are building strategies to reuse & recombine their data assets for effective monetization. Next, we have a piece on how IPO of DiDi shares in NY is leading to a data war between China & the USA. The following article examines how credit score can be calculated using alternative data in turn opening up credit opportunities for millions of Americans. Following that, we have an article about a $887 million fine being imposed on Amazon by EU who alleges that the company violated General Data Privacy Regulations (GDPR). Next is a piece about a IBM report that highlights how Covid has increased the cost of data breach & led to shortage of cybersecurity professionals due to employers’ unwillingness to pay. Finally, we have an article on DeepMind’s newly developed ML tool that has reduced the time to accurately predict protein structures from months or years to minutes or hours.

Fast-Track Data Monetization With Strategic Data Assets

For years, using more data to make better decisions has been the holy grail for global companies, and most of them aim to treat data as a strategic asset. But new research from the MIT Center for Information Systems Research (CISR) has found that future-ready companies have greater ambition regarding their data. These organizations strive to maximize their data monetization outcomes by pervasively improving processes to do things better, cheaper, and faster; wrapping products with analytics features and experiences; and selling new, innovative information solutions.

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DiDi, China, And The Data War

Welcome to the newest frontier in the struggle between the U.S. and China for geopolitical dominance: the struggle for control of the strategic commodity of the future, data. The latest casualty in this battle is Didi, the Chinese Uber UBER -2.8% lookalike with 377 million annual active users and 13 million annual active drivers. Its agony began soon after Didi shares started trading publicly in New York, following a $4.4 billion initial public offering.  Little more than two weeks later Chinese authorities sent state-security and police officials into Didi’s offices. 

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Credit Scores Are Increasingly Including Things Like Rent And Utilities—Here’s What That Means For You

Credit scores are evolving. For some consumers, that could be a blessing. First, the basics: Your credit score is used by institutions including banks, credit card issuers, auto dealers and others to determine whether to lend you money or not, and if so, at what interest rate. The higher your score, the better the deals you are likely to get. There are two main providers of credit scores in the U.S. A company called FICO produces the dominant metric used by most lenders, which is a value between 300 and 850.

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Amazon Fined Record $887 Million Over EU Privacy Violations

Now that Amazon’s Q2 earnings are in , it has submitted a 10-Q filing with the SEC that includes additional details like this eye-popping note about a fine imposed by Luxembourg’s National Commission for Data Protection (CNPD) (via Bloomberg). On July 16, 2021, the Luxembourg National Commission for Data Protection (the “CNPD”) issued a decision against Amazon Europe Core S.à r.l. claiming that Amazon’s processing of personal data did not comply with the EU General Data Protection Regulation. The decision imposes a fine of €746 million and corresponding practice revisions. We believe the CNPD’s decision to be without merit and intend to defend ourselves vigorously in this matter.

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Cost Of An Enterprise Data Breach Now US$4.2 Million

It turns out the Covid pandemic has been a golden age for the crooks targeting enterprise systems. Having people work from home has made it harder to contain security incidents. Writing at ZDNet Charlie Osborne covers the annual IBM cost of a data breach report. It says a typical enterprise data breach costs the victim US$4.2 million per incident. That’s up 10 percent on a year earlier.

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Artificial Intelligence In Structural Biology Is Here To Stay

“I didn’t think we would get to this point in my lifetime.” That’s how one research leader in structural biology responded to last week’s publication of research in which artificial intelligence (AI) was used to predict the structure of more than 20,000 human proteins, as well as that of nearly all the known proteins produced by 20 model organisms such as Escherichia coli, fruit flies and yeast, but also soya bean and Asian rice. That is a combined total of around 365,000 predictions.

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