Poor Data Quality, Dark Data, Digital Innovation, China Data Leak, Multicloud, Data Science

This week, we begin with an article outlining the huge costs of poor data quality and the role of AI in boosting the data quality for better decision-making. Next, is a piece portraying the significant risks of dark data, including data protection & compliance, along with the ways to manage & protect dark data. Then, we have a story about the transformations going on in the financial sector industry, ranging from the adoption of open banking to the adoption of cloud services. Following that, we have an article about a sale offer on a Shanghai police database containing case records and personal information data on close to 1 billion Chinese residents for 10 Bitcoins. Next, is an analysis of the security & privacy challenges of a mix of public & private clouds, also known as multi-cloud. Lastly, we have an essay describing how data science methodologies can help eCommerce merchants in addressing the issues of data management and improving profitability.

Why Poor Data Quality Is Holding Back Big Data

We can’t expect an algorithm to deliver accurate insights if it is fed with low quality data. Yet, all too often poor data quality only becomes a recognised issue when the algorithm starts delivering obviously dud results. The rest of the time, the vast majority of enterprises are content to put up with incomplete, inaccurate, duplicate or otherwise low-quality data, which can be felt any number of ways: a minor inconvenience here, a laggy system there and a reliance on guesswork, workarounds and manual processes.  

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Dark Data: Managing The Data You Can’t See

In today’s era of seemingly infinite data volume and complexity, many enterprises are unintentionally neglecting an entire category of data that is critical to their data protection and management practices. On average, more than 50% of a company’s data is “dark” – information held up in data repositories with no attached or determined value. In addition to costing an average $26 million in storage expenses per year, dark data poses significant risks to an enterprise’s security and compliance efforts, making it more important than ever to address the foundational issues that cause it. 

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Financial Transformation

The financial sector is on the cusp of yet another transformation. Customers emerging from Covid-19 are demanding new and better sets of services to meet their new consumption patterns, be it how they shop, eat, work or transfer money. It’s a dramatic shift that is compelling banks to transform or risk being left behind. “The traditional business model of banking has changed because customers expect more from banks. It’s not just lending and taking deposits, but customers expect them to be an adviser for what they’re doing,” says Bambang Moerwanto.

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Shanghai Police Database For Sale In What Could Be China’s Biggest Ever Data Breach

A database purportedly containing information about one billion Chinese residents has been listed for sale on Breach Forums for 10 Bitcoin, or approximately US$200,000. Attracting 177 replies and 300,000 views within hours, the listing was posted a short time ago by an anonymous user named ChinaDan.“In 2022, the Shanghai National Police (SHGA) database was leaked. This database contains many terabytes of data and information on Billions of Chinese citizens,” said the post.

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Managing Data Security And Privacy In Multicloud Environments

Enterprises’ love affair with multicloud is getting stronger by the day. Indeed, IDC forecasts that more than 90% of enterprises worldwide are likely to be using more than one cloud provider by 2022. The core drivers for using a mix of public and private clouds include the desire to access best-of-breed products, streamline compliance with regulations and market requirements and avoid vendor lock-in. While multicloud offers numerous business advantages, it also presents unique security and privacy challenges.

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Data Science: A Force That Promises Increased Revenue

Data is no longer an option for ecommerce businesses. Accessing, interpreting, and using it effectively has become the difference between life and death for modern online retail. The onset of the digital age and its proliferation has led to excessive data production. According to some resources, 2.5 quintillion bytes of data is produced every day. This number reflects the volume of profit-driving insights and value you might be able to get your hands on if you manage to tap into this data.

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Source: https://mailchi.mp/zigram/data-asset-weekly-dispatch_04_july_1

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