This week we begin with an article about the metagenomic universe created by the AI of Meta to find proteins in samples from many places on Earth and even in our bodies using gene sequencing. Next, we have a piece on the adoption of open banking in several regions, which will link the financial and technological ecologies and allow customers to fully own and profit from their data streams. Following that, we have the new European Union-U.S. Data Privacy Framework that has re-established clear data sharing rules between the two entities, providing businesses that handle EU personal data with legal security. After that, we have a story on why businesses should no longer delegate control of their data to IT if they hope to succeed in this new data-driven environment. Next is a write-up that addresses data quality issues as organizations delve into AI. Finally, we have an essay about how to avoid database development slowing down releases and to introduce a policy-driven approach to data management by adopting database DevOps.
Meta AI Creates First Ever Database Of 600 Million Metagenomic Structures
In a world first, Meta’s artificial intelligence (AI) has produced the structures of the metagenomic world at the scale of hundreds of millions of proteins, according to a blog by the company published on Tuesday. “Proteins are complex and dynamic molecules, encoded by our genes, that are responsible for many of the varied and fundamental processes of life. They have an astounding range of roles in biology,” wrote the Meta research team who also published a paper on the matter in the preprint database bioRxiv.
Asia Pacific’s Vast Open Banking Opportunity
Open banking is the use of application programming interfaces (APIs) to streamline the sharing of customer bank data with third parties. It “opens up banks” in the sense that it enables customers to have greater control and ownership over their personal information used by financial institutions. In theory, an optimal open banking system would be bespoke, allowing customers to select the services from different financial institutions they liked best, in contrast to the traditional one-size fits all model that remains dominant today.
New EU, U.S. Privacy Framework Sets Clear Data Transfer Rules
The new European Union-U.S. Data Privacy Framework has re-established clear data sharing rules between the two entities, giving companies that handle EU personal data legal peace of mind. The data privacy framework is a mechanism for companies, such as social media platforms, that transfer personal data between data centers in the U.S. and EU. While the EU has GDPR protecting its citizens’ right to data privacy, the U.S. has no such law, making a compliance framework for data sharing necessary.
Data Is A Business Asset, Not An IT Problem
In 2022, businesses have more access to data than ever before. Market research firm IDC estimated in 2020 that the data created between 2020 and 2023 would surpass the amount of data created over the past 30 years. We live in a data-centric world, yet many employees may still consider data the domain of the IT team—relinquishing control to those who put together the reports without taking the time to understand where the data comes from or how it is implemented.
Data Quality Is Also An AI Problem
Artificial intelligence (AI) continues its rise to prominence within the business world. The number of companies using AI today and the range of problems AI is being applied to are both increasing steadily. However, there is one issue that is plaguing AI just as much as it has plagued analytics of all kinds over the years—data quality. Organizations put tremendous resources behind ensuring the quality of their data.
How Database DevOps Can Modernize Government IT And Mitigate Risk
Software engineers are in a constant fight for efficiency. Whether teams are conducting scrum sprints or implementing a DevOps approach, the end goal is improving productivity and delivering better software, faster. Just about every industry is using data to achieve that end, but surprisingly — 19 years after Michael Lewis published Moneyball and brought data-driven decision-making to millions of everyday readers — many developer teams still fail to fully integrate data into their operations.
Source: https://mailchi.mp/zigram/data-asset-weekly-dispatch_07_november_1
