- This week we begin with an article about how data loss prevention is essential to prevent data breaches and protect an organization’s reputation.
- Next, we have a research report that states that artificial intelligence and alternative data can give credit access to a lot more eligible people by measuring the creditworthiness of borrowers with limited credit history.
- The following article lists the strategies to detect, correct, and prevent poor data quality that has the potential for reputational and business loss to organizations.
- Following that, we have an article explaining the similarity and key differences between data quality and data governance and how they are not mutually exclusive
- Next is a piece that talks about cutting through complexity and creating end-to-end visibility into an organization’s IT systems by enacting database observability.
- Finally, we have an article describing that cloud fax is more secure for data exchange than an email.
What Is Data Loss Prevention (DLP)?
Data Loss Prevention (DLP) ensures that confidential or sensitive data is not lost, stolen, or unintentionally distributed. It can be used to prevent data breaches and protect an organization’s reputation. You might have heard about the DLP in the news, but what exactly is it? And how can you use it to protect your data?
AI And Alternative Data Cloud Help Millions Gain Access To Credit
A recent research collaboration between LSU’s E. J. Ourso College of Business, Harvard Business School and industry partner Upstart, a financial technology company and online lending marketplace, provides evidence that both lenders and borrowers would benefit from increased reliance on alternative data, not just credit scores, in evaluating a person’s risk of defaulting on a loan.
How To Address Poor Internal And External Data Quality For Your Business
Between responding to supply chain disruptions, pivoting in the economic slowdown, reacting to inflation, retaining and gaining new customers, and better managing inventories and production, data quality has never been so crucial for your business. In the digital age, data is a business’s most valuable resource. Data collection, data analytics and data governance strategies are what separate leaders from the rest of the pack.
Data Quality vs Data Governance: How They Impact Your Business
Data quality and data governance describe different parts of enterprise data management strategies but are not mutually exclusive. Together, they can help your business improve its bottom line by providing better visibility into enterprise assets, all while driving efficiency and operational improvements that lead to greater business agility. This comparison defines both terms, explains their differences, and covers how data quality and data governance best practices can be used in tandem.
Database Observability: How To Circumvent Your Weakest Link
Today, IT pros field an increasing number of assets they need to monitor to secure systems and understand what’s happening in their database and applications. This is further complicated as organizations adopt hybrid IT strategies and IT pros are tasked with managing tech stacks that span across on-premises and public clouds. To cut through complexity and create end-to-end visibility into their IT systems, organizations must enact an observability approach.
Why Cloud Fax Is Better For Secure Data Exchange Than Email
The constantly-evolving email encryption landscape is a tell-tale clue as to email’s vulnerability. Email service providers and encryption software makers must continually up their game because they know organisations use email to transmit their most sensitive content – a fact that makes a valuable high-priority target for cybercriminals.