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The Health Insurance Portability and Accountability Act of 1996 (HIPAA) is a U.S. federal law. It sets national standards for health care providers to maintain the privacy of patients' protected health information (PHI), including electronically protected health information (ePHI). If you collect, store, or process any kind of patient or medical data, you need to be aware of HIPAA and how it affects your operations. But what does it really mean to be HIPAA compliant?

What should you know before getting started with ETL in Heroku? In this article, we provide a comprehensive guide to using Heroku ETL.

Imposter fraud is the second-most common type of fraud reported to the Federal Trade Commission, with around one-fifth of all cases resulting in financial loss to the victim. This often occurs because of a failure on the part of organizations to protect personally identifiable information (PII). Fraud is only one type of attack that may occur. Phishing is another exceptionally common data security threat. It often results from crawlers collecting email addresses, one type of PII, on the open web.

Organizations collect and use personal data for a variety of purposes, often without considering the impact on data privacy. Individuals are increasingly more aware of how their data is being used and the lack of say they have over the process. Data privacy and protection regulations are in place around the world to protect consumers and stop their personal information from being misused.

Personally identifiable information, or PII, is sensitive information that can identify an individual. Industry or data protection laws often regulate this type of data, requiring that organizations handle PII according to specific practices. It’s all too easy to make mistakes when working with PII, so we've highlighted six common scenarios to look out for.

Almost every aspect of our lives deals with data in some way. By 2025, the world could be producing 463 EB (exabytes, a unit equaling 1 billion gigabytes) of data each day. That’s why it’s more crucial than ever to keep personal data safe yet easily accessible to those allowed to view it.

Business intelligence (BI) teams include roles that sound similar at first, but each comes with its own distinct responsibilities and skillsets. By understanding each of these positions, you can build a BI team that delivers the solutions and capabilities to help your organization get the most out of big data.

If you're storing or processing education records, it's absolutely essential that you're familiar with FERPA. But what is FERPA exactly, and how does FERPA relate to data privacy? We go over everything you need to know.

Every data-driven business is terrified of the prospect of a data breach. Exposing sensitive data could mean reputational damage, loss of clients, and heavy fines under emerging privacy laws. But every data-driven business also wants to make use of its data. Business intelligence (BI) platforms allow anyone to build complex and detailed dashboards that help them understand the organization’s current state. How do you resolve this tension? One approach is to build a privacy-first data structure.

Extract, load, transform (ELT) technology is a type of data pipeline that ingests data from one or more sources, loads the data into its destination (typically a data lake), and then allows end-users to perform ad-hoc transformations on it as needed. ELT can perform mass extraction of all data types, including raw data, without the need to set up transformation rules and filters before data loading.