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.

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.

Collecting and analyzing data on your customers’ preferences and behavior is one of the best ways to improve your products and customer service. As your business grows, you need enterprise-class customer relationship management (CRM) software that can store and manage all of your customer data. Salesforce is a software as a service (SaaS) company that provides the Salesforce CRM software to more than 100,000 organizations worldwide.

Unfortunately, most of us have had our sensitive data or personal information compromised at one point or another. Whether the leaked data involves credit cards, a bank account number, a social security number, or an email address, nearly everyone has been a victim of a third-party data breach. In 2020, over 155 million people in the U.S. — nearly half the country's population — experienced unauthorized data exposure.

Data migration seems simple from a high-level point of view. After all, you’re simply moving data between two or more locations. In practice, however, migrating data can be one of your IT department’s trickiest data management initiatives. According to LogicWorks, 90 percent of CIOs in charge of data migrations moving from on-premises to the cloud have encountered problems during this process, with 75 percent missing planned deadlines.

When people share their personal information with an organization, they’re performing an act of trust. They trust you to keep their data safe from hackers, and they trust you to use their data only for legitimate purposes. While many organizations honor this trust, others do not. As a result, governments worldwide are rushing to pass data protection legislation that puts the power back in the hands of people.