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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.

G2 is one of the leading review and comparison sites for business software, so as an ETL provider, we’re especially proud to be recognized as market leaders by G2 and its users in Spring 2021. Xplenty received three of the coveted badges in the Spring review of top software and service providers including.

Transferring files between two or more machines is an essential part of the ETL (extract, transform, load) process. Of course, there are multiple ways to move data, including flat file databases. For example, you can physically copy the data onto a USB drive or send it to the recipient via email. But methods like these are far less efficient than sending data via FTP. So what is FTP exactly, and how do you use it to transfer files and data? Keep reading for all the answers.

As the amount of data companies are faced with snowballs, the need for efficient data governance grows. An increasing number of organizations are turning to cloud service providers for data management. In this context, data as a service, often referred to as DaaS, is becoming an essential tool for managing data integration, data storage, and data analytics.

The General Data Protection Regulation (GDPR) is a landmark piece of legislation that affects how organizations can handle, process, and store the personal data of European Union (EU) citizens and residents. But what does the GDPR require exactly, and how can you be sure that your organization complies with it? We go over everything you need to know in this all-in-one guide to GDPR compliance.

ELT is a three-step process that first extracts raw, structured, and unstructured data from source databases, applications, data stores, and other repositories. It then loads that data into a data lake and transforms it as needed by analysts. Since it doesn't move the data to an intermediate staging area or transform it before loading, the extraction process is speedy. You don’t need to pick and choose what data loads into the data lake or wait for it to be processed.

Businesses large and small depend on access to information in order to make smarter, data-driven decisions. And much of that data is personal, sensitive, or confidential. So how can you balance this demand for big data with the need to protect the individuals whom this data describes? When it comes to personally identifiable information (PII), there are multiple very good reasons why you should keep it securely under lock and key.

What do Xplenty, Snowflake software, and dbt (data build tool) have in common? When used together, they merge the best of ETL (extract, transform, load) and ELT (extract, load, transform) into a powerful, flexible and cost-effective ETLT (extract, transform, load, transform) strategy. In this guide, we’ll show you how to create an ETLT strategy with Xplenty, Snowflake software, and dbt. But first, we’ll explain why you'd want to use this strategy to build an ETLT data transformation stack.