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In this blog, we describe how you can build your own Dagster IO managers and use AWS Redshift as an example. We elaborate on the fundamentals on IO managers, and the tips and tricks we’ve learned building different IO managers over time.

Data governance is a way of managing data in your organization. Data governance in itself is thus also not the goal; it is a necessity that many organizations need because of their challenges with managing data according to the governance rules required.

Businesses are generating vast amounts of information at an unprecedented rate. To glean insights, organizations need a robust and flexible data infrastructure, the datawarehouse.

In the ever-evolving landscape of B2B marketing, digital relationship management has taken center stage like never before. The key to success lies in the art of smarter targeting, the emergence of innovative content formats, and a more personalized approach to communication.

Data-driven decision-making is crucial for startups to optimize their business operations and achieve long-term success. Unfortunately, many startups begin too late with becoming data-driven, which makes it challenging to change their approach later on.

In the rapidly evolving landscape of modern data management, selecting the appropriate ingestion tool plays a pivotal role in ensuring a successful data stack implementation. With a plethora of options available, making an informed decision requires careful evaluation of several key factors.

Business Intelligence (BI) is about using data to drive better decision-making. However, BI dashboards need to be designed with certain aspects in mind to be genuinely effective. In this post, we’ll explore some essential practices to help organizations maximize the value of their BI efforts.

The data field encompasses various roles, such as business analysts, data scientists, and data engineers. While these roles are essential, the reality is that not every business has the luxury of starting with a fully-fledged data team.

A blogpost on the modern data stack, where we look at the pros and cons of this new data architecture.

Customer retention analytics and understanding churn rates have become critical to any successful company’s strategy. Customer retention goes beyond just acquiring new customers; it focuses on retaining and nurturing the existing customer base, which often proves more cost-effective and profitable.