Data Migration Strategies to Cut Down Migration Costs by 70%

Databricks Migration

Migrating data can feel overwhelming and expensive. But it doesn’t have to be. With the right strategies, you can actually reduce migration costs by up to 70%. So, what’s the trick? It’s all about being intentional—only migrating the data that’s essential and ensuring its quality. Let’s break down three practical strategies that can make a…

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Seamless Teradata to Databricks Migration: How to Tackle Challenges and Ensure Data Quality With DataBuck

Data Quality with DataBuck

Data migration is one of those projects that often sounds straightforward—until you dive in and start uncovering the layers of complexity. Moving from Teradata to Databricks, a journey many companies are embarking on to boost flexibility and scalability, is a prime example. The promise of enhanced data processing capabilities is there, but so are a…

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Data Observability: a Blueprint for Competitive Advantage in Modern Enterprises

Blueprint for Competitive Advantage

Data Observability: a Must-Have for Modern Enterprises Modern enterprises thrive on data-driven decision-making. Yet, raw data alone offers limited value. Success lies in extracting actionable insights, driving innovation, and maintaining a competitive advantage. This requires a strategic approach to data management. Data observability fills this vital role. It allows businesses to understand their data’s health,…

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Top 5 Challenges of Data Validation in Databricks and How to Overcome Them

Artistic representation of validating data on Databricks.

Databricks data validation is a critical step in the data analysis process, especially considering the growing reliance on big data and AI. While Databricks offers a powerful platform for data processing and analytics, flawed data can lead to inaccurate results and misleading conclusions. Here’s how to ensure your Databricks data is trustworthy and ready for…

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Simpler Data Access and Controls With Unity Catalog 

Data lakes and data warehouses

Foreword: The below blog post is being reproduced on our website with permission from Speedboat.pro as it closely intertwines with FirstEigen’s DataBuck philosophy around building well-architected lakehouses. When building data pipelines, a thorough validation of the data set upfront (I call it ‘defensive programming’) yields great rewards in terms of pipeline reliability and operational resilience.…

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5 Downsides of Informatica Data Quality and How DataBuck Eliminates Them

The Informatica logo against a teal textured background.

Do you know the major downsides of Informatica Data Quality—and how to work around them? Often known as Informatica DQ, this tool is part of the larger Informatica data integration platform. Numerous enterprises rely on it to optimize data quality across both on-premises and cloud systems. However, Informatica DQ is not perfect. Users have reported…

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How to Deploy Data Quality Tools & Data Trust Monitors Across Pipelines to Reduce Dark Data?

Data Integration

As businesses collect ever-increasing volumes of data, the risk of accumulating “dark data”—data that remains unused or untrustworthy—continues to grow. The solution lies in implementing advanced data quality tools and data trust monitors across data pipelines to ensure the accuracy, reliability, and trustability of your data. Seth Rao, CEO of FirstEigen, speaks about building a…

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The Ultimate Guide to Data Preparation: A 6 Step Process

Woman tying her shoes in preparation for a run; illustrates the need for data preparation.

Do you know why data preparation is important to your organization? Poor-quality or “dirty” data can result in unreliable analysis and ill-informed decision-making. This problem worsens when data flows into your system from multiple, unstandardized sources.  The only way to ensure accurate data analysis is to prepare all ingested data to meet specified data quality…

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10 Essential Steps to Set Up AWS Managed Airflow for Optimized Workflow Management

ww.istockphoto.com/photo/science-math-chemistry-equations-gm953006962-260169543 Alt-Text: “Concept art illustrating Airflow on AWS.

Harnessing the power of cloud-based workflow management has become indispensable in modern IT environments. Amazon Web Services (AWS) offers Amazon Managed Workflows for Apache Airflow (MWAA), a crucial tool that simplifies complex computational workflows and enables Managed Airflow on AWS. In 2022, AWS’s revenue surpassed $80 billion, indicating its prominent role in the growing cloud…

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