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Build Your Second Brain One Piece At A Time

Data Engineering Podcast

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

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Looking Ahead: The Future of Data Preparation for Generative AI

Data Science Blog: Data Engineering

Businesses need to understand the trends in data preparation to adapt and succeed. If you input poor-quality data into an AI system, the results will be poor. This principle highlights the need for careful data preparation, ensuring that the input data is accurate, consistent, and relevant.

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No Python, No SQL Templates, No YAML: Why Your Open Source Data Quality Tool Should Generate 80% Of Your Data Quality Tests Automatically

DataKitchen

Current open-source frameworks like YAML-based Soda Core, Python-based Great Expectations, and dbt SQL are frameworks to help speed up the creation of data quality tests. They are all in the realm of software, domain-specific language to help you write data quality tests.

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Natural Language Processing: A Guide to NLP Use Cases, Approaches, and Tools

AltexSoft

There are two main steps for preparing data for the machine to understand. Any ML project starts with data preparation. Plus, you likely won’t be able to use too much data. Assessing text data quality. There are different views on what’s considered high quality data in different areas of application.

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The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure

DataKitchen

Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. Power BI dataflows: Power BI dataflows are a self-service data preparation tool. It does the job. Oozie is an open-source DAG runner.

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Modern Data Management Essentials: Exploring Data Fabric

Precisely

A data fabric offers several key benefits that transform your data management: Accelerates analytics and decision-making processes by enhancing data accessibility through seamless data integration and retrieval across diverse environments.

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Top Data Cleaning Techniques & Best Practices for 2024

Knowledge Hut

Data cleaning is like ensuring that the ingredients in a recipe are fresh and accurate; otherwise, the final dish won't turn out as expected. It's a foundational step in data preparation, setting the stage for meaningful and reliable insights and decision-making. Let's explore these essential tools.