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Data Integrity for AI: What’s Old is New Again

Precisely

Does the LLM capture all the relevant data and context required for it to deliver useful insights? Not to mention the crazy stories about Gen AI making up answers without the data to back it up!) Are we allowed to use all the data, or are there copyright or privacy concerns? But simply moving the data wasnt enough.

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Hadoop Explained: How does Hadoop work and how to use it?

ProjectPro

(In reference to Big Data) Developers of Google had taken this quote seriously, when they first published their research paper on GFS (Google File System) in 2003. Little did anyone know, that this research paper would change, how we perceive and process data. Since then, it is evolving continuously and changing the big data world.

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Is Apache Iceberg the New Hadoop? Navigating the Complexities of Modern Data Lakehouses

Data Engineering Weekly

The modern data stack constantly evolves, with new technologies promising to solve age-old problems like scalability, cost, and data silos. But is it truly revolutionary, or is it destined to repeat the pitfalls of past solutions like Hadoop? It promised to address key pain points: Scaling: Handling ever-increasing data volumes.

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Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

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BI On Hadoop: Transforming Big Data Into Big Insights

ProjectPro

Ready to take your big data analysis to the next level? Check out this comprehensive tutorial on Business Intelligence on Hadoop and unlock the full potential of your data! million terabytes of data are generated daily. The global Hadoop market grew from $74.6 Table of Contents Why Business Intelligence On Hadoop?

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Top Hadoop Projects and Spark Projects for Beginners 2025

ProjectPro

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Why Apache Spark?

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Databricks Delta Lake: A Scalable Data Lake Solution

ProjectPro

Want to process peta-byte scale data with real-time streaming ingestions rates, build 10 times faster data pipelines with 99.999% reliability, witness 20 x improvement in query performance compared to traditional data lakes, enter the world of Databricks Delta Lake now. It's a sobering thought - all that data, driving no value.