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Data Warehouse vs Big Data

Knowledge Hut

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Data warehousing offers several advantages.

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GPT and LLMs from a Data Engineering Perspective

Jesse Anderson

There has been quite a bit of writing covering GPT and LLMs from data science and business perspectives. I haven’t seen much from the data engineering side. Let me share my perspective, having been in data and AI for a while and using LLMs before they became popular. How can we use LLMs in data engineering?

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HBase vs Cassandra-The Battle of the Best NoSQL Databases

ProjectPro

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies.

NoSQL 52
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Top 10 Hadoop Tools to Learn in Big Data Career 2024

Knowledge Hut

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed.

Hadoop 52
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Data Lakehouse Architecture Explained: 5 Layers

Monte Carlo

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. ok, so maybe they don’t say that.

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5 Layers of Data Lakehouse Architecture Explained

Monte Carlo

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. ok, so maybe they don’t say that.

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Most important Data Engineering Concepts and Tools for Data Scientists

DareData

Learn the most important data engineering concepts that data scientists should be aware of. As the field of data science and machine learning continues to evolve, it is increasingly evident that data engineering cannot be separated from it.