Remove Cloud Storage Remove Data Ingestion Remove Data Lake Remove Raw Data
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Top Data Lake Vendors (Quick Reference Guide)

Monte Carlo

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

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Consulting Case Study: Job Market Analysis

WeCloudData

Conclusion WeCloudData helped a client build a flexible data pipeline to address the needs from multiple business units requiring different sets, views and timelines of job market data.

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Consulting Case Study: Job Market Analysis

WeCloudData

Conclusion WeCloudData helped a client build a flexible data pipeline to address the needs from multiple business units requiring different sets, views and timelines of job market data.

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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. The process requires extracting data from diverse sources, typically via APIs. Hadoop, Apache Spark).

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What is a Data Platform? And How to Build An Awesome One

Monte Carlo

We’ll cover: What is a data platform? With companies moving their data platforms to the cloud, the emergence of cloud-native solutions ( data warehouse vs data lake or even a data lakehouse ) have taken over the market, offering more accessible and affordable options for storing data relative to many on-premises solutions.

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The Good and the Bad of Databricks Lakehouse Platform

AltexSoft

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.