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How To Use Oracle GoldenGate to Ingest Data Into Snowflake

phData

Create a Directory where GoldenGate will be Installed Download and Extract GoldenGate for Big Data This should be extracted into the directory location created in step 1. Download the Snowflake-JDBC Driver JAR File That can be done here. share/hadoop/common/*:hadoop-3.2.1/share/hadoop/common/lib/*:hadoop-3.2.1/share/hadoop/hdfs/*:hadoop-3.2.1/share/hadoop/hdfs/lib/*:hadoop-3.2.1/etc/hadoop/:hadoop-3.2.1/share/hadoop/tools/lib/*

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Best 8 Data Version Control Tools for Machine Learning 2024

DagsHub

Released in 2022, DagsHub’s Direct Data Access (DDA for short) allows Data Scientists and Machine Learning engineers to stream files from DagsHub repository without needing to download them to their local environment ahead of time. This can prevent lengthy data downloads to the local disks before initiating their mode training.

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Learn the Difference between Big Data and Cloud Computing

Pickl AI

Cloud platforms like AWS and Azure support Big Data tools, reducing costs and improving scalability. Companies like Amazon Web Services (AWS) and Microsoft Azure provide this service. Software as a Service (SaaS) : Services like Gmail, Zoom, and Dropbox let you use applications online without downloading them.

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How to Manage Unstructured Data in AI and Machine Learning Projects

DagsHub

Popular data lake solutions include Amazon S3 , Azure Data Lake , and Hadoop. Apache Hadoop Apache Hadoop is an open-source framework that supports the distributed processing of large datasets across clusters of computers. Data Processing Tools These tools are essential for handling large volumes of unstructured data.

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How to Version Control Data in ML for Various Data Sources

The MLOps Blog

It supports most major cloud providers, such as AWS, GCP, and Azure. When we download a Git repository, we also get the.dvc files which we use to download the data associated with them. LakeFS is fully compatible with many ecosystems of data engineering tools such as AWS, Azure, Spark, Databrick, MlFlow, Hadoop and others.

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How Comet Can Serve Your LLM Project from Pre-Training to Post-Deployment

Heartbeat

Comet’s data management feature allows users to manage their training data, including downloading, storing, and preprocessing data. Comet also integrates with popular data storage and processing tools like Amazon S3, Google Cloud Storage, and Hadoop.