Pickl AI

NOVEMBER 25, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. What is Big Data? How Does Big Data Ensure Data Quality?

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Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

DECEMBER 9, 2024

DataNodes store the actual data blocks and respond to requests from the NameNode. YARN (Yet Another Resource Negotiator) manages resources and schedules jobs in a Hadoop cluster. What are Some Popular Big Data tools? Popular storage, processing, and data movement tools include Hadoop, Apache Spark, Hive, Kafka, and Flume.

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Big Data Big Data Hadoop Apache Kafka 52

Pickl AI

AUGUST 9, 2024

Big Data Technologies and Tools A comprehensive syllabus should introduce students to the key technologies and tools used in Big Data analytics. Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers.

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Big Data Big Data Big Data Analytics Big Data Analytics 52

DagsHub

JANUARY 14, 2025

Clustering: Clustering can group texts using features like embedding vectors or TF-IDF vectors. Duplicate texts naturally tend to fall into the same clusters. Unsupervised algorithms like K-Means clustering, DBSCAN are prevalently used to create the text clusters. Clustering Techniques (e.g.,

Machine Learning 52

Machine Learning Machine Learning Clustering Algorithm 52

Mlearning.ai

MAY 16, 2023

The events can be published to a message broker such as Apache Kafka or Google Cloud Pub/Sub. The message broker can then distribute the events to various subscribers such as data processing pipelines, machine learning models, and real-time analytics dashboards. Here’s a high-level overview of how the MapReduce pattern works: A.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

The MLOps Blog

MARCH 15, 2023

Scalability : A data pipeline is designed to handle large volumes of data, making it possible to process and analyze data in real-time, even as the data grows. Data quality : A data pipeline can help improve the quality of data by automating the process of cleaning and transforming the data.

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Data Pipeline ETL SQL Data Quality 59

DagsHub

OCTOBER 23, 2024

Data Processing Tools These tools are essential for handling large volumes of unstructured data. They assist in efficiently managing and processing data from multiple sources, ensuring smooth integration and analysis across diverse formats. It allows unstructured data to be moved and processed easily between systems.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

The MLOps Blog

AUGUST 11, 2023

1 Data Ingestion (e.g., Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., Embeddings provide a lower-dimensional representation of high-dimensional data that retains key patterns and information. Other areas in ML pipelines: transfer learning, anomaly detection, vector similarity search, clustering, etc.

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