Pickl AI

FEBRUARY 23, 2025

Introduction to Big Data Tools In todays data-driven world, organisations are inundated with vast amounts of information generated from various sources, including social media, IoT devices, transactions, and more. Big Data tools are essential for effectively managing and analysing this wealth of information. Use Cases : Yahoo!

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Big Data Big Data Apache Hadoop Apache Kafka 52

AWS Machine Learning Blog

OCTOBER 9, 2024

Using Amazon CloudWatch for anomaly detection Amazon CloudWatch supports creating anomaly detectors on specific Amazon CloudWatch Log Groups by applying statistical and ML algorithms to CloudWatch metrics. Use AWS Glue Data Quality to understand the anomaly and provide feedback to tune the ML model for accurate detection.

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Pickl AI

SEPTEMBER 18, 2024

The architecture is divided into two main categories: data at rest and data in motion. Data at Rest This includes storage solutions such as S3 Data Warehouse and Cassandra. These systems handle the storage costs associated with keeping vast amounts of content and user data.

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Big Data Big Data Apache Kafka Big Data Analytics 52

Pickl AI

AUGUST 9, 2024

Data Warehousing Solutions Tools like Amazon Redshift, Google BigQuery, and Snowflake enable organisations to store and analyse large volumes of data efficiently. Students should learn about the architecture of data warehouses and how they differ from traditional databases.

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Pickl AI

DECEMBER 9, 2024

What is Apache Hive? Hive is a data warehouse tool built on Hadoop that enables SQL-like querying to analyse large datasets. What is the Difference Between Structured and Unstructured Data? What is Apache Kafka, and Why is it Used? Explain the CAP theorem and its relevance in Big Data systems.

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Pickl AI

JULY 8, 2024

NoSQL Databases: Flexible, scalable solutions for unstructured or semi-structured data. Data Warehouses : Centralised repositories optimised for analytics and reporting. Data Lakes : Scalable storage for raw and processed data, supporting diverse data types.

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Pickl AI

JULY 29, 2024

Machine Learning and Predictive Analytics Hadoop’s distributed processing capabilities make it ideal for training Machine Learning models and running predictive analytics algorithms on large datasets. Organisations that require low-latency data analysis may find Hadoop insufficient for their needs.

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Hadoop Clustering Big Data Big Data 52