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.

AWS 94

AWS ML ML Data Quality 94

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.

Big Data 52

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.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

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.

Big Data 52

Big Data Big Data Hadoop Apache Kafka 52

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.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

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.

Hadoop 52

Hadoop Clustering Big Data Big Data 52

The MLOps Blog

MARCH 15, 2023

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. Credits can be purchased for 14 cents per minute.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59