Pickl AI

FEBRUARY 23, 2025

Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. Machine Learning Integration : Built-in ML capabilities streamline model development and deployment.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52

AWS Machine Learning Blog

OCTOBER 9, 2024

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required. To learn more, see the documentation.

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AWS ML ML Data Quality 92

AWS Machine Learning Blog

JANUARY 6, 2023

The rules in this engine were predefined and written in SQL, which aside from posing a challenge to manage, also struggled to cope with the proliferation of data from TR’s various integrated data source. TR customer data is changing at a faster rate than the business rules can evolve to reflect changing customer needs.

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AWS Data Warehouse ML ML 91

Alation

AUGUST 4, 2022

Spark, Tensorflow, Apache Kafka, et cetera, are all out found in cloud databases,” points out Jones. “File-based storage of data is the norm even under more relational models. [In This includes the ability to handle large volumes of unstructured data.”. Clearly, it is easy to create a bias in training data.

Big Data 95

Big Data Big Data Apache Kafka Data Lakes 95

Mlearning.ai

MAY 16, 2023

It is used to extract data from various sources, transform the data to fit a specific data model or schema, and then load the transformed data into a target system such as a data warehouse or a database. In the extraction phase, the data is collected from various sources and brought into a staging area.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 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

The MLOps Blog

MARCH 15, 2023

Data pipeline stages But before delving deeper into the technical aspects of these tools, let’s quickly understand the core components of a data pipeline succinctly captured in the image below: Data pipeline stages | Source: Author What does a good data pipeline look like? Credits can be purchased for 14 cents per minute.

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Data Pipeline ETL SQL Data Quality 59