Data Science Dojo

JANUARY 12, 2023

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Which one is right for your business?

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

Dataconomy

MARCH 4, 2025

The data mining process The data mining process is structured into four primary stages: data gathering, data preparation, data mining, and data analysis and interpretation. Each stage is crucial for deriving meaningful insights from data.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

Dataconomy

FEBRUARY 26, 2025

KDD provides a structured framework to convert raw data into actionable knowledge. The KDD process Data gathering Data preparation Data mining Data analysis and interpretation Data mining process components Understanding the components of the data mining process is essential for effective implementation.

Data Mining 91

Data Mining Data Mining Data Mining Data Preparation 91

AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

AWS 98

AWS Data Lakes Clustering Data Preparation 98

AWS Machine Learning Blog

AUGUST 15, 2024

You need data engineering expertise and time to develop the proper scripts and pipelines to wrangle, clean, and transform data. Afterward, you need to manage complex clusters to process and train your ML models over these large-scale datasets. These features can find temporal patterns in the data that can influence the baseFare.

ML 131

ML ML Data Preparation AWS 131

Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Here we use RedshiftDatasetDefinition to retrieve the dataset from the Redshift cluster.

ML 119

ML ML AWS Data Warehouse 119

Pickl AI

FEBRUARY 21, 2023

The data locations may come from the data warehouse or data lake with structured and unstructured data. The Data Scientist’s responsibility is to move the data to a data lake or warehouse for the different data mining processes. are the various data mining tools.

Data Mining 52

Data Mining Data Mining Data Mining Data Scientist 52