Data Science Dojo

JANUARY 12, 2023

When it comes to data, there are two main types: data lakes and data warehouses. Which one is right for your business? 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.

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

AWS Machine Learning Blog

OCTOBER 24, 2024

Conventional ML development cycles take weeks to many months and requires sparse data science understanding and ML development skills. Business analysts’ ideas to use ML models often sit in prolonged backlogs because of data engineering and data science team’s bandwidth and data preparation activities.

Data Warehouse 110

Data Warehouse Machine Learning Machine Learning Cloud Data 110

Data Science Dojo

SEPTEMBER 11, 2024

These experiences facilitate professionals from ingesting data from different sources into a unified environment and pipelining the ingestion, transformation, and processing of data to developing predictive models and analyzing the data by visualization in interactive BI reports.

Power BI 284

Power BI Data Pipeline Data Warehouse Data Engineering 284

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

ODSC - Open Data Science

JUNE 12, 2023

They all agree that a Datamart is a subject-oriented subset of a data warehouse focusing on a particular business unit, department, subject area, or business functionality. The Datamart’s data is usually stored in databases containing a moving frame required for data analysis, not the full history of data.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

IBM Journey to AI blog

DECEMBER 7, 2023

Today, OLAP database systems have become comprehensive and integrated data analytics platforms, addressing the diverse needs of modern businesses. They are seamlessly integrated with cloud-based data warehouses, facilitating the collection, storage and analysis of data from various sources.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

IBM Journey to AI blog

JULY 17, 2023

Visual modeling: Delivers easy-to-use workflows for data scientists to build data preparation and predictive machine learning pipelines that include text analytics, visualizations and a variety of modeling methods. It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud.

AI 74

AI AI Machine Learning Machine Learning 74