Alation

FEBRUARY 20, 2020

Even something like gamification may emerge as a way to fully engage data shoppers as a community. Behind the scenes, ‘backroom services” will power the storefront, performing such tasks as data acquisition, data preparation, data curation and cataloging, and tracking. Building the EDM.

Data Warehouse 52

Data Warehouse Data Lakes Hadoop Data Preparation 52

DataRobot Blog

OCTOBER 3, 2017

Standard Chartered Bank’s Global Head of Technology, Santhosh Mahendiran , discussed the democratization of data across 3,500+ business users in 68 countries. Paxata booth visitors encompassed a broad range of roles, all with data responsibility in some shape or form.

Data Lakes 52

Data Lakes Azure Data Pipeline Hadoop 52

ODSC - Open Data Science

OCTOBER 7, 2024

Understanding the MLOps Lifecycle The MLOps lifecycle consists of several critical stages, each with its unique challenges: Data Ingestion: Collecting data from various sources and ensuring it’s available for analysis. Data Preparation: Cleaning and transforming raw data to make it usable for machine learning.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Pickl AI

NOVEMBER 28, 2024

Data Transformation Transforming data prepares it for Machine Learning models. Encoding categorical variables converts non-numeric data into a usable format for ML models, often using techniques like one-hot encoding. Outlier detection identifies extreme values that may skew results and can be removed or adjusted.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

OCTOBER 10, 2024

It integrates well with cloud services, databases, and big data platforms like Hadoop, making it suitable for various data environments. Typical use cases include ETL (Extract, Transform, Load) tasks, data quality enhancement, and data governance across various industries.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

Pickl AI

DECEMBER 4, 2024

Augmented Analytics Augmented analytics is revolutionising the way businesses analyse data by integrating Artificial Intelligence (AI) and Machine Learning (ML) into analytics processes. Gain Experience with Big Data Technologies With the rise of Big Data, familiarity with technologies like Hadoop and Spark is essential.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

The MLOps Blog

MAY 31, 2023

The objective of an ML Platform is to automate repetitive tasks and streamline the processes starting from data preparation to model deployment and monitoring. One might want to utilize an off-the-shelf ML Ops Platform to maintain different versions of data. How to set up a data processing platform?

ML 59

ML ML Algorithm Machine Learning 59

Dataconomy

MARCH 19, 2025

Key disciplines involved in data science Understanding the core disciplines within data science provides a comprehensive perspective on the field’s multifaceted nature. Overview of core disciplines Data science encompasses several key disciplines including data engineering, data preparation, and predictive analytics.

Data Science 91

Data Science Citizen Data Scientist Data Scientist Machine Learning 91