O'Reilly on Data

OCTOBER 19, 2021

In this article, we want to dig deeper into the fundamentals of machine learning as an engineering discipline and outline answers to key questions: Why does ML need special treatment in the first place? ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses.

IT 364

IT Testing Experimentation Software 364

CIO Business Intelligence

APRIL 8, 2025

These issues dont just hinder next-gen analytics and AI; they erode trust, delay transformation and diminish business value. Data quality is no longer a back-office concern. In this article, I am drawing from firsthand experience working with CIOs, CDOs, CTOs and transformation leaders across industries. federal agencies.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

Cloudera

JUNE 1, 2021

And, the Enterprise Data Cloud category we invented is also growing. In fact, recent articles by Patrick Moorhead , Mike Feibus , and many others represent a clear trend toward integrated data platforms. Said simply, Datacoral offers a fully-managed service for worry-free data integrations.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. This article endeavors to alleviate those confusions.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Smarten

AUGUST 4, 2023

Gartner predicts that, ‘data preparation will become a critical capability in more than 60% of data integration, analytics/BI, data science, data engineering and data lake enablement platforms.’ In this article, we look at the features and capabilities of a comprehensive self-serve data prep solution.

Data Lake 52

Data Lake Machine Learning Data Integration Data Quality 52

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84