Pickl AI

DECEMBER 25, 2024

Summary: Data silos are isolated data repositories within organisations that hinder access and collaboration. Eliminating data silos enhances decision-making, improves operational efficiency, and fosters a collaborative environment, ultimately leading to better customer experiences and business outcomes.

Data Silos 52

Data Silos Database Data Quality ETL 52

Dataconomy

JUNE 18, 2025

Accessibility for analytics Centralized data repositories enhance access for analysts and data scientists, streamlining robust data analysis and allowing for comprehensive insights that drive strategic decisions. Data integration fosters a more interconnected environment, enabling seamless information flow.

Data Warehouse 91

Data Warehouse Data Silos ETL Big Data 91

IBM Data Science in Practice

NOVEMBER 28, 2022

Insights from data gathered across business units improve business outcomes, but having heterogeneous data from disparate applications and storages makes it difficult for organizations to paint a big picture. How can organizations get a holistic view of data when it’s distributed across data silos?

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

Women in Big Data

MARCH 5, 2025

I worked extensively with ETL processes, PostgreSQL, and later, enterprise-scale data systems. Ive always had a logical, data-driven mindset, constantly digging deeper into metrics and questioning assumptions. In simple terms, we help businesses modernize, democratize and transform their data.

ML 52

ML ML Big Data Big Data 52

Pickl AI

JUNE 28, 2023

Understanding Data Integration in Data Mining Data integration is the process of combining data from different sources. Thus creating a consolidated view of the data while eliminating data silos. Limited Scalability : The process is not workable for handling large volumes of data.

Data Mining 52

Data Mining Data Mining Data Mining ETL 52

phData

NOVEMBER 9, 2023

The primary objective of this idea is to democratize data and make it transparent by breaking down data silos that cause friction when solving business problems. What Components Make up the Snowflake Data Cloud?

Data Warehouse 98

Data Warehouse Data Lakes Clustering Cloud Data 98

ODSC - Open Data Science

SEPTEMBER 29, 2023

A 2019 survey by McKinsey on global data transformation revealed that 30 percent of total time spent by enterprise IT teams was spent on non-value-added tasks related to poor data quality and availability. The data lake can then refine, enrich, index, and analyze that data. It truly is an all-in-one data lake solution.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52