ODSC - Open Data Science

SEPTEMBER 29, 2023

Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate. and various countries in Europe.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Dataversity

DECEMBER 16, 2020

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Most organizations do not utilize the entirety of the data […].

Data Warehouse 69

Data Warehouse Data Lakes Data Profiling Data Quality 69

Pickl AI

DECEMBER 2, 2024

Introduction In today’s digital age, the volume of data generated is staggering. According to a report by Statista, the global data sphere is expected to reach 180 zettabytes by 2025 , a significant increase from 33 zettabytes in 2018. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Introduction In today’s digital age, the volume of data generated is staggering. According to a report by Statista, the global data sphere is expected to reach 180 zettabytes by 2025 , a significant increase from 33 zettabytes in 2018. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

IBM Journey to AI blog

JULY 3, 2024

The quality and quantity of data can make or break AI success, and organizations that effectively harness and manage their data will reap the most benefits. Data is exploding, both in volume and in variety. Effective data quality management is crucial to mitigating these risks. But it’s not so simple.

AI 45

AI AI Data Quality Database 45

Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

IBM Journey to AI blog

OCTOBER 12, 2023

AI-optimized data stores enable cost-effective AI workload scalability AI models rely on secure access to trustworthy data, but organizations seeking to deploy and scale these models face an increasingly large and complicated data landscape.

AI 93

AI AI Data Scientist Data Governance 93