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

OCTOBER 12, 2023

Accounting for the complexities of the AI lifecycle Unfortunately, typical data storage and data governance tools fall short in the AI arena when it comes to helping an organization perform the tasks that underline efficient and responsible AI lifecycle management. And that makes sense.

AI 93

AI AI Data Scientist Data Governance 93

Pickl AI

NOVEMBER 4, 2024

Key Takeaways Data Engineering is vital for transforming raw data into actionable insights. Key components include data modelling, warehousing, pipelines, and integration. Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 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. But it’s not so simple. With growth comes complexity.

AI 45

AI AI Data Quality Database 45