Dataversity

OCTOBER 23, 2023

This problem will become more complex as organizations adopt new resource-intensive technologies like AI and generate even more data. By 2025, the IDC expects worldwide data to reach 175 zettabytes, more […] The post Why Master Data Management (MDM) and AI Go Hand in Hand appeared first on DATAVERSITY.

Master Data Management 162

Master Data Management Data Management Data Quality Data Governance 162

Dataversity

MARCH 28, 2022

Businesses today collect and store an astonishing amount of data. According to estimates from IDC, 163 zettabytes of data will have been created worldwide by 2025. However, this data is not always useful to business leaders until it is organized to be of higher quality and reliability.

Data Quality 130

Data Quality Data Governance Government Data Management 130

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 173

Data Warehouse Data Quality Data Governance Government 173

Astera

APRIL 29, 2024

An effective data governance strategy is crucial to manage and oversee data effectively, especially as data becomes more critical and technologies evolve. What is a Data Governance Strategy? A vital aspect of this strategy includes sharing data seamlessly.

Data Governance 52

Data Governance Government IBM Maintenance Data Quality 52

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 130

Big Data Data Analytics Data Analytics Data Management 130

Astera

MAY 14, 2024

This metadata variation ensures proper data interpretation by software programs. Process metadata: tracks data handling steps. It ensures data quality and reproducibility by documenting how the data was derived and transformed, including its origin. These value additions are only the tip of the iceberg.

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