Smart Data Collective

APRIL 29, 2020

Data management approaches are varied and may be categorised in the following: Cloud data management. The storage and processing of data through a cloud-based system of applications. Master data management. The tool assigns the role of ‘data stewards’ in an organisation to manage master data.

Data Management 213

Data Management Data Warehouse Master Data Management Digital Transformation 213

Astera

JANUARY 19, 2024

Mulesoft and Its Key Features MuleSoft provides a unified integration platform for connecting applications, data, and devices on-premises and in the cloud. Built on Java, its Anypoint Platform acts as a comprehensive solution for API management, design, monitoring, and analytics. Key Features: Drag-and-drop user interface.

IBM Support 52

IBM Support IBM cost IBM Maintenance Data Warehouse 52

Astera

NOVEMBER 1, 2023

Credit rating agencies may use data from credit bureaus to evaluate creditworthiness and assign credit ratings to borrowers.   Data Quality Management   Data quality management involves monitoring and controlling data quality to ensure its suitability for the intended purpose.

Data Governance 40

Data Governance Government Data Quality Banking 40

Astera

MARCH 20, 2024

This article covers everything about enterprise data management, including its definition, components, comparison with master data management, benefits, and best practices. What Is Enterprise Data Management (EDM)? Management of all enterprise data, including master data.

Data Management 52

Data Management Master Data Management Data Warehouse Government 52

Astera

AUGUST 8, 2023

Reusable Scripts: Astera streamlines data preparation with efficient, reusable scripts across workflows, promoting automation, efficiency, and consistency. Data Security and Compliance: The tool has security and compliance features, safeguarding your data and ensuring adherence to relevant regulations.

Data Quality 52

Data Quality IBM Support IBM Maintenance Monitoring 52

Astera

JANUARY 2, 2024

Execution and handling of data operations. Objective Ensure data quality, security, and compliance. Efficient and effective handling of data. Activities Policy creation, enforcement, and monitoring. Data collection, storage, processing, and usage. Addresses immediate data handling requirements.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

JULY 13, 2023

One of the key benefits of a data lake is that it can also store unstructured data, such as social media posts, emails, and documents. This makes it a valuable resource for organizations that need to analyze a wide range of data types.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40