Bridging the Gap

FEBRUARY 16, 2023

Step 1 – Determine the Scope of the Change The very first step is to determine the scope of the change. A change request could be related to the business requirements, the stakeholder requirements, the functional requirements , the data requirements. Any aspect of the project.

Documentation 98

Documentation Planning Business Analysis Business Analysis 98

Astera

AUGUST 15, 2024

It’s also more contextual than general data orchestration since it’s tied to the operational logic at the core of a specific pipeline. Since data pipeline orchestration executes an interconnected chain of events in a specific sequence, it caters to the unique data requirements a pipeline is designed to fulfill.

Data Quality 52

Data Quality Monitoring Artificial Intelligence Government 52

Cprime

NOVEMBER 28, 2023

The spotlight was on their data, necessitating a migration of their Jira and Confluence systems from server to Cloud. The scope of the migration included the entirety of Jira and Confluence data and plug-ins. Additional intricacies arose in the form of change management, logging, and the setup of OKTA.

User Experience 52

User Experience Government Data Security Customer Experience 52

Astera

MARCH 20, 2024

This includes identifying and mapping all your data sources, understanding their formats, assessing their quality, defining ownership, and establishing security and access controls. Technology and Tools: Equip your team with the right software and infrastructure for managing enterprise data at scale.

Data Management 52

Data Management Master Data Management Data Quality Government 52

Astera

MAY 25, 2023

However, businesses can also leverage data integration and management tools to enhance their security posture. How is big data secured? Big data is extremely valuable, but also vulnerable. Protecting big data requires a multi-faceted approach to security.

Big Data 40

Big Data Data Security Monitoring Data Quality 40

Astera

JANUARY 12, 2024

Flexibility While they differ in their degree of flexibility, both Data Vault and Data Mesh aim to provide solutions that are adaptable to changing data requirements. Data Vault achieves this through versioning and change management, while Data Mesh relies on domain teams to adapt their data products.

Data Architecture 52

Data Architecture Data Warehouse Data Quality Government 52