I recently wrote about the importance of data pipelines and the role they play in transporting data between the stages of data processing and analytics. Healthy data pipelines are necessary to ensure data is integrated and processed in the sequence required to generate business intelligence. The concept of the data pipeline is nothing new of course, but it is becoming increasingly important as organizations adapt data management processes to be more data driven.
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Topics:
business intelligence,
Analytics,
Data Governance,
Data Integration,
Data,
Digital Technology,
Digital transformation,
data lakes,
data operations,
Digital Business,
Data Platforms,
Analytics & Data,
Streaming Data & Events,
AI and Machine Learning
Data governance is an issue that impacts all organizations large and small, new and old, in every industry, and every region of the world. Data governance ensures that an organization’s data can be cataloged, trusted and protected, improving business processes to accelerate analytics initiatives and support compliance with regulatory requirements. Not all data governance initiatives will be driven by regulatory compliance; however, the risk of falling foul of privacy (and human rights) laws...
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Topics:
Analytics,
Data Governance,
Data
I recently described the growing level of interest in data mesh which provides an organizational and cultural approach to data ownership, access and governance that facilitates distributed data processing. As I stated in my Analyst Perspective, data mesh is not a product that can be acquired or even a technical architecture that can be built. Adopting the data mesh approach is dependent on people and process change to overcome traditional reliance on centralized ownership of data and...
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Topics:
Business Continuity,
business intelligence,
Analytics,
Data Governance,
Data Integration,
Data,
Digital Technology,
data lakes,
Digital Business,
Data Platforms,
Analytics & Data