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Reducing Data Complexity


Table of contents


In the beginning, we list questions to address in enterprises to enable efficient data standardisation and management.

02Solving Problem: Fragmented, Inconsistent, and Siloed Data Across Various Systems

Find out the most common challenges for businesses in data integration and processing.

03Data Mapping: Foundations of Data Standardisation and Unification

In this chapter, we depict the three primary components of data mapping which are Source Schema, Mapping Rules, and Target Schema. We also explain the three most common mapping methodologies with their advantages, disadvantages, and ideal use cases.

04Data Governance: Navigating the Control and Quality

In this section, we discuss terms related to data governance and guide you through the role of metadata. We also show you what are roles and responsibilities of stakeholders from various organization divisions in efficient data management.

05Integration Strategies: Bringing Data Together

Data integration is key to holistic analysis and bridging the knowledge gap. We show you how to create an integration strategy step by step.

06Data Future Proofing: To-Be State is Just the Beginning

In this chapter, we look ahead and show how emerging technologies will affect the use and analysis of data in the coming years. This is important in terms of how to prepare data today to make the best use of it in the future.

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Reducing Data Complexity

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