Remove Data Modeling Remove Data Silos Remove ETL
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How AI and ML Can Transform Data Integration

Smart Data Collective

In this new reality, leveraging processes like ETL (Extract, Transform, Load) or API (Application Programming Interface) alone to handle the data deluge is not enough. As per the TDWI survey, more than a third (nearly 37%) of people has shown dissatisfaction with their ability to access and integrate complex data streams.

ML 131
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The Evolution of Customer Data Modeling: From Static Profiles to Dynamic Customer 360

phData

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

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What is Data Integration in Data Mining with Example?

Pickl AI

Understanding Data Integration in Data Mining Data integration is the process of combining data from different sources. Thus creating a consolidated view of the data while eliminating data silos. Limited Scalability : The process is not workable for handling large volumes of data.

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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.