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What is a data fabric?

Tableau

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Data modeling. Data preparation. Data integration. Orchestration.

Tableau 101
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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 a data fabric?

Tableau

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Data modeling. Data preparation. Data integration. Orchestration.

Tableau 98
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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. It ensures that the integrated data is available for analysis and reporting. Wrapping It Up !!!

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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.

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Why the Next Generation of Data Management Begins with Data Fabrics

Dataversity

However, most enterprises are hampered by data strategies that leave teams flat-footed when […]. The post Why the Next Generation of Data Management Begins with Data Fabrics appeared first on DATAVERSITY. Click to learn more about author Kendall Clark. The mandate for IT to deliver business value has never been stronger.

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Most Common Use Cases of Data Engineering in Healthcare

phData

Real-Time Data Processing and Predictive Insights for Patients Healthcare professionals need to make quick and informed decisions to help save lives. Through big data models, hospitals can identify trends that guide smart decision-making. Real-time data analysis could also detect irregular heartbeats that could save lives.