Data mastering is the process of integrating and normalizing data from different sources to create a unified and accurate dataset.

The array discusses the challenges of data federation and proposes a future data integration system with various components.

Pharmaceutical company improves decision-making and brings medicines to patients faster through data unification and analytics.

Analytic developers need reliable and credible data for dashboards, and establishing an analytic quality assurance process is crucial.

Enterprises face challenges in leveraging and managing data. Steps to create a data-driven culture include skill development and implementing the right solutions.

DataOps is a methodology used to improve data analytics by automating processes and reducing errors, but adoption is still low.

Traditional ETL/MDM processes for data integration and cleaning are not scalable; machine learning is needed for large-scale integration.

Enterprises face challenges in leveraging their data due to the variety of formats, structures, and silos, but human-guided machine learning can help overcome these obstacles.

This text discusses managing and testing Tableau extensions, ensuring security, and educating users for better dashboard functionality.

Tamr's data unification platform incorporates geospatial data to optimize analytics and achieve transformational outcomes for enterprises.

Oil and gas companies can benefit from data unification and analysis to make smarter decisions and improve well production.

This array describes various Tableau extensions that enhance functionality and improve data analysis and visualization in Tableau.

Tableau introduced extensions to enhance functionality, allowing developers to build custom integrations and connect with outside applications.

Banks are using big data analytics to improve compliance, understand customer needs, and streamline operations through machine learning.

The article discusses the connection between the scientific method, data science, and the importance of understanding and improving data quality in DataOps.

DataOps is an automated methodology that improves data analytics by delivering timely, high-quality data to meet changing business needs.

The article discusses the limitations of traditional data mastering methods and highlights the benefits of Tamr's cloud-native, ML-based approach.

The Tamr RWE Integration Solution combines human expertise and machine learning to integrate and apply real world data in healthcare.

Scotiabank used a machine learning model to unify customer data from multiple systems, resulting in improved analytics and efficiency.