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Data

Data is the fundamental resource that powers business operations and drives strategic decisions. We cover modern data practices, including data as a service (DaaS) for companies, data transformation challenges, and data management use cases. Our coverage also includes training data platforms, best practices for data commercialization and versioning, and the critical role of data curation.

Explore Data

Data Transformation: Challenges & Real-life examples

DataSep 17

Data is the cornerstone in many sectors, underpinning decision-making processes in business, government, health, and more. The advent of generative AI has heightened the importance of data and its various applications. Organizations must understand and proficiently implement data transformation processes to unlock the full potential of it.

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DataJul 31

Top 13 Training Data Platforms

Data is an essential part of the quality of machine learning models. Supervised AI/ML models require high-quality data to make accurate predictions. Training data platforms streamline data preparation from collection to annotation, ensuring high-quality inputs for AI systems.

DataJul 26

Data Curation: Key Concepts and Best Practices

Data curation is an important part of data management. Data curation is the process of collecting, wrangling and preserving data. It allows companies to store sustainable and accessible data to share and apply self-service analytics. Data-driven insights are crucial as data-driven sales strategies enable companies improve their sales productivity by 20 %.

DataJul 25

7 Master Data Management Use Cases

In this article, we explain 7 master data management use cases. Master data management has been frequently searched since the 2020s.

DataJun 13

7 Key Data Fabric Use Cases

In this article, we explain 7 key data fabric use cases such as data integartion, data analytics, data governance, and data virtualization.

DataMay 19

Data Versioning: Top 3 Benefits & Best Practices

Companies rely on AI/ML models to make business decisions. Effective AI/ML models require high-quality data to make accurate predictions about future conditions. That’s why data is called the new oil for which successful companies need their own refinery.

DataApr 3

Data Commercialization: Risks and Best Practices

Companies in every industry use data to create value and manage data as an asset. They collect and analyze huge amounts of data coming from various sources. The increasing availability of data enables businesses to make real-time decisions.

DataMar 24

Top 10 Data as a Service Companies

Data fuels generative AI and enterprise innovation. Data as a Service (DaaS) is a cloud computing model that provides data on demand to users, usually on a subscription basis. This streamlines data collection and management.