Remove 2023 Remove Data Governance Remove Data Warehouse
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Essential data engineering tools for 2023: Empowering for management and analysis

Data Science Dojo

Data engineering tools offer a range of features and functionalities, including data integration, data transformation, data quality management, workflow orchestration, and data visualization. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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Trends in Data Governance and Security: What to Prepare for in 2024

Dataversity

Organizations learned a valuable lesson in 2023: It isn’t sufficient to rely on securing data once it has landed in a cloud data warehouse or analytical store. As a result, data owners are highly motivated to explore technologies in 2024 that can protect data from the moment it begins its journey in the source systems.

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Top 9 Data Management Tools to Use in 2023

Analytics Vidhya

To steer growth, employ effective data management strategies and tools. This article explores data management’s key tool features and lists the top tools for 2023. Why Use Data […] The post Top 9 Data Management Tools to Use in 2023 appeared first on Analytics Vidhya.

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Optimizing data flexibility and performance with hybrid cloud 

IBM Journey to AI blog

Enhancing AI and analytics with unified data access  Hybrid cloud architectures are proving instrumental in advancing AI and analytics capabilities. A 2023 Gartner survey reveals that “two out of three enterprises use hybrid cloud to power their AI initiatives”, underscoring its critical role in modern data strategies.

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IBM to help businesses scale AI workloads, for all data, anywhere

IBM Journey to AI blog

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data?

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Journey to AI blog

Thus, DB2 PureScale on AWS equips this insurance company to innovate and make data-driven decisions rapidly, maintaining a competitive edge in a saturated market. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

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Data Integrity vs. Data Quality: How Are They Different?

Precisely

For instance, you may have a database of customer names and addresses that is accurate and valid, but if you do not also have supporting data that gives you context about those customers and their relationship to your company, that database is not as useful as it could be. That is where data integrity comes into play.