TDWI

As organizations try to keep up with new data types and become more advanced analytically, they must evolve and improve their data management practices.Numerous interrelated factors contribute to the current state of data management. Many organizations are trying to unify their data for analysis, which may include a logical or physical architecture. Some enterprises are using cloud data stacks to store and manage their data; others are using a data fabric to stitch data together across multiple environments. Some are hiring CDOs or implementing DataOps to handle complex data pipelines.Modern...

As organizations strive to keep up with increasingly complex data and enhance their analytical capabilities, they often need to transform their data management practices. TDWI has observed that many organizations are migrating to the cloud or already have hybrid models in place that involve both on-premises and cloud platforms. Some are utilizing cloud data stacks to manage and store their data, while others use a data fabric strategy to integrate data across multiple environments, both on premises and in the cloud.To better understand and manage their data, they are implementing data...

Enterprises are under increasing pressure to address social, environmental, and other responsible outcomes in their digital operations. To stay ahead of the curve, data management and analytics professionals have begun to address such topics as ethics, equity, fairness, safety, and sustainability in their strategic planning and operational practices.This TDWI Best Practices Report examines where organizations are today in terms of responsible data and analytics and what work they still need to do. It also addresses organizational imperatives and technologies to help organizations become more...

This six-day conference is designed for data professionals and leaders tasked with:Building effective data strategies, agile processes, and scalable architectures for data-driven decision-makingTransforming business through machine learning and data scienceDelivering impactful dashboards, BI, and self-service information products Designing and managing the data assets that power BI and analyticsEnsuring compliance, privacy, and data quality through data governance Elevating data literacy through data visualization and storytellingBuild new skills, network with peers and industry experts, and...

Presented at TDWI VIRTUAL SUMMIT - Modernizing Data ManagementWhile the technological advances of the past decade have addressed the scale of data processing and data storage, they have failed to address scale in other dimensions: proliferation of sources of data, diversity of data types and user persona, and speed of response to change. The essence of the data mesh and data fabric approaches is that it puts the customer first and focuses on outcomes instead of outputs.In this session, Saptarshi Sengupta, Senior Director of Product Marketing at Denodo, will address key considerations and...

Nobody needs to tell organizations dependent on supply chains that recent times have been full of uncertainty. Disruptions, economic challenges, global crises, and sudden changes in consumer demand continue to test resilience and agility. Supply chains today are complex and global, often involving hundreds, if not thousands, of suppliers and products at different stages of the journey from raw materials to finished goods in the hands of customers. However, data is distributed everywhere across global supply chains, and it is not always accessible, usable, up-to-date, or well governed....

Maximizing the value of data platforms with data integration and data management capabilities is essential for organizations that want to become data- and analytics-driven. Increasingly—but not entirely—based in the cloud, these systems and services are the engine of modern applications and smarter processes for higher business efficiency and innovation.Research indicates the need for tighter integration between two traditionally separate worlds: one devoted to analytics generation and the data integration, platforms, and management that support analytics, and the other devoted to mission-...

Nobody needs to tell organizations dependent on supply chains that recent times have been full of uncertainty. Disruptions, economic challenges, global crises, and sudden changes in consumer demand continue to test resilience and agility. Supply chains today are complex and global, often involving hundreds, if not thousands, of suppliers and products at different stages of the journey from raw materials to finished goods in the hands of customers. However, data is distributed everywhere across global supply chains, and it is not always accessible, usable, up-to-date, or well governed....

Research Insights from the Q3 2022 TDWI Best Practices Report

As organizations strive to compete in a dynamic environment, they are looking to modernize their data and analytics environment to help. This modernization includes implementing new technologies such as scalable cloud platforms and unified approaches. It includes utilizing more advanced analytics such as geospatial analytics and machine learning. It includes new paradigms such as the data fabric and the data mesh. Moreover, as part of this, modernization may include new organizational constructs such as the data office and new teams such as DataOps, MLOps, and data literacy enablement teams.