TDWI

As many companies use more data for analytics and insights, they want to enrich their data sets for analysis and make data more easily accessible and understandable. One solution to these needs is an internal data marketplace.An internal data marketplace is a platform where data and analytics within an organization are organized, managed, and made accessible to various business units and teams. It collects metadata and provides a centralized location where users can come and find data, promoting collaboration and knowledge sharing among teams.There are several benefits to using internal data...

Cloud migration is a top priority for most organizations. In fact, TDWI research indicates that platforms such as cloud data warehouses are already mainstream and the gap between on-premises warehouses and cloud data warehouses is narrowing. Cloud data lakes are in the early mainstream phase of adoption.So, how do successful organizations move to the cloud? How do organizations address challenges with hybrid multicloud environments where some systems are on-premises and others are located on multiple cloud platforms?This expert panel will discuss how to develop a cloud migration strategy as...

As many companies use more data for analytics and insights, they want to enrich their data sets for analysis and make data more easily accessible and understandable. One solution to these needs is an internal data marketplace.An internal data marketplace is a platform where data and analytics within an organization are organized, managed, and made accessible to various business units and teams. It collects metadata and provides a centralized location where users can come and find data, promoting collaboration and knowledge sharing among teams.There are several benefits to using internal data...

Data demands are exploding as organizations democratize access and expand into advanced analytics, artificial intelligence (AI), and machine learning (ML). Distributed data environments are putting stress on data integration, turning today’s labyrinth of pipelines and transformation processes into bottlenecks that affect downstream applications. Pressure is growing on legacy systems and practices, driving higher costs and reducing business value.Data-driven business initiatives depend on scalable, agile, and comprehensive data management and data governance. Fortunately, AI/ML-infused...

The data explosion continues to accelerate across distributed landscapes with data on premises and on multiple cloud data platforms. Organizations face challenges as well as tremendous potential for increasing the value of data assets, including through data monetization—potential that can go untapped without good data management and governance.Data-driven business initiatives depend on scalable, agile, and comprehensive data management and governance. The latest applications embed sophisticated analytics using AI/ML capabilities that must be provisioned with continuous, integrated, curated...

TDWI research finds that data democratization—empowering a broader spectrum of people with self-service data access, exploration, preparation, and analytics—is a top priority. Self-service business intelligence and analytics are central to transforming daily operational decisions as well as forecasting and higher-level strategies.Today, citizen data scientists are pushing beyond data consumption to perform more advanced data discovery and predictive analytics. Developers are upgrading business applications by embedding visualization and analytics capabilities. Artificial intelligence and...

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...