Watch the Webinar

Data catalogs automate the collection, discovery, and curation of information about data assets. They are critical for optimizing data quality, self-service analytics, data operations, data governance, data privacy, and data security. Despite these benefits, many companies have struggled to implement data catalogs and gain a critical mass of users. 

A new generation of data catalog products promise to accelerate adoption while delivering the intelligence that comes from managing metadata in a systematic fashion. Vendors have reinvented their products using AI and active metadata to automate many data-driven activities. And they have doubled down on ease-of-use and fast installs to deliver value quickly. Collectively, these tools increase the business value of data by reducing risk, automating processes, and increasing trust in data throughout the enterprise. 

This topical virtual event is designed to help data and governance leaders evaluate and select next-generation data catalogs and learn best practices for implementing them. The event compresses the time it takes data leaders to understand this new technology, create a short list of products, and hear tips from experts, practitioners, and solutions providers in the field.

Watch the Webinar

Data products have emerged as a key component in modern analytics strategies, offering tailored, actionable insights and flexibility to cope with ever-changing data complexity and business requirements. But how can organizations adopt a product mindset to drive successful data product development and deployment?

In this webinar, we will explore the best practices for building and scaling data products, from starting small and iterating to establishing robust automated product governance. We will also showcase a live demonstration of Starburst’s data lake analytics platform, on how to accelerate data product development and delivery across your enterprise.

Sponsor: Starburst

Watch the Webinar

Cloud platforms have revolutionized the world of analytics, but many companies still face challenges in transferring their most valuable and comprehensive data, which is stored in enterprise systems, to these cutting-edge cloud data environments.

Join Kevin Petrie, VP of Research, and Mike Pickett, VP of Product Growth for Streamsets, as they discuss how to conquer typical obstacles to free up your enterprise data and how integrating this data can improve analytics, refine financial and regulatory reporting, streamline operations, and enhance the customer experience.

Sponsor: StreamSets

Watch the Webinar

As enterprises democratize data consumption and invest in advanced analytics, they need ever-higher volumes of complex, fast-moving data. To meet this demand, data teams need to accelerate the development of data pipelines, automate their execution, and continuously validate the quality of the output. And along the way, they need to master the lifecycle of data, from ingestion and transformation to testing, orchestration, and monitoring. 

This 3-hour virtual event is designed to help data leaders evaluate and select data pipeline products, and learn best practices for implementing them. The event compresses the time it takes data leaders to understand an emerging technology, create a short list of products, and hear tips from experts, practitioners, and solutions providers in the field.

Attendees Will Learn:

• Innovative approaches to building and managing data pipelines 

• Criteria to evaluate and select the right data pipeline tools

• Ways in which modern data pipelines ingest, transform and deliver data

• How these pipelines integrate with enterprise environments

• How to design, manage, and adapt data pipelines to meet dynamic business requirements

Watch the Webinar

The data mesh methodology calls for distributing development to data domains. Data and analytics generalists in these units rely on a shared self-service data platform and data governance standards to publish data products for local and enterprise consumption. To ensure enterprise alignment, enterprise data teams need to provide a self-service data platform that abstracts the complexity of the underlying infrastructure, making it possible for citizen developers to build data pipelines and data-driven applications without deep technical knowledge or writing code.

Data architecture as a service (DAaaS) is a new concept based on traditional best practices. DAaaS embeds enterprise standards and know-how into point-and-click development tools geared. This gives domain developers the best of all worlds: the freedom and agility to build their own data-driven solutions while adhering to enterprise standards and best practices. The result is the data domains build solutions quickly and efficiently without creating data silos that undermine enterprise data consistency. The webinar will examine the convergence of data mesh and DAaaS and demonstrate DAaaS-enabled tools in action.

You Will Learn:

• How DAaaS helps fulfill the promise of data mesh

• Best practices to create a self-service data mesh platform that abstracts complexity

• How DAaaS embeds standard rules and best practices into self-service tools

• Why data mesh requires data architecture as a service (DAaaS)

Sponsor: Coalesce