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Modern business depends on real-time data integration. Sales, finance, HR, and other operations need to synchronize records across applications, departments, enterprises, regions, and clouds. Real-time data integration also supports data analytics that triggers operational actions such as customer recommendations, proactive maintenance, and fraud detection.

Change data capture (CDC) technology is the gateway to enabling real-time events on complex operational systems. This webinar will explore the requirements, use cases, and guiding principles for driving real-time operations with CDC.

Join us to learn:

- What role CDC plays in hybrid, heterogeneous environments

- Why you need CDC for real-time operations

- How to architect effective CDC pipelines

Sponsor: Equalum

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You’ve implemented a new cloud data platform using Snowflake. You’re eager to gain the benefits of cloud computing and work in a more agile, scalable way.

But you fear you’ll fall into old habits and simply use Snowflake as a storage depot for various data sets, rather than an agent to transform the way you build data pipelines, process data, and support self-service analytics. DataOps is the key to unlocking the full power of Snowflake and other cloud data platforms. 

DataOps tools and principles can help your team fulfill the promise of delivering data solutions “faster, better, cheaper.” But how do you do that?

This webinar discusses :

• Challenges of modern data pipelines and benefits of DataOps

• The DataOps framework

• Collaboration, orchestration and testing features in DataOps.live

• How to process IoT data in DataOps.live with Snowflake's zero-copy clone feature 

• DataOps Snowflake lifecycle management with two approaches—imperative and declarative

Sponsor: DataOps.live

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Exploding data demand and supply pushes modern data pipelines to the breaking point. Data observability seeks to simplify modern data pipelines by monitoring and correlating data workload events across the application, data, and infrastructure layers of the stack. Observability helps resolve the issues that break production analytics and AI workloads.

This webinar discusses:

• What data observability is.
• How key stakeholders can use it to meet requirements for production analytics and AI workloads.
• How data observability applies to three overlapping segments—on-premises data lakes, hybrid cloud and multi-cloud data warehouses.
• Role of data observability in data modernization and digital transformation.
• Data observability best-practices and use-cases of adoption.

Sponsor: Acceldata.io

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There is a growing divide between organizations that use data effectively and those that don’t. Data laggards don’t prioritize data; consequently, data is fragmented and siloed, and business users spend long hours cleaning and harmonizing it. There are no standard metrics or reports, and no one trusts or shares data. These companies find themselves spending more time arguing about data than acting upon it.

In contrast, the data elite live and breathe data; employees trust the data and take an active role in governing it. Executives use standard metrics and reports when making decisions. Analysts spend more time analyzing data than finding and cleaning it. These organizations use data to work proactively and apply algorithms to optimize or automate business processes.

Attend this webinar, and you will discover:

● What separate data laggards from the data elite

● A formula for crossing the data divide: P4+D=V

● A five-stage maturity model for evaluating progress

● How to assess your organization’s data maturity online

● The three C’s practiced by the data elite

Please register for the webinar today to learn about the journey to becoming data-driven, the technologies, tools, and techniques the data elite use to transform their organizations and disrupt industries. The webinar will highlight an Eckerson Group online assessment that helps organizations assess the degree to which they are data-driven.

Sponsor: Infor

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The data hub enables business managers and BI analysts to take a more hands-on role in data management and data governance. They use the data hub to integrate, refine, and explore data that spans customers, supply chains, employees, and other entities. This helps spread the glue of data governance, master data management (MDM), and data quality.

How can enterprises convert this vision into reality? This webinar will examine the problem of data silos, the proposed solution of a data hub, and its intended benefits. It will assess the inherent tradeoffs of converged platforms, key evaluation criteria and finally guiding principles for successful data hub initiatives.

Join this webinar to learn:

- The causes, challenges, and symptoms of data silos

- The drivers and potential benefits of data management and governance convergence

- Strategies to navigate the inherent tradeoffs of data hub solutions

Sponsor: Semarchy