Name: How to Take Control of Data Quality
Start: 2023-11-02T10:16:00Z
End: 2023-11-02T10:16:25.000Z
Location: BrightTALK
Rating: 0

Soda delivers end-to-end data quality management for the digital era where everyone needs to work with data they can trust to confidently make business decisions. By knowing when data breaks, providing real-time visibility, and enabling teams to find the root cause and prevent future data issues, Soda bridges the gap for data engineers and data consumers to collaborate and get ahead of data issues with full coverage, from observability to proactive data testing and prevention. With Soda, teams can take control of data quality and scale it across the organization, empowering everyone to leverage high-quality, reliable data for business success.

Brought to you by Data Council and Soda. 

Get ready for an electrifying panel discussion on data contracts with host Pete Soderling and renowned data contracts experts Andrew Jones, Jean-Georges Perrin, Max Schultze, and Tom Baeyens.

While the concept and theory of data contracts have been extensively discussed, this panel aims to delve into the practical aspects of implementing them. Get ready to gain a comprehensive understanding of how data contracts actually function in real-world scenarios.

Watch this panel discussion to:

- Master the essential foundations for successful data contracts
- Discover the recommended roles, responsibilities, and tools
- Learn from the experts about common pitfalls and rookie mistakes
- Understand the benchmarks for measuring success

Delve in and expand your data contract expertise!

Data Contracts: The Next Frontier

Active metadata is a game-changer for businesses operating in today's data-driven landscape. Traditionally, every data tool operated in isolation, making it very difficult to create an integrated system of tools for data ingestion, transformation, retention, quality, access, and discovery. With active metadata, data tools start to broadcast key information (metadata), allowing every other data system to to listen to metadata change events, and take action where needed.

Join us for an insightful webinar with Koen Van Duyse, where he will delve into the practical application of metadata for data quality. Discover how Soda leverages active metadata in the context of data integration and data discovery, and how we plan to expand our universe of active metadata. 

You'll learn how to:
 - Organize datasets and data quality checks
 - Involve the right stakeholders in data quality discussions
 - Schedule Scans based on metadata change events
 - Send the right alerts and recommendations to Catalog and Data Governance layers to enable operational governance

How Data Quality Can Enable Active Metadata

Data migration is a complex process that involves transferring data from one system to another. Almost 85% of data migration projects overrun time and budget and more often than not, the root cause of these failures is a lack of investment in systems and processes that ensure reliable, high-quality data. When newly-migrated data appears to be inaccurate in a new storage system, end users are likely to distrust the data and go back to the old way of working and therefore, it is crucial for businesses to ensure a smooth and successful migration to avoid any potential risks and failures.

Data reconciliation is crucial in the process of data migration. It plays a vital role in various industries, including finance, healthcare, and manufacturing, where large volumes of data are generated and analyzed, to identify and rectify discrepancies or errors that may occur during data collection, storage, or transmission. 

Data reconciliation also helps in maintaining compliance with regulatory requirements and in improving operational efficiency by streamlining data processes and reducing manual efforts, allowing employees to focus on other critical tasks. 

This 45-minute session contains:

 - Data migration use cases and best practices
 - A product showcase to test, manage, and assure data quality 
 - Guidance on how to automate the reconciliation process to save time and resources

Data Quality Use Case: How to Mitigate the Risk & Failure of Data Migration

Group 1001 is a tech-driven financial services enterprise with a mission to provide intuitive solutions and products for all Americans. 

To drive revenue, improve performance, and better serve their customers, Gu Xie, Head of Data Engineering, and his team, built a data platform and rearchitected the data strategy. In less than 6 months, a game-changing data infrastructure was implemented with Snowflake, Dagster, Coalesce, Atlan, and Soda, which enables the entire organization to be more productive, deliver operational efficiencies, while understanding and trusting the data they use. 

In this conversation Gu and Koen, Head of Customer at Soda, discuss and share insights on how to:
- build a data stack that will increase productivity and operational efficiency
- spend more time discovering new insights and delivering more value
- improve data literacy and nurture a data culture

How Group 1001 Built a Data Platform to Transform Data Analytics

CarTrawler is the Human TravelTech company and leading B2B provider of solutions for the travel industry. As an organization reliant on billions of data points, CarTrawler needed to be able to empower users across the business to trust the data they are using. 

Access this video to hear CarTrawler's transformation journey as shared by Patrick Callinan, Director of Insights and Data Science; Stephen Carey, Head of Data Intelligence; and Sutaraj Dutta, Head of Data Engineering. You'll learn how they bolstered their technology stack (Airflow, dbt, Snowflake, AWS, Snowplow, Tableau and Thoughtspot) and vast amounts of data with a scalable data quality solution, to enable its data engineers to test data quality as-code and prevent data issues and empower its data consumers to self-serve and be accountable for their own data quality expectations.

With self-serve capabilities delivered across the entire business, the organization has realized:

 - Trusted data for critical business decisions
 - Process optimization and new revenue streams 
 - Scalability and integration with all tools

Implementing Data Quality for Trusted Data Intelligence at CarTrawler

Data quality and data governance are both essential to any organization that is using data. Data quality refers to the accuracy, completeness, reliability, and consistency of data, ensuring that it is fit for its intended use, whereas data governance encompasses the overall management, control, and strategic utilization of data assets within an organization.

This video is for any organization that wants to integrate data governance and data quality to achieve trusted data, to experience streamlined data governance and data quality with Atlan and Soda. 

Watch and learn the three key principles of data trust and how to:

- Build your one-stop shop for trusted data
- Activate metadata to meet the real-time needs of enterprise data users
- Improve collaboration and increase the use and sharing of data

How to Democratize, Govern & Trust Data with Atlan and Soda

Having data is good, but having quality data is even better! With the explosion of data within companies, finding the necessary information can be quite a challenge for your business users. Not only is locating the data difficult, but it's also crucial to ensure its quality, source, safety, and compliance with privacy regulations.


To address this, Zeenea and Soda, leaders in Data Discovery and Data Quality Management, have partnered up to empower both data and business users to seamlessly locate, explore, and trust their data assets.

Watch this video and learn how Zeenea and Soda provides an integrated approach to advanced data discovery and powerful data quality that enables users to find, understand, and trust their data. See how you can eliminate the challenge of delivering trusted, reliable data to the business.

How to Simplify Data Discovery and Trust for Your Business Users

Data is critical to everyone's work but the burden for maintaining data quality often gets passed around like a hot potato, which results with bad-quality data that is not fit-for-purpose. Organizations need to take control and enable data engineers to produce and deliver reliable data that can be trusted and confidently used by data consumers to make business decisions.

In this 30 minute product showcase, you'll discover how Soda's end-to-end data quality management platform provides data engineers and data consumers with workflows to detect, analyze, resolve, and prevent data issues. Watch and learn how organizations including Group 1001, HelloFresh, and Panasonic, use Soda to:

 - Seamlessly integrate and scale across their entire stack to test data at any point
 - Support data programs including migration, decentralization, and governance
 - Increase user trust and improve the usage of data

How to Take Control of Data Quality

Data Quality

Data Management

Data Engineering

Data Observability

Data Governance

Reliability

Welcome to the big data and data management community on BrightTALK. Join thousands of data quality engineers, data scientists, database administrators and other professionals to find more information about the hottest topics affecting your data. Subscribe now to learn about efficiently storing, optimizing a complex infrastructure, developing governing policies, ensuring data quality and analyzing data to make better informed decisions. Join the conversation by watching live and on-demand webinars and take the opportunity to interact with top experts and thought leaders in the field.

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How to Take Control of Data Quality

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