Name: Don't just migrate, modern your legacy ETL
Start: 2022-05-20T17:00:00Z
End: 2022-05-20T17:00:43.000Z
Location: BrightTALK

Built ground-up for a cloud-first world, Gathr is the only platform to handle all your data integration and engineering needs - ETL, ELT, Reverse ETL, Ingestion, CDC, streaming analytics, data preparation, machine learning, advanced analytics and more. With Gathr, anyone can build, deploy and manage end-to-end 'data-to-action' pipelines in minutes, irrespective of skill levels.

Ever wondered how Amazon knows exactly what you want before you buy it? Or how Netflix throws up the perfect recommendation for a series to watch on the weekend?

The secret sauce is building a dynamic, real-time, and accurate view of the customer by harnessing the historical data and the data in motion.

Market leading brands are capturing structured and unstructured customer data in real-time, correlating different datasets, and applying sophisticated models and algorithms to build a dynamic, real-time, and accurate view of the customer.

This, in turn helps deliver hyper-personalized recommendations and win customers’ moments of truth before they consider a competing alternative.

But not many organizations have been successful in doing that – the greatest challenge comes down to successfully integrating and engineering data at speed and scale.

Modern data pipelining solutions can help accelerate and simplify the journey by doing the heavy-lifting. They can help collect, transform, and analyze petabytes of data in real-time, allowing you to focus on insights and actions, rather than data engineering processes.

Key highlights:

> Winning customer’s moment of truth – why it matters more than ever before   
> Building a dynamic, real-time customer 360 – and decoding the components for that
> Using modern data pipelines to eliminate silos and build a robust foundation for next-gen analytics
> A deep dive with real-world examples and demo

Winning customer's moment of truth by harnessing real time insights

Traditional databases and batch ETL operations have not been able to serve the growing data volumes and the need for fast and continuous data processing.

How can modern enterprises provide their business users real-time access to the most up-to-date and complete data?

In our upcoming webinar, our experts will talk about how real-time CDC improves data availability and fast data processing through incremental updates in the big data lake, without modifying or slowing down source systems. 

Join this session to learn:

What is CDC and how it impacts business
The various methods for CDC in the enterprise data warehouse
The key factors to consider while building a next-gen CDC architecture:
Batch vs. real-time approaches
Moving from just capturing and storing, to capturing enriching, transforming, and storing
Avoiding stopgap silos to state-through processing
Implementation of CDC through a live demo and use-case

Planning your Next-Gen Change Data Capture (CDC) Architecture

As C-suite and line-of-business leaders look for new ways to drive growth in the post-Covid business recovery era, they need to find faster and better ways to turn data into value. There are rich opportunities for companies to integrate customer data from different data sets (transactional, marketing, customer service) to help gain a deeper understanding of customers and their preferences and to help create ‘hyper-personalized’ next best offers for them. In addition, as organizations accelerate their adoption of SaaS and cloud platforms, technology leaders are increasingly utilizing cloud-managed data integration tools and approaches to expedite results and lower their costs.

Discover the key business and operational drivers behind ETL modernization initiatives,  and understand how modern data integration platforms help technology leaders solve major business challenges.

Join experts from HMG Strategy, Bloor Research, and Gathr to learn about:

> How the data integration market is changing – and why
> Top business and operational drivers behind data integration initiatives
> Recommendations for designing a modern data stack to harness the power of cloud and ML
> Key considerations for implementing data integration use cases

Accelerating time to value with a modern data integration approach

Join us for an exclusive fireside chat with Truist and Forrester, and see how forward-looking banks are modernizing their data stack and implementing cutting-edge customer 360 solutions.

Discover how Truist replaced a legacy analytics application with modern data pipelining to deliver the right message to the right customer at the right time.

Key Takeaways:

> Collect and harmonize data across various customer touchpoints
> Use data to identify upsell and cross-sell triggers with high precision
> Build next-gen “pro-active” analytics solution for better CX
> Modernize data stack to power faster and better decision making

Analytics modernization for better customer engagement and loyalty

Modern data engineering processes—also known as DataOps pipelines—continuously integrate, transform, and prepare data for production deployment. Many organizations undertake DataOps modernization in conjunction with larger enterprise data platform modernization projects.

Watch this webinar to learn how you can implement modernized DataOps pipelines seamlessly and ensure that your data is always accurate, relevant, and consumable. Discover how a next-gen, self-service data pipeline platform can help you embrace the DataOps paradigm and drive scalability, agility and growth.

Key highlights:

• Justifying DataOps modernization
• Identifying priority use cases for DataOps modernization
• Aligning DataOps modernization with cloud data platform strategy
• Investing in enabling DataOps infrastructure, tools, and skills
• Bringing simplicity to DataOps and restructuring management
• Realizing the promise of DataOps with an all-in-one data pipeline platform

Evolving the DataOps Pipeline to Address Fresh Challenges

Legacy analytics applications are simply not cut out to meet the challenges of modern customer analytics. They are slow, rigid, and cumbersome to operate. 

Take a deep dive into the future of customer analytics with experts from Truist Financial Corporation, Forrester, and Gathr. Discover how forward-looking businesses are modernizing their data stack and implementing cutting-edge customer analytics solutions.

Get a glimpse of how Truist replaced a legacy analytics application with a modern data pipeline platform to determine next-best actions and drive marketing success. 
 
Key takeaways:
• Enabling faster, distributed data processing to power real-time analytics
• Seamlessly rolling out new patterns/triggers and re-processing historical events with new rules
• Using a data-driven approach to identify upsell and cross-sell opportunities with high precision 
• Send the right offer to the right customer at the right time, and improve customer acquisition and retention

With unprecedented challenges to navigate in the pandemic, airlines are looking to efficiently derive actionable, real-time insights from massive volumes of complex digital interaction and operational data. Take a deep dive into the future of the aviation industry and discover how United Airlines leveraged a data-first approach to fuel significant growth.

Key takeaways:

- How to grapple with the new challenges and realities of the aviation industry
- Reducing decision-making time with real-time data ingestion and transformation
- Implementing data-driven strategies to improve the customer experience across channels
- What airlines should look for in a next-gen data pipeline platform
- How Gathr powers real-time data analytics to derive “in the moment” actionable insights, and propel digital transformation

Flying higher and farther with data: United Airlines’ journey

To stay ahead of the curve in today’s competitive world, businesses need to streamline and fast-track their analytics processes. 

DataOps helps build and deliver trusted, consumption-ready data pipelines to analytics teams across the enterprise. Learn how DataOps uses Agile and DevOps best practices to automate and optimize data analytics capabilities.

Key highlights:

- How data can make or break your digital transformation initiatives
- The building blocks of a robust DataOps strategy
- Best practices for adopting DataOps across the enterprise
- Leveraging an all-in-one data pipeline platform to foster collaboration and reduce time to insight

Accelerating digital transformation with DataOps

With massive amounts of data pouring in, there is a pressing need for businesses to swiftly derive mission-critical business insights. For this, you need a robust data architecture that supports multiple sources, enables processing at scale, and powers diverse analytics use cases. 

Learn why intelligent data pipelines are the pillars of a modern architecture and how they help improve business outcomes.

Key highlights:

- Navigating an ever-increasing volume, velocity, and variety of enterprise data
- Building intelligent data pipelines in hybrid and multi-cloud environments
- Bridging the gap between data pipeline strategy and execution
- How next-gen data pipeline platforms help drive innovation, solve customer challenges, and deliver contextual, meaningful engagement

Drive innovation and growth with intelligent data pipelines

To enable intelligent decision-making, modern enterprises need a holistic view of their enterprise data. This demands fast and easy access to data from multiple sources, including databases, applications, CRM, and ERP systems etc. 

Learn how next-gen data pipelining helps extract large volumes of structured and unstructured data, apply complex transformations, and seamlessly load the transformed data into a data store.

Key highlights:

- Balancing business needs with technology expectations
- Overcoming roadblocks across the data analytics lifecycle
- How to build robust pipelines and turn your data into action
- Must-haves of a modern data pipeline platform

Accelerate business initiatives by modernizing your data pipelines

Legacy ETL platforms are not equipped to solve the complex business problems of real-time enterprises. High cost of ownership, slow workflows, and lack of scalability make them unsustainable in the cloud-first world.

For forward-looking organizations, ETL migration and modernization must start with a simple question – “where do I want to be”? Reimagining your new data stack is a critical part of the modernization journey.

Join our fireside chat featuring Forrester to discover how modern data platforms can help you unlock new insights, reduce time-to-market, and fuel data-driven growth.

Key highlights:

The immediate need to modernize legacy ETL
The pivotal role of DI in a modern, cloud-based analytics stack
Driving innovation and growth with next-gen DI tools
Understanding the must-haves of a modern DI platform

Don't just migrate, modern your legacy ETL

Data Integration

Data Pipeline

DataOps

Data Ingestion

Data Fabric

Cloud Data Integration

Data Analytics

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Don't just migrate, modern your legacy ETL

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