Name: Take a data product approach to (finally) achieve Customer 360
Start: 2022-09-29T14:00:00Z
End: 2022-09-29T14:00:58.000Z
Location: BrightTALK
Rating: 4.7

At K2View, we believe that every company should be able to liberate and elevate its data to deliver the most personalized and profitable customer experience in its industry, while being innovative and radically agile. 

With K2View, companies manage data in a whole new way, using a business lens: they create data products that continually sync, transform, and serve data from siloed source systems – delivering a real-time, holistic view of any business entity to any data consumer.

Our Data Product Platform fuels operational and analytical workloads, at enterprise scale. It deploys as a data fabric, data mesh, or data hub - in an on-premises, cloud, or a hybrid architecture - in a matter of weeks, and adapts to change on the fly.

The most data-intensive companies in the world, including AT&T, Verizon, American Express, Vodafone, and Hertz trust K2View Data Product Platform for their operational use cases - spanning Customer 360, cloud migration, test data management, data tokenization, and legacy application modernization.

Join us for a deep dive into the world of tabular synthetic data generation for software testing: uncovering its powerful techniques, versatile use cases, and the myriad of benefits it brings to businesses. Synthetic data generation has emerged as a game-changing solution for organizations seeking to maximize the potential of their data without compromising privacy or security. 

We'll cover: 
* Gartner’s research on synthetic data generation 
* Top drivers and use cases 
* Synthetic data generation technical approaches: Pros and cons of each 
* Masked production data vs. synthetic data - which is better?
* Best practices and tools

Don't miss this opportunity to explore the potential of  synthetic data for your organization.
Visit our LinkedIn page and follow us at https://il.linkedin.com/company/k2view

Unlocking the Power of Synthetic Data Generation: Methods, Use Cases & Insights

Are you ready to discover the biggest hurdles preventing organizations from harnessing the power of Generative AI (GenAI)? 

Our latest market survey reveals that the most significant roadblocks to realizing GenAI’s full potential lie in organizations’ existing data infrastructure, particularly in the areas of data accessibility and latency, data privacy, and security.

Join 2 industry leaders as they discuss:  

* The state of GenAI adoption 
* Why enterprise data is at the crux of the biggest challenges for AI deployment 
* How to address the GenAI data readiness gap

The State of GenAI Data Readiness

In the age of Generative AI and retrieval augmented generation (RAG) the spotlight is on enterprise data. The data can reside in operational systems, data lakes / data warehouses, or on a data management platform, and it is an essential piece required for GenAI app to provide much more personalized and accurate information. 

Large Language Models (LLMs) can access structured enterprise data via RAG and SQL statements. For all the undeniable advantages of using an LLM to generate SQL queries, there are also a number of issues that accompany this approach.  

 Join 2 industry leaders as they discuss:  

* What is retrieval augmented generation (RAG) and how does it work? 
* The pros and cons of generating SQL with AI  
* Considerations for ensuring your enterprise data is GenAI-Ready  
* Closing the GenAI data gap

RAGs to Riches? The Realities of RAG and text-to-SQL

Will GenAI take your QA job? (Spoiler Alert: It won't, but it will change it!)

In just 30 minutes, join industry experts Noa Segol (PractiTest) and Amitai Richman (K2view) as they take you on a journey into the future of AI-powered testing. You'll discover:

* The current state of AI in testing: Uncover real-world applications of AI that are transforming test management and test data management today.
* Emerging trends and technologies: Explore the latest advancements in AI for test automation, optimization, analytics, PII discovery, synthetic data generation, and more.
* A glimpse into the future: Discover what's on the horizon for AI in testing and how you can prepare your team for the changes ahead.
* Practical strategies for leveraging AI: Gain actionable advice on how to implement AI-powered solutions to improve your testing processes.

Don't miss this opportunity to separate hype from reality and equip yourself with the knowledge you need to navigate the future of AI in software testing.

Register now! Even if you can't attend live, register and we'll send you the recording so you can watch it at your convenience.

The Future of AI in Software Testing: What's Hype, What's Real, and What's Next?

Chain-of-thought prompting is an innovative technique that trains GenAI models to use step-by-step reasoning to handle complex tasks with greater accuracy and agility. 

Join us to explore chain-of-thought prompting 101 and examine its potential for enhancing enterprise LLM applications across a range of use cases.  

Join 2 industry leaders as they discuss:  
* What is chain-of-thought prompting and how does it work? 
* The benefits of chain-of-thought prompting 
* Case study: How K2view uses chain-of-thought prompting to optimize customer support

Enhance Your Enterprise LLMs with Chain-of-Thought Prompting

Ready to revolutionize test data management in your enterprise?
 
Join us for an exclusive webinar on TDM best practices and live demo, "AI-Driven Test Data Management: Live Demo".

Our experts, Simon McVeigh, Global VP, Technology, and Amitai Richman, Director of Product Marketing, will show you how K2tdm’s intuitive platform empowers your QA team to seamlessly find, reserve, and provision test data, accelerating your testing cycles without any roadblocks. No masked production data available? No problem! We’ll show you how testers can generate synthetic data for any test scenario.

See for yourself how to:
• Effortlessly subset test data: Navigate through our intuitive web portal designed for testers and developers.
• Generate realistic synthetic data using AI/ML or business rules: Create safe, compliant datasets for application testing, with complexity mirroring your own production databases.
• Master sensitive data masking: Implement robust masking techniques to automatically discover and mask PII with realistic lookalike data to protect your sensitive info and ensure compliance.

AI-Driven Test Data Management: Live Demo

Join us for an insightful fireside chat with Jean-Luc Chantain, former Global CTO of AI at Accenture.

We'll discuss techniques and best practices for leveraging the power of enterprise data for Generative AI use cases.

Jean Luc will unveil solutions to conquer critical enterprise data challenges in unleashing the power of GenAI, including:
* Data governance and security 
* Metadata and data prep
* Prompt engineering and retrieval augmented generation (RAG)

Don't miss this opportunity to learn from one of the world's top AI experts, and ask your specific questions about data readiness for GenAI.

Ask The Expert: Is Your Data GenAI-Ready?

Ready to separate fact from fiction in Test Data Management? 

Join Daniel Howard, Sr. Analyst @ Bloor Research, and Amitai Richman, Dir. Product Marketing @ K2view, as they dispel persistent TDM myths in an eye-opening webinar, "Test Data Management: Separating Fact from Fiction."
We'll cut through the noise and equip you with actionable knowledge to overcome test data challenges like lengthy and error-prone test data provisioning, low test coverage, and compliance risks.
• Uncover the hidden bottlenecks that sabotage your release cycles
• Unlock the ROI of modern TDM with our calculation guide
• Uncover the truth about 'self-service' TDM – and how to truly slash test data setup time by 70%
• Discover if synthetic data can replace traditional TDM
Plus, get a sneak peek at the future of TDM and the trends shaping the industry.

Don’t miss this opportunity - register now to secure your spot.
Even if you can’t attend live, we’ll send you the recording afterward.

Test Data Management: Separating Fact from Fiction

Test data management (TDM) is a crucial aspect of software development and testing, but it also poses many challenges and complexities. If you want to learn how to overcome these challenges and optimize your TDM processes, you should join our upcoming webinar to learn about:  

* The current state of TDM, including the latest trends and challenges  
* Advanced features and capabilities to look for in a TDM solution 
* Best practices and strategies, including TDM processes and org structure 

Take advantage of this opportunity to learn from the TDM experts and get your questions answered. Register now to secure your spot for this informative and interactive webinar. We'll send you the recording if you can’t attend live.

Master Class: Test Data Management for Complex Data Environments

About this session:

We're excited to invite you to attend the 2nd in our synthetic data webinar series.

We'll delve into synthetic data generation methods, focusing on the 4 leading data generation techniques, including generative AI and rule-based data generation. 

Don't miss this opportunity to expand your knowledge of synthetic data generation, learn when to use each method and learn about the life cycle of synthetic data.


Agenda:
* The synthetic data lifecycle, and synthetic data management
* Synthetic data generation techniques, and pros and cons of each
* Product demo covering generative AI, rule-based, and data masking techniques
* Q&A

Mastering Synthetic Data Generation: Methods, Pitfalls and Best Practices

Join us for a deep dive into the world of synthetic data generation: uncovering its powerful techniques, versatile use cases, and the myriad of benefits it brings to businesses. Synthetic data generation has emerged as a game-changing solution for organizations seeking to maximize the potential of their data without compromising privacy or security. 

During the webinar, we'll cover: 

* Gartner’s research on synthetic data generation applications 
* Techniques and approaches: Pros and cons of each 
* Use cases per industry 
* Best practices and what to watch out for 

Don't miss this opportunity to explore the potential of tabular synthetic data for your organization.

Visit our LinkedIn page and follow us at https://il.linkedin.com/company/k2view

About this talk:

Protecting sensitive data is a top priority for the enterprise, and tokenization has proven to be one of the best data protection methods.

Join this webinar to learn about a revolutionary, data product approach to data tokenization.

We’ll cover data tokenization concepts and methods, the business requirements of a data tokenization solution, and the limitations of traditional data tokenization tools.

We’ll introduce a transformational approach to data tokenization that leverages data products to enable high-scale, real-time protection of sensitive data for operational and analytical systems.

Agenda:
* Data tokenization, its role in data security, and benefits
* The limitations and pitfalls of data tokenization
* Data products and how they revolutionize data security
* Live demo: Using a data product platform for data tokenization

Reduce risk of data breaches with a data product approach to data tokenization

About this session:

Join us to learn about the transformative power of Test Data Management (TDM) in driving cost savings, enhancing productivity, and accelerating software delivery for your organization. 

We’ll share a proven methodology for quantifying the business benefits of TDM, and an ROI model to use in building your financial justification for a TDM tool.

We’ll delve into the concrete benefits of DevOps TDM and provide practical approaches to achieve these outcomes. Real-world case studies and best practices will be shared to illustrate the tangible impact of TDM on eliminating test data bottlenecks and accelerating the testing and release cycles. 

Agenda:

* Top 8 challenges for software teams to overcome in provisioning compliant test data 

* Quantifying the benefits of a DevOps TDM solution

* Calculating ROI and payback period for Test Data Management tools

* TDM case studies and success stories

* Q&A

Quantifying the Benefits & Calculating the ROI of  DevOps Test Data Management

Despite the adoption of Lean-Agile thinking, modern engineering, and DevOps practices - test data management has lagged, leading to bottlenecks in productivity and reduced test coverage.

Are you struggling to manage your test data efficiently and effectively? Are you looking for new ways to improve your software testing processes while ensuring data privacy compliance?
 
If so, you won't want to miss our upcoming live webinar:
Test Data Management: Leading Approaches, Best Practices, and Strategies.
 
What you’ll learn:
• Gartner on Test Data Management: trends, hype cycle, best practices, strategies, and more
• Synthetic data generation: why, when, and how
• Recent developments in data privacy regulation and compliance
• A comparison of the three approaches to test data management

Test Data Management: Leading Approaches, Best Practices, and Strategies

About this talk:

Customer data is typically siloed in dozens of applications and data islands, in many different formats and technologies.

Many enterprises have invested heavily in various internal and commercial solutions with the aim of delivering a real-time, single view of the customer in order to improve customer experience and support innovative business initiatives. Most of them have failed.

Join this webinar to learn how Vodafone Germany has successfully implemented a Customer Data Hub (CDH), which unifies customer interactions, transactions, and master data, across dozens of data sources, to serve both operational and analytical workloads.

Agenda:

* The Customer 360 challenge

* K2View data product platform

* Key steps and lessons learnt in building a real-time Customer Data Hub

Vodafone Germany Customer Data Hub case study

About this talk:
* Join this webinar to learn about an emerging approach to data management, founded on data products.
* We will explain the “data as a product” concept, and how taking a product lifecycle approach to data can systematically deliver high-quality data to data consumers across the enterprise.
* We will showcase common data product use cases and their architectures, and how the K2View Data Product Platform delivers and manages data products, at massive scale.
* Agenda:
• What is a Data Product?
• ‘Data as a Product’ and the data delivery lifecycle
• Deployment architectures: data fabric and data mesh
• A new role: Data Product Manager
• Data Product Platform demo

Take a "Data as a Product" approach to democratize data access in the enterprise

About this talk:

Customer data is typically siloed in dozens of applications and data islands, structured and unstructured in many different formats and technologies. This explains why large enterprises face a monumental challenge in accessing unified and trusted customer data in real time.

Join this webinar to learn how Cellcom, a leading telco, took a data product approach to implement a real-time Customer Data Hub (CDH), with bi-directional integration to Salesforce CRM, in just 3 months. 

See how the Cellcom CDH delivers a real-time, complete view of the customer, including product, service, and financial information - to enable personalized and profitable customer interactions across customer touch points

Agenda:

* The Data Product approach to Customer 360  
* Cellcom business drivers and Customer 360 challenges
* Key steps and lessons learnt in building a real-time Customer Data Hub 
* Review of 10 business use cases that leverage the Customer Data Hub

Case Study: Delivering Real-Time Customer 360 in 3-Months with Data Products

About this talk:

Despite the massive investments companies have made in their Customer 360 programs, delivering a real-time, trusted, and complete view of the customer remains an illusive goal.

Conventional approaches (like CRM, MDM, CDP, and Data Virtualization) have failed to deliver on the promise. In fact, a recent Gartner survey shows that only 14% of companies have realized the full promise of Customer 360, but more than 70% are still working to get there.

We’ll introduce a transformational approach to complete your current Customer 360 initiative in weeks, using a data product approach, and while leveraging your existing investments.

Agenda:

* Challenges associated with achieving customer 360

* Why conventional approaches fall short?

* The Data Product approach to Customer 360

* Live product demo

Take a data product approach  to (finally) achieve Customer 360

Customer 360

Data Product

Customer Data Management

Customer Data Hub

Customer Data Platform

360 Degree Customer

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Take a data product approach to (finally) achieve Customer 360

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