In this episode, our hosts sit down with PeerNova’s Founder and CEO, Gangesh Ganesan, to deep dive into the classic Buy vs. Build debate, incorporating PeerNova’s powerful three-pronged approach: Buy Confidently, Benefit Immediately, and Broaden Strategically. 

Unpack the real-world challenges and costs of in-house software development vs. buying a ready-to-use platform such as Cuneiform for Valuation Risk.

Learn about our purpose-built platform that ensures you meet today’s demands while seamlessly scaling for the future. Experience cost-savings, resource efficiency, rapid deployment, immediate value, and seamless scalability with the assurance of a future-proof solution.

Gangesh answers the following questions: 

• What are some of the biggest challenges firms face when they try to build in-house vs buy externally?
• What does the current financial institution software landscape look like, especially amidst digital transformation efforts (AI, etc)? 
• What are the most common hesitations firms have when buying a solution? 
• How does Cuneiform for Valuation Risk address these hesitations?

In this episode, our hosts sit down with PeerNova’s Founder and CEO, Gangesh Ganesan, to explore how Cuneiform® for Valuation Risk addresses critical gaps in the current valuation risk landscape. 

Discover what makes the platform unique, why it's so difficult to replicate, and how it seamlessly balances zero-code accessibility for business users. Gangesh also shares insights on overcoming industry adoption challenges and the transformative potential for the future of valuation risk management.

Gangesh answers the following questions: 

• What are the biggest challenges in fair-value estimation and pricing today?
• What makes Cuneiform unique?
• Why is it so hard for others to create a product like this?
• How does Cuneiform balance zero-code usability for business users with IT oversight?
• How can we overcome adoption challenges, and what advice would you give to hesitant valuation teams?

In this week's episode, Sonia sits down with returning guest, Mehmet Orun (Sr. VP of Product at PeerNova), to discuss the meaning of fit-for-purpose  data and why it is so critical for an organization. He shares how Cuneiform for CRM helps CRM stakeholders achieve fit-for-purpose data.  

Mehmet answers the following questions: 

• What does fit-for-purpose data mean? What are some examples?
• How does fit-for-purpose apply today in business?
• Why is it critical for Salesforce customers?
• What are some things Salesforce customers can do to determine if their CRM data is fit-for-purpose?
• What is Cuneiform for CRM and how is it different from other applications?
• How can customers get started?

Install Cuneiform for CRM in the AppExchange

In this week's episode, Navid and Sonia sit down with Mehmet Orun, Sr. VP of Product at PeerNova, to announce the launch of Cuneiform for CRM, a business data quality application now available on the Salesforce AppExchange. 

Mehmet answers the following questions: 

• What is the largest data quality challenge that organizations face today?
• What are the current gaps in today's data quality for CRM applications?
• What is Cuneiform for CRM?
• What does it mean when data is fit-for-business purpose?
• How is it different from current data quality applications on the AppExchange?

Read the Announcement
Install Cuneiform for CRM in the AppExchange

In this week's episode, you will join PeerNova's Founder and CEO, Gangesh Ganesan, as he keynotes at the CDAO Financial Services event. He discusses the business value of continuous data quality and how to overcome challenges with an effective data quality model.

Gangesh answers the following questions: 

• What are both the short-term and long-term consequences of poor data quality?
• What does a proactive and effective data quality framework consist of?
• What are the key ingredients for a data quality model that will increase operational efficiency, meet regulatory compliance, and enable better business decisions?
• How does a financial firm implement an effective data quality tool that continuously addresses low-quality data across workflows?

Download the data quality whitepaper here: https://peernova.com/DQWP
Watch the video here: https://youtu.be/DmjJ38CCIQo

In this week's episode, you will join PeerNova's data quality webinar featuring industry experts as they discuss how to achieve continuous data quality in financial institutions.

Watch the video version here.
You can read the supplemental white paper here.

Panelists:
Ellen Gentile, Director of Enterprise Data Quality, Sumitomo Mitsui Banking Corporation
Dan Power, Managing Director of Data Governance, Global Markets, State Street
Erika Lunceford, Global Head of Solutions Engineering, PeerNova

Moderator:
Navid Jafari, Global Head of Marketing and Communications, PeerNova

The panelists will answer the following questions: 

• Why is a data quality strategy important for a financial services firm?
• What are the key ingredients for a data quality model that will increase operational efficiency, meet regulatory compliance, and enable better business decisions?
• How does a financial firm implement an effective data quality tool that continuously addresses low-quality data across workflows?
• How does a financial firm reinforce and measure quality to drive the change that is needed? 

This week, our host sits down with Ellen Gentile, the Director of Enterprise Data Quality at SMBC, to discuss the critical need for firms to create and implement an effective data quality framework.

Ellen answers the following questions:

• How have firms previously approached data quality and what have the challenges or limitations been?
• What is some advice for firms who are looking to create or improve their current data quality framework? 
• What are some of the benefits financial firms can expect to receive? 
  
  

To learn more about data quality and hear more from Ellen, register for PeerNova's upcoming webinar, 'Achieving Continuous Data Quality in Financial Institutions'.

This week, our hosts kick off 2021 by highlighting PeerNova's upcoming data quality webinar and recent white paper. Hosts Sonia and Navid also touch on what it means to have continuous data quality and process correctness.

Register for the webinar: https://www.eventbrite.com/e/achieving-continuous-data-quality-in-financial-institutions-registration-132476616125

Download the whitepaper: https://peernova.com/lp/white-paper-achieving-continuous-data-quality-in-financial-institutions/

This week, our host discusses ETL and data preparation tools with Gangesh Ganesan, PeerNova's Founder and CEO. This will be part of an ongoing series deep diving into the features and benefits of the PeerNova® Cuneiform® Platform, and how it compares to other tools on the market.

Gangesh answers the following questions: 

• Why are ETL and data prep tools crucial for enterprises handling mass amounts of data?
• How has the evolution of these tools helped enterprises make better business decisions?
• Do ETL and data prep tools help enterprises beyond complying with data formats and standards? Do they help with data quality and data integrity?  
• How does the PeerNova Cuneiform Platform compare to an ETL or data prep tool? Is it a competitor?  Do enterprises need all three?

This week, you will join PeerNova and Women in Big Data (WIBD), as they host a virtual panel discussing current data quality challenges with key industry leaders.

Panelists:
Erika Lunceford, Global Head of Solutions Engineering, PeerNova
Dan Power, Managing Director of Data Governance, Global Markets, State Street
Ellen Gentile, Director of Enterprise Data Quality, Sumitomo Mitsui Banking Corporation
Lara Gureje, Practical Data Governance & Stewardship Activator, DatOculi

The panelists will answer the following questions: 

• What are some challenges enterprises face when processing or using large volumes of data?
• What can happen when an enterprise has low-quality data? 
• What is an enterprise's first step in building out a data quality strategy?
• How are decision-science programs affected when data is not well understood?