Data Strategy Thought Leadership

Salesforce Data Cloud Zero Copy: When (and When Not) to Use It

Published March 21, 2025
EIGHT minutes Data Architecture Strategy

In this strategic analysis, PeerNova's GM and Data Strategist, Mehmet Orun, delivers a practical decision-making framework for determining when to leverage Data Cloud's Zero Copy capability versus traditional data ingestion. Drawing from deep architectural expertise, he moves beyond the marketing hype to help organizations carefully evaluate the business, technical and cost implications of connecting directly to external data warehouses like Snowflake and Databricks.

The article introduces a structured evaluation approach focused on three critical questions about data lake management: Is the data actively maintained? Is it recent enough for business needs? Is it complete?

Through detailed explanations of how data profiling solutions can assess these factors, the GM helps architects determine whether their Zero Copy implementation can provide reliable data or if direct ingestion would better serve business requirements.

Your Ultimate Guide to Data Management Tools on the AppExchange

Published February 14th, 2025

TWELVE MINUTES Product Evaluation Guide

This authoritative guide to the Salesforce data management ecosystem addresses a critical industry gap—no single vendor offers a complete end-to-end solution. Drawing from extensive implementation experience, he provides a methodical breakdown of complementary AppExchange categories (data profiling, cleanup, enrichment, security, and monitoring) while highlighting how these tools can work together to transform even the messiest Salesforce orgs.

The article positions data profiling as the essential foundation for effective data management, demonstrating how solutions like Cuneiform enable organizations to understand field usage patterns and identify data quality issues before undertaking cleanup initiatives.

What distinguishes this guide is its holistic evaluation framework and nine-step data transformation roadmap that integrates tools from different categories, providing Salesforce professionals with a practical approach to establishing reliable data as the foundation for strategic initiatives like Data Cloud and AI.

From Data Chaos to AI-Readiness: A Salesforce Data Governance Playbook

Published January 24, 2025

TEN MINUTES AI ImplementationS

Following Salesforce's Agentforce announcement at Dreamforce '24, PeerNova's GM and Data Strategist, Mehmet Orun, delivers a practical governance framework for organizations concerned about AI readiness. Drawing from extensive data management experience, he transforms overwhelming governance initiatives into targeted approaches focused on data fields that truly impact business outcomes.

The article methodically breaks down five AI hallucination causes, each paired with specific data profiling techniques for mitigation. Through real-world examples like opportunity stage distribution analysis revealing inverted sales funnels, Mehmet demonstrates how data profiling uncovers reliability gaps that would undermine AI effectiveness.

By connecting data profiling directly to AI success across machine-assisted capabilities, he provides a feasible entry point for organizations at any governance stage while establishing data profiling as the essential foundation for AI-ready data.

Best Practices for Using Historical CRM Data in Data Cloud and AI

Published January 10th, 2025

NINE MINUTES Strategic Data Management

This strategic analysis addresses a critical question often overlooked in Data Cloud implementations: "How much historical data should we use, and what's the best way to set up our data integration architecture?" The article challenges traditional approaches by highlighting the double-edged sword of automatic record deletion in Data Cloud—revealing how valuable historical data essential for AI can be inadvertently lost.

With organizations reporting up to 50% cost savings through effective archiving strategies, the article demonstrates how properly profiled historical data serves as a "gold mine" for predictive and generative AI.

By providing practical guidance on integrating archived data through zero-copy integration or specialized connectors, the piece offers Salesforce architects an actionable framework that optimizes both immediate system performance and long-term AI potential.

A Guide to Salesforce Duplicate Management in the Age of Data Cloud

Published September 04, 2024

ELEVEN MINUTES DATA QUALITY STRATEGY

In this comprehensive guide, PeerNova's GM and Data Strategist, Mehmet Orun, delivers an authoritative roadmap for modern Salesforce duplicate management that transcends traditional approaches. Through detailed scenarios comparing different match rule outcomes, he demonstrates how proper data profiling reveals which fields are most reliable for matching and identifies problematic data patterns (like disproportionately frequent email values) that can undermine matching accuracy.

The article presents a compelling case for Data Cloud's unified profile approach as superior to traditional record merging, showing how the keyring method preserves crucial business context while providing complete customer views.

By connecting data profiling directly to matchability formulas and governance decisions, the guide offers a practical framework for implementing duplicate management that balances technical requirements with long-term business objectives.

Expose Blind Spots in Identity Resolution With Data Profiling

Published June 10th, 2024

SEVEN MINUTES Data Quality Techniques

This expert analysis reveals how data profiling serves as a "superpower" for Salesforce admins tackling duplicate management. The article provides four strategic approaches that transform standard deduplication into a sophisticated data quality initiative.

The article showcases practical applications through real-world examples, revealing unexpected insights like high fill rates for fax numbers in healthcare organizations—a field most admins would overlook despite its value as a unique identifier.

By examining field usage statistics, value frequency patterns, and data quality indicators, readers learn how to build more effective matching rules while making informed decisions about whether to merge or link records based on business context rather than technical constraints.

Salesforce Data Cloud Contact Point Mapping Best Practices

Published June 3rd, 2024

EIGHT MINUTES Technical ImplementationS

This technical guide tackles batch profile unification in Data Cloud—the most expensive task at 100K credits per million records. PeerNova's GM and Data Strategist, Mehmet Orun, reveals why Data Kits often oversimplify contact point mapping, particularly for organizations with multiple phone numbers and custom email fields.

The article provides a six-step data profiling methodology that uses field population rates and value frequency analysis to identify reliable data and detect fake entries like "noemail@noemail.com."

This expert approach helps organizations build complete customer profiles while maintaining crucial context about consent and other attributes essential for compliance and effective data activation.

Architect's Guide: Data Profiling to Assess and Monitor Data Reliability

Published May 13th, 2024

TWELVE MINUTES Solution Architecture

PeerNova's GM leverages his Salesforce data strategy expertise to address the confidence gap in data reliability between IT (57%) and business users (42%).

The article positions data profiling as fundamental for sustainable data reliability, demonstrating how native solutions can efficiently assess large data volumes while maintaining security.

It provides architects with a comprehensive evaluation framework covering 16 key capabilities and a clear roadmap for implementing solutions that support critical initiatives like Data Cloud and AI.

Intentional vs. Unintentional Duplicates in Salesforce

Published on April 12, 2024

EIGHT MINUTES Data Governance

This expert analysis challenges conventional thinking about duplicates, introducing a nuanced framework that distinguishes between intentional duplicates (serving different business purposes) and unintentional duplicates (creating confusion).

Using practical examples like "IBM" vs "International Business Machines," the article demonstrates how data profiling reveals whether duplicates represent quality issues or legitimate business needs.

It advocates for unified profiles through Data Cloud as superior to indiscriminate merging, helping organizations create consistent, complete customer views while maintaining necessary data separation.

7 Common Data Design Mistakes in Data Cloud And How to Avoid Them

Published on March 18th, 2024

TEN MINUTES DATA CLOUD Best Practices

Drawing from hundreds of customer implementations, this expert guide identifies seven critical design pitfalls that waste credits and undermine data trustworthiness in Salesforce Data Cloud.

Through practical examples of data profiling, such as identifying fields sharing the value "Government," the article shows how to improve implementation quality.

It emphasizes deliberate data sampling, trend monitoring, and native tools like Cuneiform for Data Cloud to establish resilient foundations that balance credit efficiency with governance needs.

How to Get Started with Salesforce's Free Data Cloud Credits

Published on February 14, 2024

NINE MINUTES IMPLEMENTATION STRATEGY

This practical guide breaks down how to maximize Salesforce's free Data Cloud credits (250,000 annually for the Enterprise edition). It explains how Cuneiform for Data Cloud reduces proof-of-concept time from weeks to days through effective data profiling.

With a focus on high-value customers and fields with over 50% fill rates, the article outlines a three-step approach to gain stakeholder buy-in while uncovering hidden sales opportunities—ideal for teams beginning their Data Cloud journey without wasting precious credits.