Salesforce Data Governance vs. Data Managemen

Businesses collect data from multiple sources constantly. They use this data in a decision-making capacity and to streamline their operations. Data collection is accompanied by the responsibility to handle it securely and comply with relevant laws and regulations. 

Salesforce organizations generate massive amounts of data and often consume data from other systems, making effective data governance and management practices more crucial than before. Although they may sound similar, Salesforce data management and data governance are different practices. In short, data governance establishes policies and procedures, and data management puts them into action. 

Both are equally important for organizations handling large amounts of Salesforce data. Data governance and management directly impact your organization’s quality of data. Understanding the differences between data management vs. data governance is paramount for businesses to use their data effectively within the Salesforce context. 

  1. What Is Salesforce Data Management?
  2. What Is Salesforce Data Governance?
  3. Why Are Data Management + Data Governance Important for Salesforce?
  4. Differences Between Data Governance vs. Management
  5. Salesforce Data Management vs. Data Governance Best Practices
  6. How to Combine Data Governance + Data Management
  7. Enhance Governance and Accountability for Salesforce With OrgScan
What Is Salesforce Data Governance?

What Is Salesforce Data Management?

Modern organizations have access to massive amounts of data. Data management stores, organizes, secures, and maintains data to ensure they are viable assets to a business. One of the main goals of data management is to ensure data is accessible and used for its intended purposes only, discarding it properly when it’s no longer of value. 

Data assets have a life cycle. Data management provides reasonable access to data by managing that life cycle, from creating assets to retirement. Well-designed and executed data management eliminates data silos. It allows for better data flow across the organization—access to pertinent data results in better operational strategies and more successful decision-making. 

Data management can answer the following questions:

  • How do we ensure data is not redundant?
  • How do we maintain the quality of data?
  • Which IT tools should we use?
  • How well is the data secured?
  • How can we make data available to the organization to augment decision-making?

Common Elements of Data Management

Data management is a broad term that covers several specific practices, including data governance. Some other data management practices include the following:

  • Data preparation: The process of cleaning and transforming raw data for analysis. Data preparation ensures the data is of sufficient quality to use in decision-making.
  • Data security: The processes used to protect your data from unauthorized access by malicious actors or corruption.
  • Data architecture: The formal structure for managing data flow within an organization.
  • Data catalogs: The management of metadata and listing of data so it’s easy to find, creating an accessible overview of an organization’s data and giving users the complete picture.
  • Data pipelines: Tools used to transfer data between systems.
  • Data extract, transform, load (ETL): Transforming data to load in a data warehouse.
  • Data warehouse: Consolidates all data sources to provide clarity for data analysts.

What Is Salesforce Data Governance?

Data governance is a component of data management. It’s a set of defined structures, measurements, rules, and policies to serve goals like creating harmony between business units and data. Another goal of data governance is to ensure data quality by measuring it against parameters such as data security, usability, availability, and consistency. 

Specialized data stewards are responsible for data governance. They help monitor how their teams use and interact with data sources and ensure that team members remain compliant and aligned with data principles. With data governance in place, organizations have factual information about the ownership of the data, who can access it, how it is secured to ensure data privacy, and whether the data is compliant with regulations. 

Salesforce is an excellent example of governance in many ways, as new people constantly come in from acquisitions, and there is a need to get everyone working together. 

Some of the questions data governance answers include the following:

  • Who owns the data?
  • Who should have access to it?
  • How can we be compliant with regulations?
  • What data is required to make solid business decisions?

Principles of Data Governance

Organizations should follow a specific structure to align with data governance best practices that ensure data governance success. Organizations often base these practices on some of the following principles:

  • Integrity: To align with the principle of integrity, the organization uses ethical data management practices and maintains integrity in its choices. 
  • Stewardship: Assigning qualified team members to the role of data stewards and making them responsible for ensuring members of the organization follow the policies and rules defined by its governance structure. 
  • Auditability: Businesses must maintain accurate, and up-to-date records of all data used to show compliance with regulatory standards. 
  • Standardization: Data must be accessible and transparent, so data stored in different formats should be harmonized based on specific definitions.

Why Are Data Management + Data Governance Important for Salesforce?

Both data management and data governance are critical to gaining valuable data insights. Businesses need to use tools to manage data in their Salesforce orgs. Still, data governance is just as essential to ensure actionable policies and processes are in place to achieve strategic business goals. 

Businesses all strive to improve the decision-making process with data-driven insights, but the decision-making is impaired if the data is flawed. Basing critical decisions on poor-quality data can cause irreparable damage to an organization. Managing Salesforce data effectively and timely is crucial. It makes data suitable to augment decision-making available to stakeholders and team members. 

On the other hand, data governance is about enacting policies and procedures and holding people accountable within your team. Salespeople can still function in the short term without governance over using Salesforce. Still, businesses that pay little attention to data governance will miss the meaningful business insights associated with long-term improvement. New regulatory compliance requirements make data governance more critical than ever, especially regarding data privacy. 

Salesforce is of the most value to businesses with correct data management and governance, providing their teams with definable expectations and actionable policies.

Differences Between Data Governance vs. Management

While data management and data governance work together, it’s important to remember that data governance is part of data management. Differences between data management and data governance include the following:

  • Data governance defines procedures and policies around the use of data, and data management provides a structure regarding how team members execute these procedures and policies. 
  • Data management utilizes technology to a large extent. Data governance uses tools but places a more significant emphasis on strategic planning. 
  • Data management organizes data, and data governance provides the framework to make this organization possible. 
  • Data management aims to ensure data is accessible, reliable, and secure, and data governance leverages data to reduce risks and add value to an organization.
Salesforce Data Management vs. Data Governance Best Practices

Salesforce Data Management vs. Data Governance Best Practices

One of the most effective ways to view the differences between data management and data governance in Salesforce is to compare their best practices. The best practices illustrate the differences in the following ways:

Salesforce Data Management Best Practices

Salesforce gives you the power to leverage your business data. Implementing an efficient and detailed Salesforce data management strategy is critical. Data is integral to business operations, from the most basic to the most complex Salesforce customer relationship management (CRM) implementations. Data integrity is a vital element of Salesforce data management, as it dictates the quality of the data stored in Salesforce.

Some data management best practices for Salesforce include:

  • Naming data: The right people need access to Salesforce data at the right time. Data should be named according to specific organizational conventions so team members who access the data have an accurate understanding of the data’s underlying information and can differentiate records from one another.
  • Eliminating duplicate records: Duplicate records create an inaccurate view of databases and result in wasted efforts from sales and marketing teams. Removing duplicate records provides accurate revenue calculations and sales projections.
  • Keeping data relevant: Over time, the quality and integrity of data diminish. Updating data with add-on applications can help remove redundant data in line with Salesforce data governance practices.
  • Prioritizing data validation: The Salesforce data management rule is highly effective in validating data at an individual and organizational level. Implementing third-party validation for customer data such as addresses and phone number is critical to align with data security regulations.
  • Archiving and data backup: In line with specific business requirements, it’s always best to back up and archive data within the Salesforce system. Data is fluid, making it vulnerable to corruption and damage. Implementing a detailed backup strategy protects the business’s Salesforce data and aligns with data governance protocols.

Salesforce Data Governance Best Practices

One of the goals of a clear Salesforce data strategy is to meet compliance and governance demands. As Salesforce environments contain such large amounts of data, team members should be able to locate it and attest to its quality. Some best practices for Salesforce data governance include the following:

  • Defining goals: Identifying weaknesses in your operations gives you a clear view of which areas to address. Businesses must define critical goals in their Salesforce data governance strategy and implement all practices with these goals in mind.
  • Creating a Salesforce data governance framework: A data governance framework outlines your strategy and establishes the rules and processes for collecting, storing, and using data. Including clear definitions of processes and roles ensures team members handle data uniformly.
  • Assigning roles: To ensure data governance is taken seriously, businesses can appoint data governance teams focused on achieving data governance goals. The teams could include a manager overseeing the governance system and individuals managing different governance initiatives.
  • Communicating role expectations: Each member of the data governance team must have a complete understanding of their role, and the tasks required by their role. Companies should foster an open communication culture to provide all team members with clear communication and continuous updates.
  • Focusing on data protection: The nature of Salesforce data means that sensitive data will come into the possession of various teams across an organization. Teams must protect and handle sensitive data, including personal, financial, and medical information, with backup maintenance, secure passwords, and minimize exposure.
  • Balancing backlog with new projects: Salesforce environments have a lot of data, which continues to grow as organizations incorporate new applications and gain new customers. Data governance includes analyzing and managing existing data sets to provide a foundation for future data-driven processes.
  • Including metadata: While metadata may seem like a secondary concern compared to sensitive data like customer information, it plays a critical role in your Salesforce environment, and teams should handle and protect it the same way.
  • Monitoring for actionable feedback: Salesforce environments are fluid and ever-changing. Having an excellent data governance strategy is one thing, but businesses should monitor the efficacy of their systems to keep up with the environment. Identifying successes and opportunities for improvement is critical to providing advantages across the Salesforce environment.
How to Combine Data Governance + Data Management 

How to Combine Data Governance + Data Management

Data management and data governance should work together to be of the most value to businesses. Policies and procedures set out by suitable data governance guide the data decisions and usage in successful data management systems. Stakeholders must understand the importance of accurate and ethical data to build a company culture where data management and governance work together to provide the best Salesforce outcomes. 

Governing your Salesforce data is necessary but only adequate with active management. Throughout the lifetime of your data, it’s critical to maintain its quality and make it accessible and transparent to its users. One without the other makes little sense. Enhancing Salesforce data without clarification on roles and responsibilities is nonsensical. Similarly, having clear governance principles without data management activities will have limited value. 

Enhance Governance and Accountability for Salesforce With Salesforce Security Posture Management

Your Salesforce environment mandates your specific security and compliance rules. Salesforce security posture management governs your organizational policies by enforcing these rules. Businesses need help to stay in compliance with the regulations and policies they put in place. Salesforce security posture management helps companies maintain compliance and strengthen accountability with the following approaches:

  • Saving money: At the end of each scan, Salesforce security posture management creates an interactive dashboard that identifies your compliance score and draws your attention to any areas of concern, saving time and money. 
  • Addressing metadata rules: Salesforce security posture management rectifies metadata rules in the areas of your Salesforce environment that need it most, such as permission sets, session settings, user settings, and profiles. 
  • Tracking policy review progress: With effective tracking of your policy review, admins can maintain governance control. 

Salesforce security posture management makes it easy to understand the complexities of your Salesforce environment, whether you’re an experienced developer or an admin. A simple, easy-to-use, no-code interface allows anyone to verify policy adherence. You’ll also receive alerts if something needs to match your compliance requirements. 

With Salesforce security posture management, you can utilize specialized dashboards and reports to interpret your data and reap the benefits in the following ways:

  • Gathering actionable information: With the actionable information collected by Salesforce security posture management, you can establish governance policies and procedures to provide consistent coverage and use it to address your immediate needs. 
  • Defining policy parameters: You can hold your team accountable by assessing their ability to meet current standards. 
  • Promoting data security: Protecting sensitive data is imperative to meet privacy regulations, and Salesforce security posture management allows you to define parameters for viewing data sets within your team. 
  • Enhancing reporting: Reporting is easier with Salesforce security posture management, and a user-friendly interface allows your business to stay ahead of Salesforce regulations. 
salesforce security posture management

Next Step

CodeScan and Salesforce security posture management take your business to the next level with static code analysis and comprehensive scans to optimize your data governance and productivity strategies. You can have complete visibility of your environment’s health, reducing cost and minimizing your time to market. 

With Codescan’s two-pronged approach, you can eliminate coding errors and guarantee correct system settings every time, reducing bugs, speeding up the review process and eliminating technical debt. Schedule a demo to learn more today!


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