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Introduction

Data governance is very important. It helps companies manage their data.

Good data governance has rules and policies. These help keep data safe and correct. They also make sure companies follow laws about data.

This article explains why data governance matters. It gives examples of how to do it well.

Contents: The Importance of Data Governance: Examples of Effective Strategies

The Importance of Data Governance: Examples of Effective Strategies podcast

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Why Data Governance Is Important

Here are 3 big reasons data governance is important:

1. It Keeps Data Accurate

Good data governance stops errors. It makes sure data entry is careful. This keeps data precise.

For example, a store can check that it enters customer names right. Then the data is dependable. This helps the company make good choices.

Benefits:

  • Accurate data
  • Good business decisions
  • Happy customers

2. It Protects Data

Data governance guards data safety. It has login rules. These stop unauthorized changes. It may encrypt data too. That codes data so only some can read it.

For instance, a hospital could limit record access. Then only certain staff see patient files. This secures private data and follows privacy laws.

Benefits:

  • Data security
  • Legal compliance
  • Patient trust

3. It Helps Follow Laws

Governments make data laws. Companies must obey them. Data governance helps do this.

For example, GDPR shields EU citizen data. Firms worldwide must honor it. Data governance supports this. It can detail data practices. And limit data as needed.

This avoids fines. It also builds user faith.

Benefits:

  • Regulation compliance
  • Less legal penalties
  • More customer trust

Examples of Good Data Governance

Many methods work. Here are 3 solid ideas:

1. Data Classification

  • Rank data by 3 levels:
    • High sensitivity
      • Very private data like finances
    • Medium sensitivity
      • Basic customer details
    • Low sensitivity
      • Generic marketing data
  • Give tighter security to higher sensitivity batches. This focuses resources.

2. Data Stewards

  • Assign staff as stewards. They oversee data areas.
  • They check quality and fix issues. This person may handle product details. They verify accuracy and share reports.

3. Data Lifecycle Rules

  • Outline data handling from start to finish:
    • Set storage limits
    • Archive old data
    • Delete unneeded data

This cuts costs and risks. It makes key data easy to find too.

Pros and Cons of Data Governance

Data governance has many pros. But there are some cons too:

Pros

  • Better decisions from quality data
  • Less legal and privacy risks
  • More trust in company data handling

Cons

  • Costs money and staff to set up
  • Slows processes like data entry
  • Requires employee training

Overall, the pros outweigh the cons. Some cons decrease over time too. Employees get faster at new procedures with practice.

Real-World Examples

Data governance aids many industries:

Hospitals

Hospitals secure health data. Rules detail who can enter and access records. For example, doctors may add visit notes. But clerks should not see diagnoses.

Stewards also verify entry. This catches errors before they enter medical history. Precise data saves lives. So governance is crucial.

Insurance Firms

Insurance data must be accurate – and kept private. Governance defines access and retention rules. For instance, policy terms may show client names, ages and payout details. This data needs encryption and short retention periods.

Clear procedures protect sensitive data. They also prove the company is accountable and ethical.

Retail Chains

Chains have massive customer data. Much is personal like purchase history. Governance limits gathering and sharing of this information. It also deletes data after set periods to reduce risk.

In addition, steward teams check listing details. This ensures the brand and pricing are right across channels. Correct data helps order fulfillment and avoids confusion or over-selling.

Key Takeaway

  • Data governance creates data reliability through accuracy checks, security rules, compliance procedures and responsible data handling from start to finish. This builds trust in data – and the company itself.

Conclusion

In closing, data governance matters. First, it makes data dependable with checks and standards. Next, it protects sensitive information from misuse or theft. It also shows consumers and governments that data practices are ethical and accountable.

Some parts of data governance cost more money and time upfront. But precise data, security and compliance make it very worthwhile. Governance helps answer key business questions too. For these reasons, invest in robust data supervision. Customers, leaders and data teams will be glad you did.

Call to Action

Review current data policies. Do they cover accuracy checks and access rules? Is sensitive data encrypted? Are stewards assigned? Make upgrades to improve governance now. This futureproofs operations as data volumes grow. Contact our team to start the process.