In March 2016, a demolition crew in Rowlett, Texas followed directions from Google Maps to a home owned by Ms. Diaz and proceeded to demolish it. Unfortunately it was the wrong house. The crew blamed Google, and the company indeed admitted there was a data error in Maps .
Lack of data integrity may not only cost your company money – it may wreak all kinds of havoc in your business and worse, the lives of your customers. Read on to learn how to move from messy, corrupted data to clean, reliable data that will enable better decisions and safeguard your company’s reputation.
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Data integrity best practices
First, what is data integrity?
Data integrity refers to the accuracy, completeness, reliability, and consistency of your data. Accurate data is free of errors such as the one in Google Maps. . Complete data has all the necessary pieces you need, such as customer emails and customer addresses. Reliable data stays stable, giving you the same results time after time. And consistent data is represented the same way across different systems. Below are five key ways to stay on top of data integrity.
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1. Establish a data governance policy
How do you plan to collect, store, and access data? How will you protect it from unauthorised access? Who is authorised to view, edit, or delete it? A data governance policy is a collaborative effort across your organisation, and creating one is time well spent. Once your data governance policy is in place you can use it to train your employees about how to manage data and who is responsible for it.
2. Ensure that you have a data recovery plan
Your recovery plan can cover all types of disruption, such as hardware failure, cyberattacks, and human error. Here are the key things to include in a good recovery plan :
- Identify the key personnel that will be involved in recovery. These are the people who will help put together your data recovery plan. They usually come from executive management, business operations, and IT.
- Define your recovery time. Your objective recovery time is the maximum amount of time it should take you to restore your data after a loss or breach.
- List your disaster recovery location. Also known as your backup site, this is a remote data centre that you can use until your local data is restored. Identify your mission-critical, sensitive, and regulated data. Critical data may be your customer data and employee data. Data that, if disclosed, would cause harm to individuals is generally considered sensitive; for example, social security numbers. And regulated data is defined by applicable laws and regulations.
- Document your communication plan in case of a disaster. Who will participate in your disaster communication plan? Who will act as the disaster manager? Which stakeholders will be notified and when? When does the public need to be notified and by whom?
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3. Enforce audits and backups
Your data can be damaged by a power outage, design failure, human error, or data breach. Audits and regular backups keep you prepared for the unexpected.
- Back up data regularly: Salesforce research has found that only 39% of IT decision-makers use backup and restore solutions, a gaping hole in an IT leader’s arsenal of tools. A data backup will protect your organisation from permanent loss because your data will be copied and can be recovered. You can be strategic about which data you want to back up automatically, such as regulated and high-value data.
- Enforce audit logs: An audit log lists the events and changes that happen in your systems and the time they happen. An audit trail is a series of audit logs. Audit logs keep you compliant with industry regulations such as CIS and help you reconstruct events in case of a disaster.
4. Use data integrity tools and technologies
With so many options on the market today, choosing one can be tricky. Use this table as a guide to the most important technologies that will help get your data in order.
|
Technology |
Purpose | Tools |
|---|---|---|
| Data validation | Perform checks on data ranges, formats, and types. Flag errors, inconsistencies, and missing data. | Informatica Multidomain, Innovative Systems Synchronos, Tableau Prep, Talend Data Catalog |
| Data profiling | Sift through data to review, analyse, and assess its legitimacy. | Open source: Hevo, IBM InfoSphere Information Analyser, Informatica Data Quality and Profiling |
| Data cleaning, aka data cleansing or scrubbing | Remove incorrect, corrupted, duplicate, or incorrectly formatted data. | Tableau Prep, Trifacta Wrangler, OpenRefine |
| Data governance | Reinforce your policies and procedures. Catalog data, assess data quality, and reconcile data collected from various sources. | Tableau, Apache Atlas, Collibra Data Governance, OneTrust Data Governance |
| Data monitoring | Track data quality to assess whether it’s fit for purpose. Stay on top of data quality with alerts, dashboards, and reports. | Datadog, SolarWinds, Dynatrace, Salesforce Event Monitoring for the Salesforce CRM |
| Data encryption | Protect data from being changed, stolen, or compromised. Scramble data into a secret code that can only be unlocked with a unique decryption key. | Folder Lock, AxCrypt, VeraCrypt, Salesforce Salesforce Voice Platform Encryption for the Salesforce CRM |
| Zero copy integration (or zero-ETL) | Share data between two or more data stores without actually moving it. The technology cuts down the expense and risk of data errors. | Talend, Informatica, AWS Glue. Also available between Salesforce and Snowflake. |
5. Train and educate your employees on data integrity
Every employee plays a role in maintaining good data hygiene. Once you implement your policies for data governance and health, provide your employees with the appropriate training. Make sure they understand their roles and responsibilities, and keep the training top of mind with frequent reminders.
Get going on your data integrity journey
Staying on top of data integrity will pay off by saving you hours in productivity, giving you data you can trust to make better decisions, and enhancing your reputation with customers and partners.
Data integrity best practices FAQs
Best practices involve implementing rigorous data validation rules at the point of entry, establishing clear and enforced data governance policies, performing regular data audits and profiling, and maintaining strict access controls to data.
Data validation rules are crucial for enforcing accuracy by checking data inputs against predefined criteria and formats. They prevent incorrect, incomplete, or inconsistent data from entering the system, maintaining data quality from the start.
Data governance provides the overarching framework, policies, processes, and assigned responsibilities necessary to consistently maintain high levels of data quality and integrity across the entire organization throughout the data lifecycle.
Regular data auditing helps identify inconsistencies, errors, anomalies, and potential vulnerabilities within datasets. This proactive approach allows for timely correction of issues and continuous improvement of data integrity processes.
Robust data backup and recovery procedures are critical for safeguarding data integrity. They ensure that data can be accurately and swiftly restored to a valid state in the event of system failures, data corruption, or accidental loss.
Access controls limit who can view, modify, or delete data based on their roles and permissions. This significantly reduces the risk of unauthorized changes, accidental corruption, or malicious tampering, thereby preserving data integrity.
Data Governance Tips and Best Practices
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