Take Control of Your Data: Effective Data Management Best Practices
- Sesame Software
- 10 hours ago
- 3 min read
Data is your company’s most valuable asset, but only if you can find it, trust it, and use it. Take control of your data with a straightforward, step-by-step approach: assess what you have, lock it down, automate the heavy lifting, and govern continuously.
Read on for five practical steps you can start today based on our decades of experience developing, and helping customers implement, data management best practices.
Why Data Management and Handling Best Practices Matter
When data is messy or inaccessible, it becomes a source of risk and cost. Good practices increase accuracy, protect sensitive information, make data discoverable, and ensure regulatory compliance, all while saving time and money.
Defining the Business Reason for Moving Data Comes First
Many data engineering teams are told to “replicate everything” because the business expects all data to be available everywhere. But without understanding why the data is being moved — what decisions it supports, who needs it, and how often — companies end up replicating far more than they actually use.
This creates more pipelines to maintain, higher storage and compute costs, and future integrations that are harder to scale. A clear business purpose helps teams choose the right data to move, not all of it, so they can design efficient, durable systems from the start.
This upfront clarity is also where tools like Sesame Software make a difference: our platform lets teams move only the data they need, at the frequency they need it, without building excess pipelines or custom code.
5 Steps Toward Data Management Best Practices
1. Assess your data landscape. Map your sources, flows, and owners. Identifying where data lives and who uses it reveals gaps, redundancies, and risk.
2. Define clear policies. Standardize naming, retention, access, and deletion rules so everyone follows the same playbook.
3. Secure proactively. Use encryption, role-based access, and audit logging — and test your protection and access processes regularly.
4. Automate routine tasks. Automate replication, synchronization, and backups to reduce human error and improve consistency and reliability.
5. Govern continuously. Monitor data quality, measure compliance, and refine policies with stakeholder input as systems evolve.
Practical Tips That Make a Difference
Start small: pick one critical dataset (CRM, finance) and optimize it first.
Use consistent naming conventions and metadata.
Archive or tier older data to keep production systems fast.
Set up alerts for data quality drift or failed automations.
Choose tools your team will actually use, because adoption matters.
How Our Solution Helps
Sesame Software helps teams take control of their data by centralizing access, automating replication and synchronization, and providing secure, governed endpoints for analytics and integration. Our platform supports high-frequency data movement, granular access control, and bring-your-own storage for cost efficiency, so your team spends less time managing data and more time using it.
Next Steps for Implementing Data Management Best Practices for your Organization
Talk to a data expert about your specific needs.
Explore our platform capabilities — from backup and replication to pipelines and migration.
See how customers use Sesame Software to regain control of their data.
Effective Data Management FAQ
How often should I back up critical data?
That depends on business impact — for mission-critical applications, aim for high-frequency or near real-time replication; for most others, daily or scheduled backups with incremental captures are common.
Can automation replace manual data cleanup?
Sesame Software continuously replicates data between Salesforce and NetSuite Automation reduces manual work by handling replication, deduplication, and monitoring — but governance and human oversight remain essential. of relying on point-to-point integrations. This approach keeps customer, billing, and revenue records synchronized in near real time, eliminating version mismatches and reducing the need for manual updates or reconciliation.
What’s the difference between archiving and backing up?
Backups are for operational protection and continuity; archives are for long-term retention and historical access. Both are important but serve different business needs.
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