What are database improvements?
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Definition of database improvements
Database improvements can mean improving the design of the database, improving the performance of the database, and improving the security of the database. These improvements ensure that data is accurate, secure, accessible (where appropriate) and efficiently stored in order to reduce the cost of storage and access, and to reduce downtime.
Executive view
Data is important to achieving your strategic goals, and making improvements to your database will ensure that your data is stored securely, is accurate, and is efficiently and readily available to appropriate parties.
Database improvements helps businesses:
ensure compliance with data security legislation.
reduce downtime and data loss.
ensure accurate and reliable data is available for modeling and insights.
Business function leader view
Database improvements become a priority once a team starts experiencing issues of data loss, data corruption, data inaccuracies or data security gaps. Improvements can be made to the design of the database to ensure that data storage and structure is consistent and that relationships are clearly defined, which reduces instances of duplication and decreases storage costs. Database performance can also be improved to speed up data access, and improving the security of the database helps ensure compliance.
These improvements matter most when a team:
experiences problems of data duplication, corruption or loss.
experiences database downtime.
has a large volume of data and does not have adequate security measures in place.
is using data to gain insights that drive decision-making.
KPIs worth measuring for this are:
Reduced downtime.
Increased speed of data availability.
Costs saved by reducing unnecessary load.
Reduced costs associated with data loss and corruption.
Technical view
When implementing data science and AI solutions in your products, the availability, security and accuracy of your data are essential. Implementing database improvements will improve the performance of your projects and make development smoother and more efficient.
Database improvements help deliver:
improved data security and compliance
faster page loads
faster interactive applications
user retention
reduced bounced rate
faster access to data for analysis
reduce database size
improved scalability
Signs that database improvements are overdue include:
slow performance of web pages and applications.
increasing server resource charges.
high bounce rates.
inadequate data security measures or noncompliance.
Key criteria to consider are:
The most appropriate tech stack.
The cost of improvements compared to benefits from those improvements.
Data security.
GDPR.
Any potentially unneeded data.
Database improvements in metals manufacturing
For a manufacturer, “the database” is usually the system of record behind traceability, inventory, and production planning — which changes what “improvement” actually means in practice.
Design improvements and traceability. A steel or metals manufacturer’s core database has to hold linked chains of records: a heat number on a mill certificate, linked to a stock item, linked to the cut pieces made from it, linked to the customer order those pieces fulfilled. If that relational design is inconsistent — duplicate stock records, orphaned certificate links, inconsistent heat number formats — the traceability chain breaks somewhere in the middle, and it’s usually only discovered when a quality issue forces someone to trace material back to source under time pressure. Getting the relational design right up front (proper foreign keys, consistent natural keys, no duplicated data) is a design improvement with direct compliance consequences, not just a tidiness exercise.
Temporal / audit history. Certificates get corrected, stock records get amended, orders get changed. A database design that only stores the current state of a record can’t answer “what did this record say on the date it was approved?” — which matters when a customer or auditor asks for evidence months later. System-versioned temporal tables (a native SQL Server feature) automatically retain every historical version of a row alongside who changed it and when, without the application having to hand-roll an audit log. This is exactly the kind of design improvement that pays for itself the first time someone needs to answer a “who changed this, and when” question.
Performance at manufacturing data volumes. A busy steel service centre or fabricator can generate tens of thousands of inventory and order line item rows a year, each potentially carrying a certificate link, tag assignments, and history. Query performance improvements — the right indexes on the columns actually used in list and filter queries, avoiding full table scans on frequently-queried lookups — are what keeps an inventory or order list responsive as the historical data volume grows, rather than degrading month over month as more records accumulate.
Security for compliance-critical data. Mill certificates and the chemical/mechanical test data they contain are commercially sensitive and, in regulated supply chains, subject to real accountability if they’re altered or lost. Database-level security — access control scoped correctly, encryption at rest, audit logging on who accessed or changed what — is part of what makes a digital certificate record trustworthy enough to replace the paper original in a dispute.