ReadOS / Technology
Databases and Data Models — Part 2
Relational thinking, database structures, data integrity, queries and information architecture.
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- 01ORM loading strategies and hidden query costsDiagnose hidden database work in object-relational mapping by comparing lazy, joined and batched loading against the data each application operation needs.
- 02Paging database results without skips or duplicatesChoose a pagination strategy with explicit ordering, continuation and consistency rules, and test how inserts, deletes and changing sort values affect traversal.
- 03Partitioning database tables around real workloadsChoose database partition boundaries using query patterns, data lifecycle and maintenance needs, while checking indexing, late arrivals and operational costs.
- 04Preventing double counting in SQL joinsLearn why valid SQL joins can inflate business totals, how to define the grain of a report, and how to reconcile aggregates before trusting the result.
- 05Reading query plans through row estimatesDiagnose database query plans by comparing estimated and actual row counts, tracing estimation errors and testing targeted improvements against real workloads.
- 06Relational, document, graph or time-series: choosing the right kind of database for the jobDifferent databases suit different data shapes and workloads. How relational, document, key-value, graph, time-series, search and analytical databases compare, and how to choose.
- 07Replacing overloaded status codes in databasesHow to separate independent business facts hidden inside one status code, choose flags or related records appropriately, and migrate old meanings without inventing missing information.
- 08Reporting databases and data warehouses: separating day-to-day systems from analysisReports run on live systems slow work and disagree with each other. How reporting copies, data warehouses and dimensional models give consistent figures, and how to start small.
- 09Retiring database compatibility structures safelyHow to prove old database views, columns and synchronisation paths are no longer needed, account for infrequent consumers, and remove them with a tested recovery plan.
- 10Retrying database work without repeating business effectsDesign database retries around known transaction outcomes, repeatable operations, bounded deadlines and load control so that recovery does not duplicate work.
- 11Securing business databases: access, encryption, exposure, injection risks and monitoringDatabases hold the information attackers want most. How to classify data, limit access, encrypt it, keep databases off the internet, guard against injection and detect misuse.
- 12Separating database access from business decisionsHow to place a useful boundary between persistence code and business rules, preserve transaction meaning and test applications without hiding important database behaviour.
- 13Sizing and managing database connection poolsUnderstand connection pool limits, waiting time, transaction scope and failure recovery so application demand stays within the database's capacity.
- 14SQL for managers and analysts: reading and writing simple queries to answer business questionsA little SQL lets managers and analysts answer questions directly from business data. The core of the language, how to avoid common traps and how to check results before trusting them.
- 15SQL NULL and the meaning of missing dataUnderstand how missing values affect SQL filters, totals and business decisions, with practical ways to distinguish unknown, absent and inapplicable data.
- 16SQL queries for meeting every requirementUse relational division to find records that satisfy every required condition, with clear treatment of missing evidence, duplicate records and empty sets.
- 17SQL set operations and the meaning of duplicatesChoose union, intersection and difference by defining record identity and multiplicity, then validate combined datasets without hiding legitimate repeated events.
- 18Tables, keys and relationships: how business databases are structured, for the people who commission themA plain-language guide to relational databases: entities, keys, relationships, normalisation, constraints and transactions, and how to review a proposed data model.
- 19Testing data models with facts and counterexamplesValidate a conceptual data model using precise sentences, small example populations and counterexamples that expose hidden uniqueness and participation assumptions.
- 20Time intervals, overlaps and gaps in databasesModel database time intervals with clear boundaries, detect overlaps and coverage gaps, and distinguish business-effective periods from recorded history.
- 21Updating sets of database records correctlyHow to define a multi-record database change, select the right population, avoid ambiguous update joins, and verify the result without relying on row-by-row assumptions.
- 22What a database management system does: storage, queries, concurrency, recovery and security explainedBehind every business system sits software that stores, protects and shares its data. What a database management system does, in plain language, and what owners should ask about it.
- 23When a business outgrows its spreadsheets: choosing between spreadsheets, databases, low-code apps and packaged systemsSpreadsheets are superb for analysis but fragile as shared record systems. How to recognise when one has become a system, and how to choose and make a move that lasts.
- 24Why business systems slow down: diagnosing database performance before buying more hardwareSlow business systems are often blamed on hardware. How to measure the problem, find where time is really lost, fix common database causes and plan capacity before it runs out.
All chapters preserve the original KEVOS Insights content. These topic-based reading collections are organised alphabetically; chapters may be read in any order.
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