Database Migration
Plan conversion, validation, rehearsal, cutover and operating handover across on-premises and cloud environments.
Oracle · SQL Server · PostgreSQL
Managed database services for dependable production operations.
Datrick provides senior DBA support, monitoring, migration, performance tuning, and recovery for CTOs and IT service firms. Keep on-premises and cloud databases reliable, with clear ownership across data pipelines, BI, and AI integrations.
Operating control loopEvidence before expansion
1
OwnInventory systems, access, dependencies, recurring work, risks, stakeholders, and accountable owners.
Context2
OperateMonitor signals, handle incidents, coordinate backups and restores, and maintain escalation paths.
Continuity3
ChangePlan, test, approve, execute, validate, and document migrations and production changes.
Control4
ImproveReduce recurring failure, tune workloads, strengthen reporting, automate repeatable work, and update runbooks.
ProgressSpecialist services
Find the right scope for your production systems.
Database Monitoring
Connect health signals, alert triage, escalation and review to an agreed operating owner.
PostgreSQL DBA Services
Operate queries, maintenance, replication, backup recovery and database changes.
SQL Server DBA Services
Support T-SQL, scheduled jobs, query performance, availability and upgrades.
Oracle DBA Services
Scope administration, authorized diagnostics, recovery and migration support.
Database Performance Tuning
Establish a workload baseline, diagnose bottlenecks and measure controlled improvements.
Disaster Recovery and High Availability
Define recovery objectives, restore evidence, failover responsibilities and drills.
BI Support Services
Keep reporting, refreshes, models and their production dependencies under an agreed support scope.
Platform expertise
Operational depth across your database estate.
Oracle Managed Services
Database monitoring, SQL performance review, backup and recovery, replication, high availability, and migration planning. Define authorized access, maintenance windows, and recovery expectations before taking ownership.
SQL Server Managed Services
T-SQL development, query and index tuning, scheduled job reliability, backups, availability, and migration support. Plan conversion, application dependencies, validation, and cutover for on-premises or cloud targets.
PostgreSQL Managed Services
Query tuning, index and vacuum maintenance, replication, backup verification, restore drills, and production incident support. Include data reconciliation and operating handover in every migration scope.
What success means
Data operations is not a ticket queue. It is accountable continuity across systems and change.
The environment can be understood without one indispensable person
Systems, access, dependencies, recurring work, reporting commitments, known issues, decision routes, and escalation paths are visible enough for an authorized team to operate and change responsibly.
Incidents and recurring work have a controlled response
Monitoring signals, severity, coverage, backup and restore expectations, on-call boundaries, status communication, evidence capture, and follow-up actions are explicitly assigned.
Migrations and releases preserve evidence and rollback options
Readiness, data validation, output comparison, performance, reporting continuity, approval, cutover, rollback, and handover are treated as operating responsibilities rather than last-minute checks.
Business decisions do not depend on unexplained dashboards
KPI definitions, source ownership, refresh schedules, access rules, transformation logic, quality checks, performance behavior, and stakeholder outputs are documented and reviewable.
Entry routes
Start with the failure mode creating business pressure.
ContinuityOperate and recover
Emergency DBAControlled incident intake, production triage, evidence capture, stabilization, and next-step scoping.
Handover recoveryInventory, authorized access, dependencies, risks, runbooks, recurring work, and named ownership.
DBA / NOC programMonitoring, incidents, backup checks, restore coordination, performance review, and escalation cadence.
Reliability backlogRecurring failure analysis, monitoring improvements, runbook updates, automation, and ownership cleanup.
DeliveryMove and report
Migration supportDevelopment, QA, reconciliation, performance review, cutover readiness, rollback evidence, and transition.
Power BI managed servicesKPI logic, dashboard ownership, refresh reliability, stakeholder outputs, access, data quality, incidents, releases, and improvement work.
Analytics and pipelinesModels, transformations, integrations, orchestration, quality checks, analysis, and operating handover.
PerformanceQuery patterns, scan behavior, model structure, refresh workloads, capacity drivers, and maintainability.
Delivery evidence
Use measured outcomes where measurement is available, and clear boundaries where it is not.
68% faster analytical queries
A warehouse optimization engagement reviewed query patterns, model structure, scan behavior, refresh ownership, and reporting-layer maintainability. Measured query time fell by 68%.
85% lower scan volume
The same engagement reduced unnecessary data scanning by 85%, improving both reporting responsiveness and the operating team's ability to explain workload behavior.
Reliable delivery expanded into adjacent services
An IT operations partner began with urgent database and migration needs. Prompt, documented execution led to additional BI, reporting, analytics, and operations work while the partner retained the client relationship.
Client and contract details remain private
The partner's identity, end-client identity, environments, workloads, rates, contract terms, and confidential operational metrics are not published. The operating pattern is shared without inventing public proof.
Core operating controls
Critical environments need explicit boundaries before delivery begins.
Authorized and attributable
Named accounts, least privilege, secure credential channels, environment boundaries, approval, expiry, revocation, and emergency procedures are agreed with the authorized owner.
Defined rather than implied
Support windows, severity, response expectations, on-call duties, communication routes, escalation, and exclusions are written into the operating model.
Reviewable and reversible
Request, approval, implementation, validation, rollback, evidence, and stakeholder communication are assigned before critical changes are executed.
One decision route per responsibility
Systems, jobs, dashboards, runbooks, vendors, incidents, risks, and business outputs have accountable owners and an escalation path.
Decisions leave an operating record
Status notes, assumptions, findings, changes, tests, risks, known issues, runbooks, and acceptance evidence reduce reliance on memory.
Recurring work becomes a backlog
Repeated incidents, slow workflows, manual checks, unclear reports, and missing documentation are prioritized instead of rediscovered indefinitely.
Phase-gated onboarding
Build control before expanding responsibility.
- 1
Qualify
Describe the business risk, service area, environment, workload, urgency, stakeholders, current ownership, and what has already been tried.
- 2
Inventory
Map systems, environments, authorized access, dependencies, monitoring, repositories, recurring work, reports, vendors, and active changes.
- 3
Classify
Separate critical continuity gaps from high, moderate, and planned improvement work using operating consequences and available evidence.
- 4
Agree controls
Confirm coverage, priorities, communication, access, approvals, deliverables, acceptance, escalation, documentation, and commercial boundaries.
- 5
Deliver
Execute the prioritized scope through a named lead, surface blockers early, preserve evidence, and maintain reviewable status.
- 6
Improve or hand back
Continue into an operations program, extend a project, or complete a documented transfer based on demand and observed results.
Engagement shapes
Choose the smallest model that can own the required outcome.
Incident or ownership recovery
A bounded production issue, failed handover, migration blocker, reporting failure, or immediate operational risk.
Typical outputControlled intake, evidence, risk, stabilization actions, ownership map, and recommended next scope.Project or improvement workstream
Migration QA, BI reliability, performance optimization, pipeline delivery, documentation, or another defined outcome.
Typical outputPlan, deliverables, implementation evidence, validation, risks, runbook updates, and handover.Data operations program
Recurring database, migration, reporting, analytics, and improvement responsibilities with agreed coverage and cadence.
Typical outputNamed ownership, prioritized backlog, status, incident context, documentation, and senior review.Data operations FAQ
Questions to resolve before granting responsibility.
What is included in Datrick data operations support?
Scope can include database operations and NOC coverage, backup and restore coordination, incident support, database handover recovery, migration development and QA, BI reporting reliability, analytics, pipelines, integrations, performance tuning, runbooks, and operational improvement. Final coverage is documented for each engagement.
Can Datrick take over an undocumented data environment?
Datrick can begin with an evidence-led handover recovery: inventory systems, map authorized access, identify dependencies, review monitoring and recurring work, classify risk, create runbooks, and establish named ownership. Missing information is recorded as risk rather than guessed.
Can we start with one urgent data operations issue?
Yes. Many engagements begin with one bounded problem such as an incident, failed handover, migration blocker, slow reporting workload, unreliable dashboard, or missing pipeline owner. Datrick then recommends whether to close the scope, extend the project, or establish ongoing coverage.
Does Datrick provide 24/7 database support?
Coverage windows, on-call responsibilities, severity definitions, response expectations, escalation paths, and staffing depend on the engagement. Datrick does not represent every data operations engagement as automatic 24/7 support; the required coverage model must be scoped and confirmed in writing.
How is migration support different from owning the entire migration?
Migration support can cover a defined workstream such as development, QA, reconciliation, performance review, reporting continuity, cutover readiness, rollback evidence, or handover. Full migration ownership adds broader architecture, program governance, stakeholder, dependency, and acceptance responsibilities and must be scoped separately.
What does data operations onboarding require?
Onboarding normally requires named stakeholders, a system and environment inventory, authorized access paths, monitoring context, known incidents, backup and restore expectations, repositories, recurring work, reporting dependencies, active change plans, communication routes, and approval authority. Sensitive credentials should never be sent through the website form.
Operations library
Find the guide that matches the operating risk before written scoping.
Database operations handover checklist
Prepare systems, access, backups, monitoring, recurring work, escalation, risks, and reporting dependencies.
Migration support playbook
Prepare QA, validation, reporting continuity, cutover, rollback, stakeholder updates, and operating handover.
ETL and ELT pricing guide
Compare row-, connection-, usage-, and infrastructure-based pricing before committing a growing data estate to an integration platform.
BI reporting reliability checklist
Prepare KPI definitions, dashboard ownership, refresh cadence, access, data quality, and stakeholder review.
Power BI and Fabric managed support
Establish accountable ownership for reporting reliability, gateways, governance, incidents, releases, service reporting, and continuous improvement.
Database performance incident triage
Connect waits, locks, queries, plans, platform evidence, and changes into a safe, supervised DBA investigation workflow.
Data pipeline failure triage and recovery
Use run evidence, lineage, quality, output state, and controlled recovery policies to restore failed data workflows safely.
Data migration reconciliation and validation
Build layered source-to-target validation, exception evidence, CDC checks, and an accountable cutover gate.
BI report reconciliation and freshness incidents
Detect stale or inconsistent reports with source cutoffs, refresh evidence, KPI controls, impact, and accountable recovery.
Power BI semantic model refresh and gateway reliability
Manage refresh failures, schedules, gateway HA, credentials, capacity overlap, incremental partitions, freshness SLAs, and validated recovery.
Microsoft Fabric throttling and cost-performance optimization
Connect CU smoothing, throttling, operations, workspaces, items, users, performance, schedules, and Azure cost into an approval-ready capacity decision.
Power BI report, DAX, and semantic model optimization
Find the measured bottleneck across visuals, DAX, model structure, storage mode, Power Query, sources, gateways, and capacity, then validate correctness and user latency.
Power BI and Fabric tenant governance
Build a verified inventory, restore ownership, review effective access, classify lifecycle, and operate evidence-backed archive and remediation decisions.
Power BI and Fabric CI/CD release governance
Replace manual publishing with controlled source, environment binding, dependency sequencing, testing, approval, rollback, and post-deployment validation.
Power BI and Fabric tenant-to-tenant migration
Map source and target tenants, artifacts, identities, gateways, dependencies, data, security, links, cutover, validation, and post-migration operations.
Power BI RLS and effective-access security audit
Audit workspace roles, Build permission, app audiences, direct grants, external sharing, service principals, RLS, and source access before controlled remediation.
Power BI and Fabric L2/L3 managed support
Add incident ownership, monitoring, complex escalation, controlled changes, backlog delivery, SLA reporting, and service improvement under your brand.
AI agent L2/L3 operations for MSPs
Operate client agents under the partner's brand with quality regression, telemetry, retrieval, tool, identity, incident, release, cost, and reporting controls.
Power BI developer handover and takeover rescue
Restore ownership, reconstruct undocumented dependencies, validate business outputs, stabilize personal credentials, and establish a supportable operating model.
Tableau to Power BI migration assessment and validation
Inventory and rationalize the Tableau portfolio, map semantic logic, prove a representative pilot, validate parity, and cut over with controlled adoption.
SSRS RDL to Power BI paginated report migration
Assess catalog usage and compatibility, migrate supported RDLs, redesign exceptions, rebuild distribution, validate rendering, and retire report-server dependencies.
Power BI Embedded multi-tenant SaaS assessment
Test service principal profiles, customer mapping, RLS identity, embed tokens, lifecycle automation, capacity SLOs, and cross-customer isolation.
Power BI and Fabric Copilot readiness
Prepare governed semantic models, configure AI context, evaluate answers against deterministic controls, and roll out Copilot by use case and risk.
Microsoft Fabric readiness and adoption roadmap
Choose the first production workload, establish architecture and operating controls, validate capacity economics, and sequence a 90-day implementation plan.
Microsoft Fabric disaster recovery and business continuity
Prove item-level protection, reconstruction, recovery sequencing, security, reconciled data, RPO, RTO, and business acceptance with a controlled drill.
Microsoft Fabric managed services and support
Give production workloads accountable monitoring, incident response, capacity and cost control, reliable change, backlog delivery, and continual improvement.
Azure Synapse to Microsoft Fabric migration
Classify every Synapse workload, test migration-tool coverage, prove a production-shaped pilot, reconcile parity, and execute reversible migration waves.
Microsoft Fabric Data Agent implementation
Ground conversational agents in governed semantic, SQL, and KQL sources; enforce user permissions and prove answer quality with deterministic evaluation.
Microsoft Fabric IQ Ontology implementation
Turn one business domain into governed entities, relationships, source bindings, and measurable ontology grounding for enterprise agents.
Microsoft Fabric Operations Agent implementation
Convert one operational signal into a tested playbook, safe recommendation or action, Teams approval, audit evidence, and measured response improvement.
OneLake security and AI agent access assessment
Prove effective access across workspace and OneLake roles, RLS, CLS, SQL identity modes, Spark, Direct Lake, shortcuts, and Data Agents.
Microsoft Purview governance for Fabric AI agents
Validate sensitive grounding data, interaction controls, audit evidence, risk monitoring, retention, eDiscovery, licensing, and incident response.
Fabric AI agent observability and cost governance
Connect Data Agent, Operations Agent, Copilot, generated-query, storage, and action consumption to quality, unit economics, SLOs, and capacity risk.
Fabric Data Agent CI/CD and lifecycle governance
Control Git definitions, draft and published stages, source rebinding, dev/test/prod promotion, evaluation gates, drift, and rollback.
Fabric Data Agent production incident and rollback support
Contain unreliable answers, isolate routing, query, identity, policy, publishing, integration, and capacity failures, then restore a tested service path.
Fabric Data Agent MCP server implementation
Expose governed OneLake knowledge to approved AI clients with tested identity, permissions, data boundaries, tool routing, answer quality, and operating controls.
Fabric Data Agent service principal custom application integration
Give custom applications and background services governed Fabric answers through a least-privilege service principal, resilient MCP adapter, and production quality controls.
Fabric Data Agent multi-agent orchestration assessment
Partition specialist data domains, route intent, preserve identity, synthesize attributable answers, isolate actions, and recover individual agent routes.
Fabric Data Agent standard and preview runtime evaluation
Prove Advanced NL2SQL gains, catch query and answer regressions, and control runtime republishing, monitoring, and rollback.
Fabric Data Agent SQL source and NL2SQL assessment
Tighten schema scope, join and date rules, categorical values, few-shot examples, generated SQL, deterministic results, security, and regression gates.
Fabric Data Agent example query retrieval assessment
Validate question-query pairs, Clarity, Relatedness, Mapping, schema execution, run-step retrieval, collision risk, generated SQL or KQL, security, and lifecycle.
Fabric Data Agent multilingual rollout assessment
Define the English-only support boundary and validate any translation layer across terminology, intent, generated queries, values, locale rules, security, disclosure, and rollback.
Fabric Data Agent instruction conflict assessment
Place routing, query, semantic, policy, and response rules in the configuration layer that can use them, then test draft and published behavior.
Fabric Operations Agent identity and action security
Validate creator permissions, Teams approvers, parameter controls, downstream execution, expiry, identity lifecycle, evidence, containment, and recovery.
Fabric Operations Agent rule and duplicate alert assessment
Reconcile generated queries, source and time semantics, state and transition conditions, replay, false positives, missed events, duplicate messages, and monitoring.
Fabric Operations Agent remote MCP security
Separate query and configuration access, govern OAuth identities and write-capable tools, test source and action changes, and establish audited recovery controls.
Fabric Operations Agent and Fabric IQ Ontology
Validate ontology entities, properties, relationships, live bindings, graph freshness, generated rules, source permissions, action parameters, and monitoring evidence.
Fabric Operations Agent REST API and CI/CD
Version public definitions, rebind environment resources, handle delegated identity and long-running updates, deploy inactive, run behavioral gates, and prove rollback.
Fabric Operations Agent production troubleshooting
Contain unsafe automation and reconcile source, query, rule, operation, Teams, identity, approval, action, capacity, change, recovery, and reactivation evidence.
Fabric pipeline long-running and failed-run monitoring
Use workspace Eventhouse logs, deterministic alerts, Operations Agent context, Teams escalation, replay, capacity checks, and NOC ownership for critical pipeline runs.
Fabric Data Agent Eventhouse KQL assessment
Prove event-time windows, entity state, selected KQL schema, functions, examples, generated queries, user permissions, capacity, and answer fidelity.
Fabric Data Agent Graph and NL2GQL assessment
Prove node and edge semantics, path direction and modes, source instructions, example GQL, generated traversals, refresh, permissions, capacity, and answer evidence.
Fabric Data Agent Azure AI Search RAG assessment
Prove document authority, index and chunk design, retrieval relevance, citations, user access, source routing, answer groundedness, freshness, and failure behavior.
Fabric Data Agent Build agent with AI review
Turn schema and query-history suggestions into reviewed instructions, validated few-shots, measured query and answer regressions, controlled releases, and rollback evidence.
Fabric Data Agent mixed-source routing assessment
Prove source authority, configuration boundaries, route selection, tool output, combined evidence, effective access, runtime changes, and route-level rollback.
Fabric Data Agent Power BI NL2DAX assessment
Test semantic model metadata, Prep for AI, verified answers, generated DAX, business correctness, RLS and CLS, performance, release, and rollback.
Fabric Data Agent Verified Answers assessment
Prove trigger precision and recall, filter behavior, visual and DAX grounding, conflicts, model dependencies, consumer security, cross-experience behavior, and rollback.
Fabric Data Agent automated evaluation engineering
Version ground truth, automate SDK runs, calibrate critics, inspect step evidence, compare sandbox and production, and block unsafe regressions.
Fabric Data Agent Code Interpreter assessment
Prove source and input completeness, generated Python, numeric and visual correctness, effective access, sandbox governance, latency, and release safety.
Fabric Data Agent native visual response assessment
Test source queries, 200-row truncation, stable ordering, chart selection, labels, permissions, accessibility, client compatibility, release, and rollback.
Fabric Data Agent context drift assessment
Prove 25-by-25 output boundaries, multi-turn reference resolution, new-chat behavior, history persistence, effective permissions, query fidelity, and regression safety.
Fabric Data Agent cross-region deployment assessment
Align agent and source capacities, tenant settings, AI processing and storage boundaries, client data flows, capacity, migration controls, validation, and rollback.
Microsoft Foundry and Fabric Data Agent integration
Preserve user permissions across Foundry orchestration, Fabric source routing, generated queries, answer synthesis, tracing, evaluation, and production support.
Microsoft Foundry AgentOps managed support
Run tracing, evaluation, retrieval, tools, MCP, identity, incident response, controlled releases, telemetry security, and cost as one service.
Claude Managed Agents production support
Operate persistent sessions, event streams, MCP and tools, cloud or self-hosted sandboxes, credentials, incidents, releases, cost, and beta risk.
OpenAI Agents SDK production support
Operate application runtimes, traces, sessions, tools and MCP, handoffs, guardrails, approvals, incidents, releases, and cost.
Vertex AI Agent Engine managed support
Operate runtime metrics, quality, sessions, memory, IAM, private networking, tools, incidents, releases, quotas, and cost.
Amazon Bedrock AgentCore managed support
Operate runtime sessions, traces, evaluations, identities, gateways, tools, memory, policy, incidents, releases, quotas, and cost.
Salesforce Agentforce managed support
Operate sessions, topics, actions, flows, Apex, permissions, Data 360, incidents, controlled releases, quality, and consumption.
ServiceNow AI Agent managed support
Operate agentic workflows, execution plans, agents, tools, ACLs, identities, analytics, incidents, releases, and Assist consumption.
Oracle AI Agent Studio managed support
Operate sessions, evaluation, agent teams, tools, Fusion roles, OAuth integrations, incidents, quarterly releases, and outcomes.
SAP Joule agent managed support
Operate traces, tools, approvals, BTP environments, destinations, transport, deployment drift, incidents, releases, and consumption.
IBM watsonx Orchestrate managed support
Operate messages, traces, tools, workflows, knowledge, connections, credentials, channels, incidents, versions, and outcomes.
Databricks Mosaic AI Agent Framework managed support
Operate MLflow traces, evaluation, Model Serving, governed retrieval and tools, Unity Catalog identity, incidents, releases, and cost.
Snowflake Cortex Agents managed support
Operate request traces, evaluations, Analyst and Search tools, semantic data, custom actions, default-role access, incidents, releases, and cost.
LangGraph production support and LangSmith AgentOps
Operate API and queue workers, durable threads and checkpoints, Postgres, Redis, tracing, evaluation, tool actions, incidents, and releases.
CrewAI production support and AMP managed services
Operate crews and flows, state, triggers, memory, tools, API and worker workloads, external PostgreSQL and storage, incidents, releases, and cost.
LlamaIndex and LlamaCloud production support
Operate document sources, parsing, index synchronization, embeddings, vector stores, hybrid retrieval, tenant filters, incidents, releases, and cost.
Pinecone production support and managed services
Operate index and namespace design, ingestion freshness, tenant isolation, retrieval performance, Dedicated Read Nodes, monitoring, backups, incidents, and cost.
Weaviate production support and managed services
Operate collections, asynchronous indexing, shard and replica consistency, tenant lifecycle, retrieval performance, monitoring, backups, and cost.
Qdrant production support and managed services
Operate collections, shards, replicas, consistency and ordering, tenant routing, optimizer pressure, monitoring, backups, incidents, and cost.
Milvus and Zilliz Cloud production support
Operate ingestion freshness, segments, indexes, collection loading, QueryNode replicas, resource groups, tenant isolation, monitoring, backups, and cost.
PostgreSQL pgvector production support
Operate vector schemas, HNSW and IVFFlat recall, filtered queries, planner behavior, vacuum and reindex, replication, restore, incidents, and cost.
Azure AI Search production support
Operate source ingestion, indexers, skillsets, vector and hybrid retrieval, semantic ranking, security, capacity, releases, resilience, and cost.
Elasticsearch vector search production support
Operate ingest pipelines, mappings, aliases, shard health, vectors and inference, hybrid relevance, security, snapshots, upgrades, and cost.
Amazon OpenSearch Service production support
Operate provisioned domains and Serverless collections, ingestion, k-NN relevance, shards or OCUs, IAM and VPC, monitoring, snapshots, and cost.
MongoDB Atlas Vector Search production support
Operate collection-to-index freshness, mappings, ANN and ENN recall, Search Nodes, tenant filters, private networking, recovery, and cost.
Redis vector search production support
Operate source keys, Search indexes and aliases, exact and approximate recall, filters, shards, memory, persistence, restore, and cost.
Vertex AI Vector Search production support
Operate data updates, ScaNN recall, filters, index and endpoint releases, shards, replicas, private connectivity, quotas, and cost.
Azure Cosmos DB vector search production support
Operate source items, partition and tenant design, DiskANN recall, indexing policies, RU/s, 429s, consistency, failover, restore, and cost.
Amazon Bedrock Knowledge Bases production support
Operate source sync, document ingestion, chunking, embeddings, vector-store state, retrieval, citations, security, incidents, and cost.
Vertex AI RAG Engine production support
Operate corpora, file imports, chunking, embeddings, managed or external vector stores, retrieval, reranking, grounded answers, security, quotas, and cost.
Amazon Kendra production support
Operate repository connectors, document sync and deletion, enrichment, ACLs, Query and Retrieve relevance, capacity, monitoring, incidents, and cost.
Microsoft 365 Copilot connector production support
Operate source crawls, external items, schema, ACL and identity mapping, indexed content, Copilot discovery, throttling, incidents, rollout, and governance.
Atlassian Rovo production support
Operate connected knowledge, permission and deletion sync, Search and Chat outcomes, agent scope, tool actions, MCP access, incidents, and governance.
Glean enterprise search and agents production support
Operate datasource crawl and index coverage, permission synchronization, search relevance, Assistant answers, agent actions, background runs, and governance.
Coveo Relevance Cloud production support
Operate sources, item and permission freshness, security identities, query pipelines, ML relevance, generative answers, performance, incidents, and usage.
Algolia AI Search production support
Operate source-to-index tasks, atomic releases, replicas, settings, NeuralSearch relevance, analytics events, key security, rate limits, and cost.
Salesforce Data Cloud vector search and Agentforce RAG support
Operate data streams, DLO and DMO mappings, chunks, embeddings, vector and hybrid indexes, retrievers, citations, permissions, quality, and credits.
ServiceNow AI Search and Now Assist production support
Operate source indexing, search profiles and applications, relevance, Genius Results, external permissions, grounded answers, analytics, incidents, and releases.
SAP Joule document grounding production support
Operate repository scope, pipeline ingestion, schedules, document limits, chunking, metadata, access, answer quality, AI Units, incidents, and releases.
Microsoft 365 Copilot declarative agent support
Operate SharePoint and connector knowledge, manifest scope, permission trimming, licenses, context limits, citations, incidents, releases, and governance.
Box AI Studio agent production support
Operate files and Hubs, permissions, agent instructions, API completeness, extraction confidence, metadata writes, integrations, AI Units, and releases.
Slack enterprise search and AI production support
Operate built-in and custom sources, user account connections, OAuth, workspace grants, permission-aware retrieval, citations, incidents, and releases.
Dropbox Dash enterprise search production support
Operate connector scope, OAuth and consent, content and permission sync, searchable types, extraction limits, AI answers, audit, incidents, and releases.
Copilot Studio and Fabric Data Agent integration
Prove connected-agent authentication, source permissions, generative orchestration, Teams or website channel behavior, answer quality, and policy.
Copilot Studio production support
Operate session quality, knowledge, tools, triggers, identities, data policies, releases, incidents, Copilot Credits, and client-facing service evidence.
Microsoft 365 Copilot Fabric Data Agent rollout
Move governed Fabric answers into Agent Store and Teams with proven discovery, user access, response fidelity, visualization, support, and adoption.
Data quality root cause and remediation
Turn failed quality checks into evidence-backed diagnosis, impact analysis, reversible containment, and independently validated recovery.
Data contract change impact assessment
Find affected pipelines, reports, APIs, models, exports, and customers before a schema or contract change is released.
Customer deduplication and merge review
Combine explainable entity matching, false-merge controls, survivorship, human approval, downstream reconciliation, and rollback.
Warehouse access review and recertification
Give data owners effective-access, usage, sensitivity, purpose, and ownership evidence before retain, reduce, or revoke decisions.
Retention and deletion evidence automation
Turn approved policies and requests into scoped actions, hold handling, platform-aware execution, downstream evidence, and verified closure.
Privileged database activity investigation
Turn audit streams into context-rich cases with identity attribution, sensitive-object risk, change evidence, and controlled response.
Database patch risk and validation
Prepare patch windows with deterministic prechecks, dependency evidence, baselines, rollback controls, and post-change service validation.
Database failover readiness and DR drills
Validate role transition, DNS, client recovery, data integrity, application transactions, RPO, RTO, fencing, and failback end to end.
Connection pool exhaustion and saturation incidents
Correlate pool acquisition, proxy waiting, database sessions, long transactions, locks, retries, capacity, and customer impact.
Database deadlock and blocking root cause
Turn native deadlock graphs and blocking chains into grouped patterns, safe response, validated fixes, and recurrence evidence.
Query plan regression detection and rollback
Detect material plan changes with representative runtime evidence, controlled containment, automatic unforce conditions, and permanent remediation.
Database statistics drift and maintenance validation
Prioritize targeted statistics work from distribution, sample, estimate, plan, workload, maintenance, and post-change evidence.
Index bloat and maintenance prioritization
Replace fixed rebuild schedules with engine-aware condition, workload impact, execution risk, cost, and outcome evidence.
Database storage growth and incident forecasting
Forecast capacity limits across data, logs, temp, backups, and replicas, then route evidence-backed scale or remediation before risk becomes an incident.
Replication lag root cause and failover risk
Locate transport and apply bottlenecks, quantify stale-read and recovery exposure, and validate controlled remediation.
Transaction log and WAL growth incidents
Find the engine-native reuse blocker, protect availability, preserve recovery, and validate durable remediation without unsafe purge or shrink actions.
Schema migration lock risk and deployment validation
Resolve exact DDL against engine behavior, production concurrency, dependencies, resources, compatibility, rollback, and measurable deployment gates.
Database configuration drift and performance risk
Find which settings differ across desired, persisted, runtime, pending, and fleet states, then validate controlled correction against service outcomes.
Database certificate expiry and rotation validation
Inventory server and CA certificates, client trust, verification modes, connection paths, restart risk, rehearsal, rollback, and post-rotation evidence.
Database credential rotation and connection validation
Coordinate account, secret version, consumer refresh, connection-pool renewal, job testing, rollback, old-access revocation, and application proof.
Database major-version compatibility and cutover
Move beyond vendor prechecks with extension, SQL, driver, topology, workload, performance, downtime, rollback, and production transaction evidence.
Cloud database sizing, cost, and performance validation
Profile representative demand, compare target architectures and total-cost scenarios, then validate the leading size with production-relevant workload.
Database consolidation candidate and workload isolation assessment
Find which workloads can safely share capacity using correlated peaks, platform compatibility, recovery, security, licensing, and concurrent tests.
Database licensing and edition optimization assessment
Build reviewable deployment, feature, core, edition, cloud benefit, workload, cost, and target evidence while authorized owners interpret rights.
Cloud database cost allocation and chargeback
Join provider billing, resource identity, database usage, shared cost pools, versioned rules, reconciliation, showback, and chargeback evidence.
Database backup retention and snapshot cost optimization
Map every retained copy to recovery purpose, owner, chain, policy, restore evidence, legal controls, cost, approval, and verified outcome.
Database data transfer and cross-region replication cost
Reconcile regional topology, replication and application flows, egress, lag, RPO, RTO, routing, failover capacity, and tested cost outcomes.
Database reserved capacity and commitment utilization
Reconcile eligible usage, utilization, coverage, expiry, stable workload, architecture roadmaps, commercial scenarios, and authorized renewal decisions.
Idle nonproduction database cost optimization
Classify development and test demand, implement guarded schedules, manage exceptions, verify restore, and retire expired environments without hidden dependencies.
Database compute rightsizing and risk validation
Compare target limits, replay representative workload, validate maintenance and failover, reconcile commitments, and control production change and rollback.
Serverless database capacity and auto-pause optimization
Balance minimum and maximum capacity, scale-up speed, pause and resume, background wake-ups, readers, failover, SLOs, and effective billing.
Database cloud cost forecast and budget variance
Reconcile actuals, model technical cost drivers, incorporate plans and commitments, quantify uncertainty, and route explainable variance to accountable owners.
Database storage tier, IOPS, and throughput optimization
Separate capacity from performance, validate latency and queueing, test backup and recovery, price the complete topology, and control production changes.
Database monitoring and telemetry cost optimization
Trace metrics, logs, plans, alerts, retention, exports, privacy, incidents, stores, and billing; test lower-cost settings without losing operational evidence.
Managed database HA topology cost optimization
Connect every standby, readable replica, zone, tier, and proxy to funded failure modes, degraded capacity, application failover, RPO, RTO, and realized cost.
Managed database read replica utilization and cost
Trace every paid replica to real endpoints, clients, query classes, consistency limits, peak demand, workload isolation, promotion or DR value, and realized billing.
Database audit logging cost and compliance
Connect every audit event and retained copy to a control, investigation, sensitive-data boundary, integrity test, retrieval objective, performance result, and realized invoice.
Managed database extended support cost planning
Connect engine deadlines, paid-support year tiers, vCPU and topology exposure, compatibility blockers, delivery capacity, exceptions, upgrade milestones, and realized invoices.
Managed database proxy and pooling optimization
Measure client-to-backend reuse, pinning, borrow waits, session correctness, failover recovery, database headroom, endpoint cost, edition premium, and realized billing.
Written scoping
Describe the operating gap, what is at risk, and the responsibility you need covered.
A senior lead will review the environment, urgency, ownership, workload, access constraints, and expected outcome, then respond with qualifying questions or a recommended starting shape.