Search the practice set
275 questions, 991 terms and 600 topics in 30 areas.
60 results for “Data Platform Tenancy”
Compute Isolation Boundary
The line across which one domain's analytical workload cannot affect another's performance, cost attribution or access.
Data Mesh
An organisational approach that gives domain teams ownership of their analytical data as a product, with a self-serve platform and federated governance.
Namespace Tenancy
Isolating teams within a shared cluster by namespace plus quota plus network policy, and being explicit about what that does not isolate.
Salesforce's Metadata-Driven Multi-Tenancy
Salesforce serves every customer from shared infrastructure with a single physical schema, storing customer-specific data structures as metadata rather than as separate tables.
Analytical Estate Topology
The full picture of where analytical data lands, is transformed and is served, including the paths that bypass the intended one.
Booking.com's Experimentation Platform
Booking.com runs over a thousand concurrent experiments and treats the ability to test any change safely as a platform capability rather than a product feature.
Capital One's Data Centre Exit
A major US bank closed all eight of its data centres and moved fully to public cloud, treating governance automation as the enabling technology rather than a constraint.
Change Data Capture
Publishing a stream of a database's row-level changes by reading its replication log, without modifying the application that owns it.
Control Plane and Data Plane
The separation between the machinery that makes changes to a system and the machinery that serves its traffic.
A business sponsor asks for a real-time data platform because "the competition has one". Reporting is currently a nightly batch that lands at 06:00 and nobody has complained. How do you handle this?
Do not answer the technology question "Real time platform" is a solution, and it has arrived without a problem attached. Answering it directly leads either to a
A new platform must serve a public partner API, three internal front-ends with different data needs, and high-volume service-to-service traffic. Choose the API styles and defend the choice.
Resist "pick one" These are three different problems with three different consumers. Standardising on one style optimises for architectural tidiness at the expe
A regulated client requires that no traffic between their data centre and your SaaS platform traverses the public internet. Design the connectivity and justify the cost.
Two distinct requirements hiding in one sentence Traffic must not traverse the public internet — a routing requirement. The client must be able to demonstrate i
You are asked to choose between a cloud data warehouse and a lakehouse for a new analytics platform. How do you decide?
What actually differs The gap has narrowed considerably, so the decision turns on fewer things than the marketing suggests. Format ownership. In a lakehouse, da
A CDO proposes moving to a data mesh because the central data team is a bottleneck with a nine-month backlog. How do you assess the proposal?
Agree with the diagnosis, examine the prescription The bottleneck is real and it is structural rather than a matter of capacity. A central team receives data fr
Leadership wants to consolidate a warehouse, a data lake and three departmental marts into a lakehouse. How do you scope and sequence this?
Establish the actual driver "Consolidate onto a lakehouse" is a solution. The driver is usually one of: cost of maintaining several copies, inconsistency betwee
A logic bug means six months of a derived table are wrong. You must reprocess without disrupting live consumers. How?
Establish the blast radius first Which downstream tables, reports and extracts consumed the wrong data, and did any of it leave the organisation — a regulatory
A multi-tenant SaaS product has outgrown one database. You must shard. How do you choose the partition key, and what makes this decision so expensive to get wrong?
What the interviewer is testing Whether you exhaust cheaper options first, and whether you understand that a shard key is close to irreversible. First: do not s
A team is choosing between Iceberg, Delta and Hudi for a new lakehouse. How would you approach the decision?
The formats are more alike than the debate suggests All three provide the same core: atomic commits over object storage, snapshots and time travel, schema evolu
A transformation project has grown to 600 models with chains twelve deep. A change at the base has an unknowable blast radius. What do you do?
Treat it as a software architecture problem, because it is one Six hundred models with twelve deep chains is a codebase with no module boundaries. The remedies
A warehouse table now feeds the CRM through reverse ETL. It breaks, and the analytics team and the CRM team each say it is the other's problem. How do you resolve it?
The dispute is a design gap, not a personality problem A warehouse table built for analysis — nightly latency, best effort availability, schema changes made by
A GDPR erasure request arrives for a customer. Where does their data actually live, and what makes this expensive to retrofit?
Where the data lives Longer than people expect, and enumerating it is most of the work: Primary database · read replicas · caches · search indexes · analytical
A design review presents a new event-driven platform. What cost questions do you ask before approving it?
What the interviewer is testing Whether cost is part of your architecture review or an afterthought handled by finance later, and whether you know the specific
A platform of 40 services has logs only, and incidents take hours to diagnose. Design the observability strategy and its rollout order.
Why logs alone fail at this size Logs answer "what happened in this service". They cannot answer "where did this request spend its time across twelve services",
A platform team proposes adopting a service mesh for 40 services. Make the case for and against, then decide.
What it genuinely provides mTLS everywhere, with automated certificate rotation. This is usually the deciding factor. Doing mTLS by hand means short lived certi
A query that ran in 50ms for two years now takes 90 seconds. Nothing was deployed and the data volume grew normally. What happened?
The most likely cause: a plan flip The optimiser's choice is a function of estimated row counts. As the data grows or its distribution shifts, an estimate cross
A regulator asks whether customer data is encrypted. The team says yes, disks are encrypted. Is that a sufficient answer?
What disk encryption actually protects against Someone obtaining the physical medium or a raw storage snapshot. In a cloud context that means a provider employe
A single deploy took down your monitoring platform. What happened, and how do you prevent a recurrence?
What almost certainly happened A high cardinality label was added to a metric. Each unique combination of label values is a separate time series, and cost scale
A vendor claims their streaming platform provides exactly-once processing. How do you evaluate the claim?
Ask where the guarantee ends Nearly always at the platform's boundary. Within it, state and offsets commit together, so internal state reflects each input once.
An AI feature launched two months ago now costs more per month than the rest of the platform. What do you investigate?
Get cost per request, decomposed Token cost splits into input and output, and they price differently. Break the bill down by feature, by user, and by input vers
An e-commerce platform stores card numbers to support repeat purchases. How do you reduce PCI scope?
Stop the card number reaching your systems at all The strongest reduction is not storing cards more safely; it is never receiving them. A hosted field or an ifr
Application teams say the platform is unreliable. The platform team's dashboard shows 99.95% on every component. How do you resolve this?
Both are right, and that is the finding The platform measured its components. Consumers experience journeys. The gap between those two views is where trust erod
Choose storage for four workloads: a Postgres data directory, user-uploaded images, a shared build cache, and seven years of audit records.
Postgres data directory — block storage It needs low latency random reads and writes and a filesystem, and it attaches to one instance. That is precisely block
Data Platform Tenancy
Multiple domains on shared storage and compute, with separable access and cost.
Data Platform Architecture
General material on designing the analytical data estate end to end.
Platform Tenancy
Isolating teams sharing a cluster, account or pipeline fleet, and where isolation must be hard.
Data Mesh
Domain ownership, data as a product, self-serve platform, and federated governance.
Data Vault Modelling
Hubs, links and satellites, and the auditability and load parallelism they buy.
Data Virtualisation
Querying across sources without moving data, and the performance ceiling that imposes.
Analytics Cost Control
Scanned bytes, idle warehouses, and the query nobody knew was running hourly.
Batch Orchestration
DAGs, dependencies, retries, and the difference between a schedule and an orchestration.
CDC Pipeline Design
Building on a change stream: snapshot plus delta, tombstones, and merge into the target.
Dimensional Modelling
Facts, dimensions, grain, and the star schema's continued relevance.
File Formats & Compaction
Columnar formats, the small-file problem, and the maintenance nobody schedules.
Ingestion Patterns
Full load, incremental, append-only and merge, and the source system each one suits.
Medallion Architecture
Bronze, silver and gold layers, and what each layer is allowed to guarantee.
Open Table Formats
Iceberg, Delta and Hudi — transactions, snapshots and time travel over object storage.
Reverse ETL
Pushing modelled analytical data back into operational systems, and who owns it then.
Slowly Changing Dimensions
Overwriting, versioning or timestamping attribute history, and the reporting each enables.
Storage Layout & Partitioning
Partition keys, clustering, and the scan the query planner is left able to skip.
Transformation Frameworks
Declarative SQL transformation with tests, lineage and versioned models.
Warehouse Migration
Moving off a legacy warehouse with thousands of reports pointed at it.
Warehouse, Lake & Lakehouse
Three answers to where analytical data lives, and the workloads that separate them.
Workflow Schedulers
Airflow, Dagster and their kin — where the control plane sits and what it can recover.
Workload Isolation
Keeping an analyst's query off the pipeline's compute, and both off the dashboard's.
Change Data Capture
Turning a database's replication log into a stream, and its coupling risk.
Client Caching & Data Layer
Stale-while-revalidate, invalidation and optimistic updates on the client.