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Showing 20 results · Page 10 for “Microsoft”. More results are available below.
DP-420 · SQL querying
SQL joins determine which rows are combined, filters determine which remain, and aggregation summarizes the result. Confirm the intended grain before calculating a total. Joining one parent …
DP-600 · Data governance
Data governance defines who is accountable for data meaning, quality, access and retention. A catalog can describe datasets and lineage, but decisions still need responsible owners. Establis…
DP-600 · Microsoft Fabric analytics
…e ingestion, storage, transformation and reporting. In Microsoft Fabric, identify which item owns each stage and how data reaches downstream consumers. A refreshed report can still show stal…
DP-600 · Power BI data modeling
A star schema separates measurable events in fact tables from descriptive dimensions such as date and product. Relationships carry filter context into calculations. Define the grain of each …
DP-700 · Data pipeline design
A data pipeline needs defined inputs, transformations, outputs and checkpoints. Failures can leave partial results, so decide how processing resumes without losing or duplicating records. Tr…
DP-700 · Data quality
A value can have the right data type and still be wrong for the business. Data quality checks should cover required values, uniqueness, valid ranges and relationships, along with freshness a…
DP-700 · Microsoft Fabric analytics
…e ingestion, storage, transformation and reporting. In Microsoft Fabric, identify which item owns each stage and how data reaches downstream consumers. A refreshed report can still show stal…
DP-750 · Data pipeline design
A data pipeline needs defined inputs, transformations, outputs and checkpoints. Failures can leave partial results, so decide how processing resumes without losing or duplicating records. Tr…
DP-750 · Databricks lakehouse concepts
A lakehouse workflow can separate raw ingestion from validated and business-ready datasets. Each layer should have a clear contract rather than merely a different folder name. Preserve enoug…
DP-750 · Machine-learning engineering
Data leakage occurs when training or model selection uses information that would not be available at prediction time. Split data in a way that respects time and related entities, and fit lea…
DP-750 · Responsible AI evaluation
Aggregate accuracy can hide poor performance for particular users or situations. Evaluate representative subgroups and realistic failure cases, and consider privacy, misuse and human oversig…
DP-800 · Data modeling
A data model expresses entities, identifiers and relationships. Design it around the operations that must remain correct and the questions that need efficient answers. Normalization can redu…
DP-800 · Database administration
Database administration balances availability, integrity, performance and recovery. Investigate workload evidence before changing indexes or resource limits, and understand the impact on wri…
DP-800 · Identity and access
Authentication establishes who or what is requesting access. Authorization decides which actions that identity may perform on a resource. A successful sign-in therefore does not imply permis…
DP-800 · SQL querying
SQL joins determine which rows are combined, filters determine which remain, and aggregation summarizes the result. Confirm the intended grain before calculating a total. Joining one parent …
DP-900 · Describe core data concepts
Structured data has a fixed schema of rows and columns, like a relational table or a CSV with consistent headers. Semi-structured data carries its own tags but the shape can vary between rec…
DP-900 · Describe core data concepts
Transactional systems (OLTP) handle large numbers of small, fast operations such as placing an order or updating a balance. They are normalised, enforce ACID properties and are optimised for…
DP-900 · Describe core data concepts
Transactional databases guarantee four properties. Atomicity means a transaction is all or nothing; a failed money transfer leaves both accounts untouched. Consistency means every transactio…
DP-900 · Describe core data concepts
Batch processing collects data over a period and processes it in one run, such as a nightly load of the day's sales files. It is efficient for large volumes and complex transformations but r…
DP-900 · Describe core data concepts
DP-900 expects you to distinguish three roles. The database administrator installs, configures, secures, backs up and tunes databases and is accountable for availability and recovery. The da…
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