Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

DP600 > DP-600 Part 1 > Flashcards

DP-600 Part 1 Flashcards

1
Q

How to use on-premise data gateway

A
  1. Install the data gateway on the on-premise server
  2. In Fabric, create a new on-premise data gateway connection
  3. Use the gateway in a dataflow or data pipeline to get data into Fabric
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Fabric Admin Portal - Tenant Settings

A
  • Allows users to create fabric items
  • Allows users to create workspace
  • Whole host of security features
  • Allow service principal access to Fabric APIs
  • Allow Git integration
  • Allow Copilot
    Some settings can be enabled for entire organization, specific security groups, all except for certain security groups. Other settings are either enabled or disabled
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Fabric Admin portal - Capacity Settings

A
  • Create new capacities
  • Delete capacities
  • Management capacity permissions
  • Change the size of the capacity
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Where to increase the SKU of the capacity

A

Go to Admin portal > Capacity settings and click through to Azure to update your capacity

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Structure of a Fabric implementation and where admin happens

A
  1. Tenant: Fabric Admin Portal (Tenant Settings)
  2. Capacity: Azure Portal and Fabric Admin Portal (Capacity Settings)
  3. Workspace: Workspace settings (in the workspace)
  4. Item level: data warehouse, lakehouse, semantic model
  5. Object level: dbo.customer, VW.MySQL View
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Capacity adminstration tasks in Fabric capacity settings

A
  1. Enabled disaster recovery
  2. View capacity usage report
  3. Define who can create workspaces
  4. Define who is a capacity administrator workspace creation permissions
  5. Update Power BI connection settings from/to this capacity
  6. Permit workspace admins to size their own custom Spark tools based on workspace compute requirements
  7. Assign workspaces to the Capacity
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Workspace administrator settings

A
  1. Edit license for the workspace (Pro, PPU, Fabric, Trial,etc.)
  2. Configure Azure connections
  3. Configure Azure DevOps connection (Git)
  4. Setup workspace identity
  5. Power BI settings
  6. Spark settings
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What is xmla endpoint

A

The XMLA endpoint is essentially a gateway that lets external tools communicate with the data stored in Microsoft Fabric. This feature is particularly useful for those who need more control or prefer working with tools they are already comfortable with, like SSMS or Excel.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Difference XMLA with Fabric loading options like mirroring, copy data acitivity, etc.

A

XMLA: ETL (transform data using tools you’re familiar with outside of Microsoft Fabric and then load it into the lakehouse)

Others: ELT
load raw data into Fabric and then transform it using tools within the platform

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Dataflow vs Data Pipeline

A
  • Dataflows are for straightforward ETL processes and data preparation, with a focus on user-friendly transformation of data for analytics.
  • Data Pipelines are for more complex orchestration and management of data workflows, handling multiple steps and dependencies, often in an ELT scenario. They are more suited for technical users who need to automate and manage comprehensive data workflows.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Shortcut vs mirroring in Fabric

A

Shortcut: reference to a dataset that exists in OneLake

Mirroring: process that creates a replicated copy of data in OneLake. Useful when you need a local copy of data for performance reasons, redundancy, or to ensure that your operations are not impacted by the availability or performance of the original data source.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is Azure Blob Storage

A

cloud-based storage service provided by Microsoft Azure, designed to store large amounts of unstructured data. “Blob” stands for Binary Large Object and refers to data types like images, videos, documents, and other types of unstructured data.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What determines the number of capacities required

A
  • Compliance with data residency regulations (e.g. maybe if the data must be located in the EU, then another data must be in the US, then you must separate the capacity)
  • Billing preference within the organization
  • Segregating by workload type (i.e. Data Engineering, Business Intelligence )
  • Segregating by department
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What determines the required sizing of a capacity

A
  • Intensity of expected workloads (high volume of data ingestion)
  • Heavy data transformation (i.e. Spark)
  • The higher the SKU, the more expensive (budget)
  • Can you afford to wait?
  • Access to F64+ features or not? >F64: co-pilot
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Options of data ingestion

A
  • shortcut: ADLS Gen 2, Amazon S3, Google Cloud Storage or dataverse
  • database mirroring: Azure SQL, Azure Cosmos DB, Snowflake
  • ETL - dataflow: On-premise SQL
  • ETL - data pipeline: On-premise SQL
  • ETL - notebook
  • Eventstream: real-time events
    Other: ETL by dataflow, data pipeline or notebook
    *above shows the preferred options and possibilities that are open
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Data Ingestion requirement

A

Location of the data
- On-premise data gateway: if data is living in on-premise sql
- Vnet Data gateway: if data is living in azure virtual network or private endpoint
- Fast copy

Volume of the data
- low (megabytes per day):
- medium (gigabytes per day): fast copy and staging
- high (many GB or terabytes per day): fast copy and staging

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Difference between Virtual network data gateway and On-premises data gateway

A

Virtual network data gateway: used when all your data is stored within Azure Virtual Network (VNet). Enables secure connections between Azure services (like Power BI) and data sources that are inside an Azure VNet.

On-Premises data gateway: data is stored outside of Azure like on your local network or in another cloud provider’s environment (AWS, Google Cloud), if you have direct network connectivity like VPN or ExpressRoute to these environment. Enables secure connections between cloud services (like power BI) and data sources that are not within azure

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Data Storage Options

A
  • Lakehouse
  • Warehouse
  • KQL database
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Deciding factors for data storage

A

Data type:
- Lakehouse: structured, semi-structured and or unstrcutred
- Relational /strctured: lakehouse or warehouse
- Real-time/streaming - KQL data warehouse

Skills exist in the team:
- T-SQL: data warehouse
- Spark: lakehouse
- KQL: KQL database

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

The admin portal can only be accessed by

A

Someone with a Fabric license and either a:
- Global admin
- Power platform admin
- Fabric admin

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Toby creates a new workspace with some Fabric items to be used by Data Analysts. Toby creates a new security group called Data analyst. He includes himself as a member of this security group. Toby gives the data analysts security a viewer role in the workspace. What workspace role does Toby have?

A

Admin. Since he is the creator of the workspace, his admin role supersedes the viewer role

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Toby wants to delegate some of the management responsibilites in the workspace. He wants to give this person the ability to share content within the workspace, invite new Contributors to the workspace but no add new Admins to the workspace. Which role should Toby give this person?

A

Member

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

You have admin role in a workspace. Sheila is a data engineer in your team. Currently she has no access to the workspace. Sheila needs to update a data transformation script in a PySpark notebook. The script gets data from a Lakehouse table, cleans it and then writes it to a rable in the same Lakehouse. You want to adhere to the principle of least privilege. What actions should you take to enable this?

A

Share the lakehouse data with ReadAll Spark Data permission and share the Notebook with Edit permission

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

You have admin role in a workspace. You want to pre-install some useful Python packages to be used across all notebooks in your workspace. How do you achieve this?

A

Create an environment, install the packages in the environment and then go to workspace settings > spark settings and set the default environment.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

About Domains

A

It is a way of logically grouping together all the data in an organization that is relevant to a particular area or field.

To group data into domains, workspaces are associated with domains!!! When a workspace is associated with a domain, all the items in the workspace are also associated with the domain and they receive a domain attribute as part of their metadata.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Domain Roles

A
  • Fabric admin (or higher): fabric admins can create and edit domains, specify domain admins and domain contributors, and associate workspaces with domains. Fabric admins see all the defined domains on the Domains tab in the admin portal and they can edit and delete domains
  • Domain admin: can only see and edit the donains they’re admins of
  • domain contributor: are workspace admins whom a domain or fabric admin has authorized to assign the workspaces they’re the admins of to a domain, or to change the current domain assignment.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

When you define a domain for specified users and/or security groups, the following happens

A
  1. The system scans the organization’s workspaces. When it finds a workspace whose admin is a specified user or member of a specified security group: if the workspace already has a domain assignment, it is preserved. The default domain doesn’t override the current assignment. If the workspace is unassigned, it is assigned to the default domain.
  2. After this, whenever a specified user or member of a specified security group creates a new workspace, it is assigned to the default domain.

The specified users and/or members of the specified security groups generally automatically become domain contributors of worskpaces that are assigned in this manner

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

Delta vs Parquet

A

Parquet: a way to store data in a very organized and efficient manner. Great for big data tools like Apache Spark and Hadoop because it helps save space and speeds up data retrieval. However once you write a parquet file, you cant change it. If you need to update it, you have to create a whole new file.

Delta file is the upgraded version of parquet. It allows you to make changes to your data without creating bew files every time. So if you need to update or depete something, you can do it easily. Handy for real-time applications

Relating to microsoft fabric:
- Using Parquet files: getting the benefits of efficient storage and fast queries
- Using Delta files: gain the ability to handle chanfes in your data more flexibly, which is great for applications that need to adapt quickly to new information.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

According to Spark Definition a Managed Table is a

A

table which is stored in the Fabric Tables section and data as well as metadata are managed by spark

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

Deployment rules can be implemented to change things like

A

The default lakehouse (for a notebook) at different stages

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

There are other ways to management deployment oter than the development, test/staging, production stages

A
  • managed through branching
  • managed through Azure DevOps Pipelines (YAML templates)
  • for semantic models, you can do it using the XMLA endpoint
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

In a Azure DevOps repo, the main branch is ‘protected’ (needs approval before any changes are merged into it). The repo contains one PBIP. You have to update the Title in the report, merging these changes to the Main branch, in which order should you carry out the following tasks to achieve this

A
  1. Clone the repository to your local machine
  2. Checkout a new feature branch from the MAIN branch
  3. Make the required changes to the report
  4. Commit and push the feature branch
  5. Open a pull request in Azure Repos
  6. Wait for approval, then merge into the main
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

You want to deploy a semantic model using the XMLA endpoint. where can you do to find the XMLA endpoint to set up a connection with a third-party tool?

A

Go to the workspace settings for the workspace you want to deploy your model to

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

Different types of power bi files

A
  • pbix: standard
  • pbit: template
  • pbip: track changes in Git for version control
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

What is the fabric capacity metrics app

A

Observe capacity utilisation trends to determine what processes are consuming CUs and whether any throttling is occurring

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q

What is DMV

A

Retrieves information about the current state of the data warehouse

34
Q

sys.dm_exec_connections

A

Returns info about data warehouse connections

35
Q

sys.dm_exec_sessions

A

Returns information about authenticated sessions

36
Q

sys.dm_exec_requests

A

Returns information about active requests and provide details about SQL commands running in the data warehouse

37
Q

Admin,member,viewer, contributor has permission which dmv and

A

Admin: all 3
Member,viewer,contributor: except sys.dm_exec_connection

38
Q

3 Query Insights Views:

A
  • queryinsights.exec_requests_history: details of each completed SQL query
  • queryinsights.long_running_queries: details of query execution time
  • queryinsighrs.frequently_run_queries: details of frequently run queries
39
Q

In Power Bl Desktop, you enable incremental refresh for the table and load only one week’s worth of data. You publish the semantic model to Workspace 1.
Due to the size of the semantic model, you need to bootstrap the initial full load.
What can you use to create the partitions in the Power BI service without processing them?

A

Use tabular editor to run apply refresh policy command on a table that has an incremental refresh policy defined in power bi desktop. This will create the partitions based on the policy but does not process them. This method is useful when working with very large datasets when the initial full load can take many hours

40
Q

You are developing a large Microsoft Power BI semantic model that will contain a fact table. The table will contain 400 million rows.
You plan to leverage user-defined aggregations to speed up the performance of the most frequently run queries.You need to confirm that the queries are mapped to aggregated data in the tables.
Which two tools should you use? Each correct answer presents part of the solution.

A

SQL Server Profiler and DAX Studio can detect whether queries were returned from the in-memory cache storage engine or pushed by DirectQuery to the data source

41
Q

You have Azure Databricks tables and a Fabric lakehouse.
You need to create a new Fabric artifact to combine data from both architectures. The solution must use data pipelines for the Azure Databricks data and shortcuts for the existing Fabric lakehouse.
What Fabric artifact should you create?

A

Only lakehouse can create shortcut to other lakehouses. Fabric data warehouse can use data pipeline but cannot use shortcuts!!!

42
Q

You have a Fabric workspace that contains a lakehouse named Lakehouse1.
You need to create a data pipeline and ingest data into Lakehousel by using the Copy data activity.
Which properties on the General tab are mandatory for the activity?

A

Name only

43
Q

You have a Fabric workspace that contains a set of Dataflow Gen2 queries.
You plan to use the native Dataflow Gen2 refresh scheduler to configure the queries to refresh as often as possible.
What is the fastest refresh interval that can be configured?

A

The native refresh scheduler for dataflows, just like semantic models, can be scheduled every 30 minutes.

44
Q

You have a Fabric warehouse named Warehouse 1.
You discover a SQL query that performs poorly, and you notice that table statistics are out of date.
You need to manually update the statistics to improve query performance for the table.
Which column statistics should you update?

A

When manually creating or updating statistics for optimising query performance, you should focus on columns used in JOIN ORDER BY and GROUO. Y clauses

45
Q

How can you bring data into fabric

A
  1. Data ingestion: Dataflow, data pipeline, notebook, eventstream
  2. Shortcuts: external (amazon s3, adls) and internal (lakehouse, warehouse, kql tables)
  3. Database mirroring: snowflaks,cosmosdb, azure sql
46
Q

Ingest data with a dataflow

A

Pros: now low code, perform ETL, access on-premise, get multiple datasets at once (but better to soace it out for data validation), can upload raw diles or static files

Cons: struggles with large datasets, difficult to implement data validation, cannot pass in external parameters

47
Q

Ingest data with a dataflow

A

Pros: now low code, perform ETL, access on-premise, get multiple datasets at once (but better to soace it out for data validation), can upload raw diles or static files

Cons: struggles with large datasets, difficult to implement data validation, cannot pass in external parameters

48
Q

Ingest data with data pipeline

A

Pros: able to ingest large datasets, import cloud data, wheb you need control flow logic, trigger wide variety of actions in fabric (and outside of fabric) like dataflows, notebooks, stored procs, kql scripts, webhooks, azure functions, azure ml, azure databricks

Cons: cannot do trasnform natively but can embed notebooks or dataflow, no ability to upload local files, does not work cross workspace currently

49
Q

Ingest data with notebook

A

Pros: extraction from APIs (using Python requests library or similar), to use client libraries, good code for reuse, for data validation and data quality testing of incoming data, fastest in terms of data ingestion (and most efficient for CU soend)

Cons: when you dint have a puthon caoabukuty in your organisation and when you want to write to a data warehouse

50
Q

What is monitoring hub used for

A

to track fabric items like semantic model

51
Q

What is the capacity metrics app used for

A

Compute: capacity units spend, time, overages and also breakdown by workspace and fabric item.

Storage: GB storage by workspace

52
Q

What is performance monitoring and which data ingestion is it used for?

A
  • Used for dataflows
  • Provides a high level summary of a dataflow run which is available in the monitoring hub
  • Lower-level data and specific understanding of a dataflow is available in the refresh history of a particular dataflow. (Inspect error messages and get a breakdown of the different sub-activities being performed by the dataflow)
53
Q

Performance Optimization / Features

A
  • Staging: when enabled it’s useful when you have huge data volume and require lots of transformation. Not useful for small dataset
  • Fast Copy: similar to data pipeline, used when struggling with performance
  • DMV: receive live SQL Query lifecycle insights
54
Q

Problem with delta tables and what are the ways to solve delta table problems

A

Context: Fabric is built on delta files. And while it is a great format as it updates the data into the same file. However, it can lead to poor performance and bloated storage size.

Solution: V-Order, Optimise, VACUUM,coalesce.repartition are some of the options to help reduce the problem with delta tables

55
Q

How do i get the summary of the file and how it is partitioned

A

%%sql
describe

56
Q

V-order purpose

A

reduce file size

  • if it’s enabled: spark.conf.get
  • to enable/disable:
    spark.conf.set(____,’false’/’true’)
57
Q

Optimise purpose and features

A

It is idempotent (meaning that it won’t reoptimise files that has been optimised)
- performs bin compaction by joining small files into large files

58
Q

VACUUM purpose

A

removal of files no longer reference by a delta table

59
Q

COALESCE

A

spark method to reduce the amount of partitions in a delta table. Let’s say you have 100 partitions, you can coalesce into 10 partitions

60
Q

Repartition

A

Involves breaking of existing partitions to create new partitions, either be more or less than the original partitions. Repartitioning is an expensive operation because it involves shuffling (unlike coalesce)
- always reoptimises files regardless whether it has been optimised previously or not

61
Q

V order increases the ___________ but reduces the _____ performance

A

increases the write time but reduces the read performance

62
Q

What level of access do you need to run query info

A

Contributor level. Viewer not possible

63
Q

Benefits of Direct Lake

A
  • read parquet files direct.
  • for real-time, stored in one fabric data store, and dataset size is large
  • must be in lakehouse or warehouse
64
Q

What is composite model used for

A

for many-to-many relationships without the need for bridge tables. For example: for fact tables use direct query and for dim tables use import mode

65
Q

Implicit vs Explicit measure

A
  • Implicit measures in Power BI are measures that are automatically created by Power BI based on the data model. Power BI generates implicit measures based on the aggregation used in the visualizations. For example, if you create a bar chart and drag a field to the Value area, Power BI automatically creates a sum aggregation for that field, which becomes an implicit measure. Implicit measures are also created when you use the Quick Measure feature in Power BI.
  • Explicit measures in Power BI are measures that are created by the user using DAX formulas. Explicit measures are highly customizable and can be used to create more complex calculations.
66
Q

You have a Fabric tenant that contains a semantic model. You need to prevent report creators from populating visuals by using implicit measures. What are two tools that you can use to achieve the goal»

A

-Microsoft Power BI Desktop: allows you to control and manage how measures are used within your reports. By carefully defining and using explicit measures within your data model, you can ensure that report creators use only these predefined measures instead of creating implicit measures automatically
-Tabular Editor: powerful tool for managing and editing Power BI and Analysis service tabular models. It allows you to enforce best practices, such as disabling implicit measures, by modifying model’s properties and ensuring that only explicit measures are available for use in reports.

67
Q

Transformations that support query folding

A
  • removing or renaming columns
    -merging foldable queries that are based on the SAME source
  • appending foldable queries based on the SAME source
  • numeric calculations
  • joins
  • pivot and unpivot
68
Q

Transformations that do not support query folding

A
  • merging or appending queries that are based on different sources
  • using some functions while adding custom columns that do not have a counterpart in sql
  • adding columns with complex logic. these refer to functions that do not have equivalent functions in the data source.
69
Q

importance of query folding

A
  • increased efficiency
  • optimisation of cpu usage
  • improved data security
70
Q

What is the visualisation command in Microsoft Fabric Notebook to see summary of the data

A
  • display()
  • display(df,summary=true) to check the statistics summary of a given Apache Spark Dataframe. The summary includes the column name, column type, unique values, and missing values for each column.
  • Microsoft Fabric also supports displayHTML() option
71
Q

How to Embed a Power BI report in a notebook

A
  • import powerbiclient
    Capabilities:
  • you can render an existing Power BI report Istill in preview)
  • create report visuals from a pandas Dataframe
  • create report visuals from a spark dataframe
72
Q

What does setting the XMLA Endpoint to read write do?

A

Allows users not only to read the data from the Power BI service but also to write back to it. Necessary for users to create and publish custom direct lake semantic models. Without write access, users would be unable to publish or update their models, which is critical part of managing semantic models.

73
Q

What does allowing XMLA Endpoint and Analyze in Excel with on-premises datasets to Enabled in the Tenant Settings do ?

A

We need to enable XMLA endpoints from the tenant settings to ensure that external tools interact with the data models as and when necessary within the tenant’s workspace. The analyze in excel is just complimentary to this setting in Fabric and is irrelevant

74
Q

RLS only applies to queries in _____ or _____ in Fabric. Power BI queries on a warehouse in Direct Lake mode will fall back to _____ to abide RLS

A
  • Applies to queries on warehouse or sql analytics endpoint
  • will fall back to direct query mode
75
Q

Query the $System.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS dynamic management view (DMV). What does this do?

A

provides information about memory grants for queries. Helps identify the frequently used columns that are loaded into memory

76
Q

Clone table in microsoft fabric

A

Microsoft fabric offers the capability to create near-instantaneous zero-copy clones with minimal storage costs.

  • table clones facilitate development and testing processes by creating copies of tables in lower environments
  • provides consistent reporting and zero-copy duplication of data for analytical workloads and ML modeling and testing
  • provide the capability of data recovery in the event of a failed release or data corruption by retaining the previous state of data.
  • help create historical reports that reflect the state of data as it existed as of a specific point-in-time in the past.
77
Q

What is zero-copy clone

A

creates a replica of the table by copying the metadata, while still referencing the same data files in OneLake. The metadata is copied while the underlying data of the table stored as parquet files is not copied. The creation of a clone is similar to creating a table within a Warehouse in Microsoft Fabric

78
Q

Permissions to create a table clone

A
  • users with admin,member, or contributor workspace roles can clone the tables within the workspace. The viewer workspace role cannot create a clone
  • select permission on all the rows and columns of the source of the table clone is required.
  • users must have create tale permission in the schema where the table clone will be created
79
Q

Table clone inheritance

A
  • inherits OLS from the source table of the clone
  • inherits RLS and dynamic data masking
  • all atributes that exist at the source, same schema or not
  • inherits primary and unique key
80
Q

Where can you do delta lake table optimisation and V-order?

A

ONLY IN THE LAKEHOUSE

81
Q

You have a Fabric tenant that contains a warehouse.
You use a dataflow to load a new dataset from OneLake to the warehouse.

You need to add a PowerQuery step to identify the maximum values for the numeric columns.

Which function should you include in the step?

A

Use Table.Profile instead of Table.Max because Table.Max returns the row in a table that contains the maximum value for a specified column, rather than providing the maximum values for all numeric columns.

82
Q

Where to enable XMLA read-write

A

By default, Premium capacity or Premium Per User semantic model workloads have the XMLA endpoint property setting enabled for read-only. This means applications can only query a semantic model. For applications to perform write operations, the XMLA Endpoint property must be enabled for read-write.

  • Go to Settings > Admin Portal > Capacity Settings > Power BI premium > capacity name
  • Expand workloads. In the XMLA endpoint setting, select read write.
83
Q

TRUNCATE TABLE

A

removes all rows from a table, but the table structure and its columns, constraints, indexes, and so on, remain.

84
Q

Query folding is not applicable to

A

csv files

85
Q

Are parquet files compressed?

A

by default yes. No need to enable it .When writing parquet files, you can specify the desired compression codec, to further optimise storage and performance

DP600 (1 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions