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Azure Migrate

Azure Migrate is a service that helps you migrate from an on-premises environment to the cloud. Azure Migrate functions as a hub to help you manage the assessment and migration of your on-premises datacenter to Azure. It provides the following:

Unified migration platform: A single portal to start, run, and track your migration to Azure.

Range of tools: A range of tools for assessment and migration. Azure Migrate tools include Azure Migrate: Discovery and assessment and Azure Migrate: Server Migration. Azure Migrate also integrates with other Azure services and tools, and with independent software vendor (ISV) offerings.

Assessment and migration: In the Azure Migrate hub, you can assess and migrate your on-premises infrastructure to Azure.

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Availability Zones

Availability zones are physically separate datacenters within an Azure region. Each availability zone is made up of one or more datacenters equipped with independent power, cooling, and networking. An availability zone is set up to be an isolation boundary. If one zone goes down, the other continues working. Availability zones are connected through high-speed, private fiber-optic networks.

Use availability zones in your apps

You want to ensure your services and data are redundant so you can protect your information in case of failure. When you host your infrastructure, setting up your own redundancy requires that you create duplicate hardware environments. Azure can help make your app highly available through availability zones.

You can use availability zones to run mission-critical applications and build high-availability into your application architecture by co-locating your compute, storage, networking, and data resources within an availability zone and replicating in other availability zones. Keep in mind that there could be a cost to duplicating your services and transferring data between availability zones.

Availability zones are primarily for VMs, managed disks, load balancers, and SQL databases. Azure services that support availability zones fall into three categories:

Zonal services: You pin the resource to a specific zone (for example, VMs, managed disks, IP addresses).

Zone-redundant services: The platform replicates automatically across zones (for example, zone-redundant storage, SQL Database).

Non-regional services: Services are always available from Azure geographies and are resilient to zone-wide outages as well as region-wide outages.

Even with the additional resiliency that availability zones provide, it’s possible that an event could be so large that it impacts multiple availability zones in a single region. To provide even further resilience, Azure has Region Pairs.

Region pairs

Most Azure regions are paired with another region within the same geography (such as US, Europe, or Asia) at least 300 miles away. This approach allows for the replication of resources across a geography that helps reduce the likelihood of interruptions because of events such as natural disasters, civil unrest, power outages, or physical network outages that affect an entire region. For example, if a region in a pair was affected by a natural disaster, services would automatically fail over to the other region in its region pair.

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Overview of data analysis

Before data can be used to tell a story, it must be run through a process that makes it usable in the story. Data analysis is the process of identifying, cleaning, transforming, and modeling data to discover meaningful and useful information. The data is then crafted into a story through reports for analysis to support the critical decision-making process.

As the world becomes more data-driven, storytelling through data analysis is becoming a vital component and aspect of large and small businesses. It is the reason that organizations continue to hire data analysts.

Data-driven businesses make decisions based on the story that their data tells, and in today's data-driven world, data is not being used to its full potential, a challenge that most businesses face. Data analysis is, and should be, a critical aspect of all organizations to help determine the impact to their business, including evaluating customer sentiment, performing market and product research, and identifying trends or other data insights.

While the process of data analysis focuses on the tasks of cleaning, modeling, and visualizing data, the concept of data analysis and its importance to business should not be understated. To analyze data, core components of analytics are divided into the following categories:

Descriptive

Diagnostic

Predictive

Prescriptive

Cognitive

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Transform and load data

Most data requires transformations before loading into tables. You might ingest raw data directly into a lakehouse and then further transform and load into tables. Regardless of your ETL design, you can transform and load data simply using the same tools to ingest data. Transformed data can then be loaded as a file or a Delta table.

Notebooks are favored by data engineers familiar with different programming languages including PySpark, SQL, and Scala.

Dataflows Gen2 are excellent for developers familiar with Power BI or Excel since they use the PowerQuery interface.

Pipelines provide a visual interface to perform and orchestrate ETL processes. Pipelines can be as simple or as complex as you need.

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Branching scenarios

Changes that you make to a workspace when you're doing development work affect all other workspace users so it's a best practice to work in isolation outside of shared workspaces. To keep your development work isolated from shared workspaces, you can develop using:

A separate, isolated workspace

Client tools like Power BI Desktop for reports and semantic models or VS Code for Notebooks.

In both scenarios, your feature development work should take place in a dedicated branch instead of the main code branch. This makes it easy for multiple developers to work on a feature without affecting the main branch.

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Configure Semantic model permissions

A user's role in a workspace implicitly grants them permission on the semantic models in a workspace. Semantic models allow for security to be defined using DAX. More granular permission can be applied using row-level security (RLS). To learn more about the managing RLS or permissions on the semantic model see:

Semantic model permissions

Row-level security (RLS) with Power BI

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Explore Microsoft Copilot features

Some of these features might be temporarily unavailable due to app updates. .

Dictate: Use the dictate feature to ask a question. (Restate the previous prompt or create a new one.)

Rate: Rate the quality of the response.

Copy: Select the Copy button and copy the response to another location.

Export: Select the Export button and export the response to Word, Word Online, a PDF, or a text file.

Share: Select the Share button and choose a way to share the response with someone else.

Read aloud: Listen to the response read aloud through your device’s speakers.

Chat history: Open the chat history to view previous chats from the same account.