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DP-500 Exam Questions - Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI | [HOSTED-SITE]

Microsoft DP-500 : Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI Exam Dumps

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Exam Number : DP-500
Exam Name : Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI
Vendor Name : Microsoft
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DP-500 Exam Format | DP-500 Course Contents | DP-500 Course Outline | DP-500 Exam Syllabus | DP-500 Exam Objectives

Exam Specification: DP-500 Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI

Exam Name: DP-500 Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI
Exam Code: DP-500
Exam Duration: 150 minutes
Passing Score: 700 out of 1000
Exam Format: Multiple-choice
Exam Delivery: Proctored online or at a testing center

Course Outline:

1. Introduction to Enterprise-Scale Analytics Solutions
- Overview of enterprise-scale analytics solutions
- Understanding the benefits and features of Microsoft Azure and Power BI
- Exploring the architecture and components of Azure and Power BI

2. Planning and Designing Azure Data Platform Solutions
- Gathering and analyzing business requirements
- Designing data storage and processing solutions using Azure services
- Designing data integration and data movement solutions

3. Designing Data Processing Solutions
- Designing batch processing solutions using Azure Data Factory
- Designing real-time data processing solutions using Azure Stream Analytics
- Designing big data processing solutions using Azure Databricks and HDInsight

4. Designing Data Storage Solutions
- Designing relational and non-relational data storage solutions using Azure services
- Designing data warehousing solutions using Azure Synapse Analytics
- Designing data lake and analytics solutions using Azure Data Lake Storage and Azure Analysis Services

5. Implementing Power BI Solutions
- Designing and implementing data models in Power BI
- Creating and optimizing Power BI reports and dashboards
- Implementing security and governance in Power BI

Exam Objectives:

1. Understand the concepts, benefits, and features of enterprise-scale analytics solutions using Azure and Power BI.
2. Plan and design Azure data platform solutions based on business requirements.
3. Design data processing solutions using Azure Data Factory, Azure Stream Analytics, and Azure Databricks/HDInsight.
4. Design data storage solutions using Azure services, including Azure Synapse Analytics and Azure Data Lake Storage.
5. Design and implement data models, reports, and dashboards in Power BI.
6. Implement security and governance measures in Power BI.

Exam Syllabus:

Section 1: Introduction to Enterprise-Scale Analytics Solutions (10%)
- Enterprise-scale analytics solutions overview
- Benefits and features of Azure and Power BI
- Architecture and components of Azure and Power BI

Section 2: Planning and Designing Azure Data Platform Solutions (25%)
- Gathering and analyzing business requirements
- Designing data storage and processing solutions using Azure services
- Designing data integration and data movement solutions

Section 3: Designing Data Processing Solutions (25%)
- Designing batch processing solutions using Azure Data Factory
- Designing real-time data processing solutions using Azure Stream Analytics
- Designing big data processing solutions using Azure Databricks and HDInsight

Section 4: Designing Data Storage Solutions (25%)
- Designing relational and non-relational data storage solutions using Azure services
- Designing data warehousing solutions using Azure Synapse Analytics
- Designing data lake and analytics solutions using Azure Data Lake Storage and Azure Analysis Services

Section 5: Implementing Power BI Solutions (15%)
- Designing and implementing data models in Power BI
- Creating and optimizing Power BI reports and dashboards
- Implementing security and governance in Power BI

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Microsoft Analytics Test Prep

Microsoft 365 usage analytics will be pseudonymized by default from tomorrow3 3

Microsoft 365 logo on an orange background

Privacy, even within organizations, has become a major focus area in light of recent laws such as the General Data Protection Regulation (GDPR) in the EU. This is even more important in analytics use-cases where you have to look at dashboards to draw insights, among many other things. In accordance with its commitment to privacy, Microsoft has announced that it is making some changes to Microsoft 365 configurations.

Starting from September 1, 2021 - that is, tomorrow -, usage analytics for Microsoft 365 will be pseudonymized by default. This change impacts user-level information stored and accessed across the following APIs and products:

Microsoft 365 Reports in the Microsoft 365 admin center

Microsoft 365 usage reports in Microsoft Graph

Microsoft Teams analytics and reporting in the Microsoft Teams admin center

The reportRoot: getSharePointSiteUsageDetail API (1.0 and beta) for SharePoint site detail

It is important to note that while this will be a default configuration from tomorrow, global admins can revert back to showing personally identifiable information (PII) via the Microsoft 365 admin center. Any changes to this configuration will be logged to the Microsoft 365 compliance center for auditing and traceability. Modifications to this configuration will be contingent to the organization's privacy practices.

If identification is allowed, administrative and report reader roles will be allowed to view PII in clear. Meanwhile, Global reader and Usage Summary Reports Reader roles will not be able to see PII in clear regardless of the configuration. Microsoft hopes that this move will help increase privacy while still allowing admins to to measure trends and Microsoft 365 license allocation and renewal within their organization.

Analytics Will Be More Prominent in Draft Prep

No result found, try new keyword!Robinson understood that draft analytics did have at least some role in evaluating prospects – or pro personnel – but felt that it paled in comparison to the good old-fashioned eye test.

Introducing Microsoft Fabric: The future of data analytics

Zia Marais, Engagement Lead at Decision Inc.

Data is the new oil. And in the digital age, businesses that can harness the power of data will have a competitive advantage, says Zia Marais, Engagement Lead at Decision Inc.

That’s where Microsoft Fabric comes in.

Microsoft Fabric is a unified SaaS (software as a service) platform bridging the data and intelligence gap. It provides data integration, data engineering, data warehousing, data science, real-time analytics and business intelligence all within a single architecture. It brings together all the data and analytics tools that organisations need, including Power BI, Azure Data Factory and Azure Synapse Analytics.

What Power BI did for business intelligence, Fabric has done for data science. No longer will enterprises find it hard to manage, analyse and visualise their data because there is one platform for everything.

What does that mean for businesses today?

Imagine a place where data engineers, data warehousing professionals, data scientists, data analysts and business users can all access their company’s data in the way that they need to.

For example, data engineers can connect and curate data from different sources, while at the same time, data scientists can develop models without having to move the data elsewhere. While this is happening, data analysts can create rich visualisations within Power BI Online or Desktop.(1) And then to benefit the normal business user, this same data can be explored in standard Microsoft 365 apps using natural language queries or pre-built templates.

Looking at those breakdowns in a bit more detail:

In the data warehousing function, Fabric can help organisations to:

Consolidate data from multiple sources into a single repository.

Improve data quality and consistency.

Automate data lineage and governance.

Scale up or down to meet changing business needs.

In the data engineering function, Fabric can help organisations to:

Build and deploy data pipelines.

Automate data processing tasks.

Monitor data quality and performance.

Scale up or down to meet changing business needs.

In the data analytics function, Fabric can help organisations to:

Analyse data using a variety of tools and techniques.

Visualise data in a way that is easy to understand.

Share insights with stakeholders across the organisation.

In the data science function, Fabric can help organisations to:

Build and train machine learning models.

Deploy machine learning models into production.

Monitor machine learning models for performance and accuracy.

In short, by housing all their data and data processes in one platform, organisations can significantly reduce costs, improve collaboration and simplify purchasing. Fabric provides deeply integrated, consistent, role-specific experiences that work.

What other ways will businesses benefit?

Microsoft has put together the whole package and the benefits Fabric has to offer are impressive. Here are a few benefits enterprises should expect:

Automated data lineage and governance – Fabric can automate data lineage and governance, which can equip businesses to track the movement of data and ensure that it is compliant with regulations. This enables businesses to reduce the risk of data breaches and other compliance violations.

Scalability and performance – Fabric is a scalable platform that can handle large volumes of data. This means that businesses can use Fabric to analyse data from a variety of sources, without having to worry about performance issues.

Security and compliance – Fabric is a secure platform that meets industry compliance standards. This means that businesses can use Fabric to store and analyse sensitive data without having to worry about security breaches.

Cost-effectiveness – Fabric is a cost-effective platform that can help businesses to save money on their data analytics costs. This is because businesses can pay for the resources they need, when they need them, with the pay-as-you-use function without getting into the data integration processes.

Democratisation of data – Fabric makes it easier for non-technical users to access and analyse data. This can help to improve decision-making across the organisation.

Increased collaboration – Fabric facilitates collaboration between data scientists, analysts and other stakeholders. This can help to accelerate the time to insights.

Improved agility – Fabric makes it easier for organisations to adapt to changing business needs. This can help to improve the organisation's competitive advantage.

Because different data users are all using the same data in a single platform, it creates a culture of empowerment around a business’s data.

And because Fabric is held entirely in the cloud, it scales as your business scales – meaning you aren’t hindered by the performance of your servers. In fact, the platform’s infrastructure ensures high performance and reliability, allowing businesses to process and analyse large datasets easily.

As businesses continue to generate more data, they will need a platform that can help them to manage, analyse and visualise their data. Fabric is a platform that will not just meet these needs but exceed them.

I believe it will become an essential tool for businesses in the years to come.

(1) Unlike with other systems, Power BI Desktop doesn’t need to import the data – it references and uses the data within Fabric.

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