This technical course educates about creating visualizations, the Power BI Mobile App, and the Power BI service. It helps in optimizing data models and links to data sources and guides in combining and shaping data from various sources.
Course Price : $1725 Per Participant
Note: DA-100 is the replacement course for 20778 which is retired.
20778: Analyzing Data with Power BI Training is aimed at professionals to help them develop a conceptual understanding of data analysis with Power BI.
This technical course educates about creating visualizations, the Power BI Mobile App, and the Power BI service. It helps in optimizing data models and links to data sources and guides in combining and shaping data from various sources.
This training program is suitable for professionals who are responsible for analyzing data with the help of Power BU. It is also ideal for individuals who want to gain the MCSA: BI Reporting certification.
Throughout this course, professionals will learn to demonstrate self-service BI, model data, create reports, and handle solutions. It also helps in describing the Power BI developer APU and Power Bi mobile application.
This training is designed based on the objectives of the course variant 20778C.
Courses
Years of Experience
Global Learners
Modeling data.
Describing self-service BI.
Describing products of the Power BI.
Describing Power BI developer API.
Describing the Power BI mobile app.
Creating reports and managing solutions.
Connecting data sources and optimizing data models.
Shaping and combining data from various sources.The best-suited audience for this course is Power BI professionals who want to learn data analysis utilizing Power BI.
The other audience for the course is business users with technical knowledge.
Microsoft Learning PartnerMicrotek Learning is a Microsoft Certified Partner for Learning Solutions. This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).
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You can also speak with a learning consultant by calling 800-961-0337.
Business intelligence (BI) is a term that has become increasingly common over recent years. Along with big data, data mining, predictive analytics, data science, and data stewards, BI is now very much part of business vocabulary. Much of the impetus behind this is the need for organizations to cope with ever-increasing datasets. It is now normal to have databases that contain millions of rows, requiring gigabytes, terabytes, or even petabytes, of storage space. Data is no longer confined to an on-premises server room—it is hosted in the cloud, feeds are taken from third-party providers, public datasets are freely available, and social media interactions generate ever-expanding datasets. Reporting and analysis is certainly not a new concept to business, but the difference between how data analysis is done today, compared with five or 10 years ago, is immense. Nowadays, organizations need BI to see not only what was done in the past, but also more of what is to come. There is now an overwhelming amount of data to gather and compose into reports. There is also an increasing need for data to offer up-to-the-minute numbers, so business can react faster to changing trends in markets and industries. Those businesses that can react fast and predict near-term trends to provide products and services where there is consumer demand have the best chance of survival in our modern and highly competitive world. With the rise of big data, there is an increasing need for data analysts who can take this data, and find the critical points within a plethora of information.
Lab: Exploring an Enterprise BI Solution
After completing this module, students will be able to:
Self-Service Business Intelligence (BI) has rapidly grown in popularity because of its ability to empower users to generate reports, process data, perform analysis, and more—all without having to depend on a report developer. The Self-Service BI trend is driven by Microsoft's commitment to improving Excel and Power BI, both products having seen many enhancements over recent years. However, despite Microsoft enabling deeper data analysis with the four power tools added to Excel—Power Pivot, Power View, Power Query, and Power Map—they are not fully integrated into the Excel interface. Instead, they exist in separate windows. Add to this the complexity of publishing to SharePoint to share reports with colleagues, and it all becomes a time-consuming effort. Using Power BI eliminates complications and barriers with a simple integrated user interface, and has the ability to publish rapidly to either a cloud-based or an on-premise portal to share reports easily. This module introduces Power BI, and explores the features that enable the rapid creation and publication of sophisticated data visualizations.
Lab: Creating a Power BI Dashboard
After completing this module, students will be able to:
Power BI offers a straightforward approach to report creation, and the ability to create and share dashboards without dependency on a report developer, or the need for Microsoft SharePoint. Microsoft Excel has long been the tool of choice for data analysts who work in a self-service style. However, Excel does not offer a quick and easy way to share reports without the use of either SharePoint, or the creation of multiple copies of spreadsheets that quickly become out of date, or exist outside source control. In recent years, power tools have been added to Excel: Power View, Power Query (known as Get & Transform in Excel 2016), and Power Pivot. Power BI brings much of this power into an integrated environment in the form of Power BI Desktop. Previously, Excel users have been inconvenienced by needing to transition between the different power tools, but Power BI Desktop brings the tools together. This means that Power BI is fast becoming an obvious choice for the analysis and sharing of data. However, analysts are likely to continue working with Excel for the foreseeable future. Power BI easily cooperates with Excel, and many other data sources. It’s this ability to create reports rapidly, by using data from a combination of sources, that really puts the power into Power BI.
Lab: Importing Data into Power BI
After completing this module, students will be able to:
Power BI Desktop offers a self-service solution for creating visual, interactive reports and dashboards. Users can connect to a wide variety of data sources, combining data from on-premises databases, Software as a Solution (SaaS) providers, cloud-based services, and local files such as Microsoft Excel, into one report. The beauty of Power BI reports and dashboards is the ability to rapidly build reports to present this data so it is instantly readable—with clusters, outliers, and patterns in data visually brought to light. To achieve this, each report must have a dataset comprising tables and columns that are ready to add straight into visualizations. Data must be formatted for relevant currencies, numbers should have correct decimal places, additional columns and measures might be required, and data may have to be combined from multiple tables. With Power BI Desktop, you can do all of this, with powerful, built-in tools for shaping your data. This module introduces the tools that are available for preparing your data, and transforming it into a form ready for reporting.
Lab: Shaping and Combining Data
After completing this module, students will be able to:
Microsoft Power BI is making its mark in the self-service BI world—because it can quickly create visually stunning, interactive reports, and dashboards. Power BI provides a straightforward way to combine data from a wide range of sources into a single dataset, and then work with that data to create cohesive reports. This module goes behind the scenes of the visualizations, and explores the techniques and features on offer to shape and enhance your data. With automatic relationship creation, a vast library of DAX functions, and the ability to add calculated columns, tables, and measures quickly, you will see how Power BI creates attractive reports, while helping you find hidden insights into data.
Lab: Modeling Data
After completing this module, students will be able to:
Self-service business intelligence (BI) is becoming increasingly popular in organizations. This approach enables business users to access corporate data, and create and share reports and key performance indicators (KPIs) without dependency on a dedicated report developer. Business users can use the Microsoft Power BI suite of tools to connect to a wide variety of data sources. These include the main industry-standard databases, Microsoft cloud-based services—Microsoft Azure SQL Database, Azure Data Lake, and Azure Machine Learning—alongside Microsoft Excel and other files, and software as a service (SaaS) providers such as Microsoft Bing, Facebook, and MailChimp. The combination of flexibility and the ability to create visually stunning, interactive dashboards quickly makes Power BI an obvious choice for any organization that needs to provide its users with a self-service BI solution.
Lab: Creating a Power BI Report
After completing this module, students will be able to:
Power BI service supports live direct connections to Azure SQL Database, Azure SQL Data Warehouse, big data sources such as Spark on Azure HDInsight, and SQL Server Analysis Services. DirectQuery means that whenever you slice data or add another field to a visualization, a new query is issued directly to the data source. Power BI works with SQL Server Analysis Services models that are running in multidimensional mode, so that you can use OLAP cubes and models in reports and dashboards. It doesn’t matter if you are using the Power BI service in the cloud, and an on-premises SQL Server Analysis Services implementation; the on-premises data gateway enables live connections between the cloud and on-premises data servers.
Lab: Direct Connectivity
After completing this module, students will be able to:
The Power BI API is a REST-based API that developers use to access programmatically datasets, tables, and rows in Power BI. Using this API, you push data from an application into Power BI and integrate Power BI visualizations into an application. You can also add custom visuals to your applications and to Power BI dashboards and reports. In this module, you will learn how to use the Power BI API to embed content in your applications and how to use custom visuals in your reports.
Lab: Using Marketplace Visualizations
After completing this module, students will be able to:
Power BI mobile apps enable you to access and use Power BI information on a mobile device, including iOS (iPad, iPhone, iPod Touch, Apple Watch), Android phone or tablet, and Windows 10 devices. This means that, potentially, Power BI reports and Power BI dashboards created in Power BI Desktop and the Power BI service can be used anywhere and at any time. Power BI reports and dashboards are designed to work on a mobile device without modification. However, you can also create specific optimized reports and report layouts for display on mobile devices. The Power BI mobile apps support the sharing and annotation of dashboards, and you can use Power BI data on mobile devices even when you are not connected to a network. Power BI alerts and notifications also work across the Power BI service, including on mobile devices.
After completing this module, students will be able to:
As being the leading accredited training partner for Microsoft, our highly experienced certified Power BI trainers cover the widest scope of training. Under 'Power BI mobile app' training module, you will learn about mobile apps for iOS, Android, and Windows 10 mobile devices to use the data and reports for the business interests.
Our Power BI trainers cover the widest scope including to create DAX queries formulas for calculated columns, calculated tables, and measures. You also learn to calculate the actual; calculate the target; calculate actual to target.
VUE and Certiport are the Microsoft 70-778 exam providers.
To get MCSA (Microsoft Certified Solution Associate) certification in BI Reporting, you need to pass two exams: 70-778: Analyzing and Visualizing Data with Power BI and 70-779: Analyzing and Visualizing Data with Microsoft Excel.
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