Self-service Business Intelligence Examples – A series of articles. This series focuses on the use of Power BI within Microsoft Fabric. To learn more about this list, see Power BI Setup.
. Data architecture is often managed by a single team of centralized BI experts, while reporting responsibility rests with developers in departments or businesses.
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In many cases, there are more report developers than dataset developers. These reports can be located in any area of the organization. Because automated reporting developers often need to produce data quickly, an integrated approach allows them to focus on creating reports that support timely decision-making without the additional effort of generating data.
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Self-service BI driven experiences are the first of many self-service BI experiences. For a complete list of self-service BI activities, see the Power BI user guide.
In summary, some of the information described in the related topics is not covered in this article. For the full story, read the articles first.
The following diagram shows a high-level overview of what most users use with the Power BI tools that support BI automation. The main goal is for many report developers to reuse shared datasets. To that end, this event focuses on removing the modeling process from the reporting process.
Dataset developers create models using Power BI Desktop. For data reuse groups, it is common (but not required) for developers to be part of a team that supports users across organizational boundaries (such as IT, enterprise BI, or a Center of Excellence).
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Data model development is done in Power BI Desktop. Extra effort is made to create a well-designed and easy-to-use model as it will be used as a data source by many automated report generators.
The data set is published to a dedicated workstation for storage and storage of shared data. Since the data is intended for reuse, it is valid (verified or upgraded, if necessary). The archive is also published as accessible to encourage its reuse. Row views in the Power BI service can be used to track dependencies between Power BI objects, including reports linked to a dataset.
Access to data in the data bar is enabled because the data group is marked as available. Annotation makes the existence of the dataset visible in the data hub and other Power BI product developers looking for the data.
If report developers do not have permission, they can request Build permission for the dataset. This starts the process of requesting a Build license from an authorized licensee.
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Report developers create new reports using Power BI Desktop. Reports use correlations that occur with a shared dataset.
Published reports remain linked to shared datasets stored in different workstations. Any changes that are shared affect all linked reports.
Some automated report generators can write new reports using previously distributed data. Report creators can choose to use Power BI Desktop, Power BI Report Builder, or Excel.
To connect to data sources that reside in a public network, an On-premises data gateway is required for data recovery.
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Function is to reduce the size of the dataset. This is about datasets that help achieve a
For simplicity, this diagram shows only one data distribution. However, it is not often practical to include all of the group’s data in one group. Another major challenge is creating new data for each report, as many product developers often do. The goal of automated BI is to find the right solution, lean on limited datasets and make new decisions when they make sense.
When data is separated from reports, it helps to separate effort and responsibility. A shared tool is often maintained by a central team (such as IT, BI, or a Center of Excellence), while reporting is handled by business subject matter experts. However, that is not necessary. For example, this model can be taken by any manufacturer who wants to reuse it.
For simplicity, the data flow is not shown in the diagram. As for dataflows, see the events for preparing automated dataflows.
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It’s best practice to have a regular, repeatable, consistent process for content approval. Validations must indicate that the data type has been verified. It must also comply with regulatory requirements, have legal support, and be fully documented. Because certified products have passed strict standards, reliability expectations are very high.
A database system helps reporters find, search, and use data across the board. In addition to the acceptance of the dataset, allowing the accessibility of the dataset is very important in promoting its reuse. The group of data that can be found is visible in the reporting area that is looking for data.
If the data is not configured to be accessible, only Power BI users with Build permission can access it.
The report designer can find the data group he wants to use. If they don’t have Build permission for the dataset, they can request permission. Depending on the settings of the dataset request, an email will be sent to the owner of the dataset or instructions will be provided to the person requesting access.
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A Power BI Desktop Live connection connects a report to an existing dataset. Live connections avoid the need to create a new data type in the Power BI Desktop file.
When using the Internet, all the data the report designer needs must be contained within the linked dataset. However, a fully customizable BI interface defines how the data can be enhanced with additional features and calculations.
First, there is clarity about who is responsible for managing the content of the workplace. Second, the report creators have permission to publish the content of the reporting site (through the work sites, members, or sponsors). However, they only have Read and Build permissions for specific datasets. This option allows line-level security (RLS) to operate when necessary for users who have been assigned viewing privileges.
When you publish a Power BI Desktop report to a workspace, RLS roles are assigned to members who have been assigned viewing roles in the workspace. Even if the viewer has Build permission to the dataset, RLS is still active. For more information, see Using RLS with workspaces in Power BI.
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When shared data is used by many reports, those reports can exist in many work environments. Linear visualization helps identify and understand underlying dependencies. When planning a dataset change, first analyze the results to understand which reliable reports may need to be changed or tested.
In most cases, a data gateway is required when accessing data sources that reside in a public or virtual network. The On-premises data gateway works when a Power BI Desktop file is published to a Power BI application. The two purposes of the gateway are to refresh data that has been exported, or to view a report that queries an existing connection or DirectQuery dataset.
. In standard mode, the data gateway supports live communication with DirectQuery services (including data refresh services).
The event log records user activities that occur in the Power BI service. Power BI administrators can use the collected data for analysis to help them understand usage and adoption. The work plan is also important in supporting regulatory efforts, security assessments, and compliance. With an automated BI interface, it is very useful to monitor the usage of shared data. The amount of reporting to the dataset indicates the optimal reuse of the dataset.
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In the next article in this series, about ways to change and expand shared data to meet other needs. As the amount of business data is constantly increasing, it is important that companies put their efforts in managing data and analyzing it with the help of business intelligence, designed to help business people get information from past work, predict the future and avoid obstacles even before they happen. Investing in and using tools that can generate better business intelligence has been a long-term trend, regardless of economic conditions. It has grown exponentially in recent years as businesses demand more information to not only grow and manage, but also run their businesses on a daily basis.
Gone are the days when online BI was used only by large enterprises due to the complexity, cost and skills required. Today, small and medium-sized businesses (SMBs) are becoming the largest consumers of BI. In order to stand out from the competition, reduce costs, and increase profits, a company must make smart decisions. To do this, these decisions must be based on reliable and relevant data, and this is where BI helps. As services, tools, and software become cheaper, the introduction of business intelligence (SSBI) has made deep analytics easier to use, so that everyone in the organization can participate.
These ideas will be the main focus of our article. We will explain the business intelligence of automation, provide an overview and comparison between traditional and automated BI, list the most common advantages, and explain what tools used in BI should be in order to produce the right business results. Finally, we show you the best practices you can
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