Microsoft Business Intelligence Developer Tasks – This series of articles focuses primarily on Power BI workloads in Microsoft Fabric. To learn more about this series, see Power BI Implementation Planning.
. Data architecture is typically maintained by a single team of centralized BI experts, while reporting responsibility rests with developers in departments or business units.
Microsoft Business Intelligence Developer Tasks
There are usually many more report builders than dataset builders. These report makers can exist in any area of the organization. Because self-service report creators often need to generate content quickly, a hybrid approach allows them to focus on generating reports that support timely decision-making, without the extra effort of creating datasets.
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The managed BI self-service scenario is the first of the BI self-service scenarios. For a complete list of self-service BI scenarios, see the Power BI usage scenarios article.
For brevity, some aspects described in the topic of collaboration and content delivery scenarios are not covered in this paper. For complete coverage, read those articles first.
The diagram below shows a high-level overview of the most common user actions and Power BI components that support managed self-service BI. The main goal for many report builders is to re-use centralized shared data sets. To do that, this scenario focuses on separating the model development process from the report creation process.
Dataset builders develop models using Power BI Desktop. For datasets intended for reuse, it is common (but not required) for creators to belong to a centralized 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. More effort has been put into creating a well-designed and user-friendly model as it will be used as a data source by many self-service report builders.
The dataset is published in a dedicated workspace to store and secure the shared dataset. As the dataset is intended for reuse, it is verified (verified or upgraded as necessary). The dataset is also marked as discoverable to further encourage its reuse. The lineage view in the Power BI service can be used to trace the dependencies that exist between Power BI items, including reports connected to datasets.
Dataset discovery is enabled in the data center because the dataset is marked as discoverable. Discoverability allows the existence of a dataset in the data center to be visible to other Power BI content creators looking for the data.
If report creators do not have a license, they can request a license to build the dataset. This initiates a workflow to request a build permit from an authorized verifier.
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Report builders create new reports using Power BI Desktop. Reports use a live connection to a shared dataset.
Published reports remain connected to a shared dataset stored in a different workspace. Any changes to the shared dataset will affect all reports connected to it.
Other self-service report builders can write new reports using existing shared datasets. Report creators can choose to use Power BI Desktop, Power BI Report Builder, or Excel.
To connect to data sources located on a private enterprise network, an on-site data gateway is required to update the data.
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The task is to minimize the number of data sets. This scenario is about shared data sets that help achieve a
For simplicity, the scenario diagram shows only one common data set. However, it is usually not practical to model all enterprise data in one dataset. The other extreme is to create a new dataset for each report, as less experienced content creators often do. The goal of managed self-service BI is to find the right balance, leaning toward relatively small data sets and creating new data sets when it makes sense.
When the dataset is separated from the reports, it facilitates separation of effort and responsibility. A common dataset is typically maintained by a centralized team (such as IT, BI, or a center of excellence), while reports are maintained by subject matter experts in business units. However, this is not required. For example, this pattern can be adopted by any content creator who wants to achieve reusability.
For simplicity, data flows are not shown in the scenario diagram. For data flow, see the self-service data preparation scenario.
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Having a consistent, repeatable, and accurate process for content approval is best practice. Verified content should indicate that the quality of the data has been verified. It should also follow change management rules, have formal support and be fully documented. Because verified content has passed rigorous standards, expectations for trustworthiness are higher.
The data hub helps report creators find, explore, and use data sets across the organization. In addition to validation of the dataset, it is important to enable the discovery of the dataset to promote its reuse. A discoverable dataset in the data center is visible to report creators who are searching for data.
If a dataset is not configured to be discoverable, only Power BI users with Build permission can find it.
The report creator may find a dataset in the data center that they want to use. If they do not have permission to build the dataset, they can request access. Depending on the requested access settings for the dataset, an email is sent to the dataset owner or customized instructions are 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 model in the Power BI Desktop file.
When using a live connection, all the data that the report builder needs must be in the connected dataset. However, the configurable managed self-service BI scenario describes how a dataset can be extended with additional data and calculations.
First, it is clear who is responsible for content management in which workspace. Second, report creators have permission to publish content to a reporting workspace (via the workspace administrator, member, or contributor roles). However, they only have read and create permissions for specific datasets. This technique allows Row Level Security (RLS) to be applied to users assigned to the viewer role as needed.
When you publish a Power BI Desktop report to a workspace, RLS roles are applied to members assigned to the viewer role in the workspace. Even if viewers have permission to build datasets, RLS still applies. For more information, see Using RLS with workspaces in Power BI.
What Is Business Intelligence (bi): Complete Implementation Workflow
When a common dataset is used by many reports, those reports can exist in many workspaces. Line view helps identify and understand downstream dependencies. When planning to change a dataset, first perform an impact analysis to understand which dependent reports may need to be edited or tested.
Typically, a data gateway is required when accessing data resources located on a private enterprise network or a virtual network. When a Power BI Desktop file is published to the Power BI service, the On-premises data gateway is associated. The two purposes of a gateway are to refresh imported data or to view a report that requests a live connection or DirectQuery dataset.
. In standard mode, Data Gateway supports live connection and DirectQuery operations (in addition to scheduled data retrieval operations).
The activity log records user activities that occur in the Power BI service. Power BI administrators can use the activity log data collected to perform audits to help them understand usage and adoption patterns. Activity reporting is also valuable for supporting governance efforts, security audits, and compliance requirements. With a managed self-service BI scenario, tracking the usage of shared data sets is very useful. A high log-to-dataset ratio indicates good reuse of the dataset.
What Is Business Intelligence (bi)?
In the next article in this series, we’ll talk about ways to customize and extend a common dataset to meet other types of needs. Everything related to the past and present state of your business is recorded as bits of data. Marketing numbers, HR, corporate budgeting, sales volume – you name it. The number of business areas that data comes from can be large. But, as a business, you may be interested in extracting value from this information rather than collecting it. Be thankful that there is software for everything.
Business Intelligence (BI) is a set of technologies and methods for turning business information into actionable reports and visualizations. Founded in the early 80s, BI has developed as a separate industry over time, spawning numerous roles and professions. We have already explained the role of an ETL developer. This material reveals the features of the BI data infrastructure, so we suggest you read it to get a deeper insight into the topic.
Today we will discuss the role of a BI developer, typical responsibilities, background and skills required. We also define the difference between the other standard roles involved in building BI systems and the specifics that require you to hire a BI developer.
A business intelligence developer is an engineer responsible for developing, deploying, and maintaining BI interfaces. These include query tools, data visualization and interactive dashboards, ad hoc reporting, and data modeling tools. But, as we talk about business intelligence, we need to give a more detailed explanation of this technological concept.
Power Bi Usage Scenarios: Managed Self Service Bi
The whole BI system can be divided into the internal part and the actual user interface for interacting with the data. Why is this division so important? Regardless of system complexity, a typical BI platform has 3 layers: a data
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