Self-service Business Intelligence Tools

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Self-service Business Intelligence Tools – . Data architecture is typically managed by a centralized team of BI experts, while reporting responsibility rests with creators within departments or business units.

In general, there are more report creators than dataset creators These report creators can exist in any area of ​​the organization Because self-service report creators often need to produce content quickly, a hybrid approach allows them to focus on producing reports that support timely decision making without the additional effort of creating a dataset.

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A managed self-service BI scenario is the first of its kind in a self-service BI scenario For a complete list of self-service BI scenarios, see the Power BI use cases article

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For the sake of brevity, some aspects described in the context of content collaboration and delivery scenarios are not covered in this article For complete coverage, read those articles first

The following figure describes a high-level overview of common user functions and power BI components that support managed self-service BI The primary purpose is to reuse centrally shared datasets for multiple report creators To accomplish that, this scenario focuses on decoupling the model development process from the report generation process

Database developers develop models using Power BI Desktop For datasets intended for reuse, it is common (but not required) for the creators to be from a centralized team that supports users across organizational boundaries (such as IT, enterprise BI, or a center of excellence).

Data models are developed in Power BI Desktop Extra effort is put into creating a well-designed and user-friendly model because it will be used as a data source by many self-service report creators.

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The dataset is published in a workspace dedicated to storing and securing shared datasets Since the dataset is intended for reuse, it is approved (certified or promoted as appropriate). The dataset is also discoverable to further encourage its reuse The lineage view in the Power BI service can be used to track dependencies between Power BI items, including reports linked to datasets.

Dataset discovery is enabled in Data Hub because the dataset is marked as discoverable Discoverability allows the existence of a dataset to be made visible in Data Hub by other Power BI content creators looking for the data.

If the report creator does not have permission, they can request permission to build on the dataset This initiates a process to request build permission from an authorized approver

Report creators create new reports using Power BI Desktop Reports use a live connection to a shared dataset

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Published reports are linked to shared datasets that are stored in a different workspace Any change to a shared dataset affects all reports linked to it

Other self-service report generators 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 residing within a private organizational network, an on-premise data gateway is required for data refresh.

The task is to minimize the number of databases This scenario is about shared datasets that help achieve a

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For simplicity, the scene diagram depicts only one shared dataset However, it is usually not practical to model all organizational data in a single dataset The other extreme is creating 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 datasets and creating new databases when it makes sense to do so.

When the dataset is decoupled from the report, it facilitates the separation of effort and responsibility A shared dataset is typically managed by a centralized team (such as IT, BI, or a center of excellence), while reports are managed by subject matter experts across business units. However, that is not necessary For example, this pattern can be adopted by any content creator who wants to achieve reusability.

For simplicity, the dataflow view is not depicted in the figure About Dataflow, see Self-Service Data Preparation Scenarios

It is a best practice to have a consistent, repeatable, rigorous process for supporting content The certified content should indicate that the data quality has been validated It should also follow change management rules, have formal support and be fully documented Because certified content has passed strict standards, expectations for reliability are high

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Data Hub helps creators find, explore, and report on the use of datasets across organizations Along with dataset endorsement, it is important to enable dataset discovery to promote its reuse. A discoverable dataset is visible in the Data Hub for report creators searching for data

If a dataset is not configured to be discoverable, only Power BI users with Build permissions can access it.

A report creator can find a dataset in Data Hub that they want to use If they don’t have build permission for the dataset, they can request access Depending on the request access settings for the dataset, an email will be submitted to the dataset owner or custom instructions will be presented to the person requesting access.

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

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When using a live connection, all the data the report creator needs must be within the connected dataset. However, the customizable managed self-service BI view illustrates how a dataset can be extended with additional data and calculations.

First, there is clarity on who is responsible for content management in which workplace Second, the report creator has permission to publish content to a report workspace (via the workspace admin, member, or collaborator roles). However, they only have Read and Create permissions for specific databases This technique allows Row Level Security (RLS) to be implemented if needed for users assigned to the Viewer role.

When you publish a Power BI Desktop report to a workspace, the RLS role is applied to members assigned to the viewer role in the workspace. Even if the viewer dataset has build permission, RLS still applies For more information, see Using RLS with Workspaces in Power BI

When a shared dataset is used by multiple reports, those reports can exist in multiple workspaces A genealogical view helps identify and understand downstream dependencies When planning a dataset change, first perform an impact analysis to understand which dependent reports may need editing or testing.

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Typically, a data gateway is required when accessing data resources residing within a private organizational network or a virtual network. On-Premier Data Gateway becomes relevant after a Power BI desktop file is published to the Power BI service. The two purposes of a gateway are to refresh imported data, or to view a report querying a live connection or DirectQuery database.

. In standard mode, Data Gateway supports live connections and DirectQuery operations (including scheduled data refresh operations).

The activity log records user activity that occurs in the Power BI service Power BI administrators can use the activity log data that is collected to conduct audits that help them understand usage patterns and adoption. Activity logs are also valuable in supporting governance efforts, security audits, and compliance requirements With a managed self-service BI view, tracking the usage of shared databases is especially helpful A high report-to-dataset ratio indicates good reuse of the dataset

In the next article of this type, we discuss ways to customize and extend a shared dataset to meet additional types of needs. By clicking Sign in with Social Media, you authorize PAT Research to store, use and/or disclose your social media profile. Email address and agree to Terms of Use as per PAT Research Privacy Policy

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Business intelligence solutions transform raw data into meaningful and actionable data for insightful representations of knowledge and the publication of business intelligence objects.

Business Intelligence solutions enable, enrich and enhance the collection and adoption of confidential data Business intelligence solutions can manage large amounts of information through collaboration

Business Intelligence helps identify and develop new opportunities through solution theory, methods, processes, architectures and technologies.

Deploying business intelligence can bring additional business value across all business verticals Visible benefits can be achieved in measurement, analytics, reporting, enterprise reporting, collaboration, collaboration platforms, knowledge management.

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The availability of business intelligence tools on the cloud enables fast and real-time access to important data regardless of location. Data from various sources can be integrated and formatted and this enables managers to run various ad hoc reports. Better business processes lead to better efficiency and productivity

Business intelligence tools enable seamless scalability of users across different business enterprises – from single users to hundreds of users without significant changes in costs.

The tools allow the integration of powerful reporting software such as Crystal Reports Reports can be customized for use by customers, board directors, managers and employees BI-generated charts, graphs and visualizations can be integrated with existing customized applications.

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Insights are provided for both historical and real-time data The resulting reports can be exported to various user-defined formats such as Excel, PDF or PowerPoint presentations. Users

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