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Microsoft Power BI Dataflow with self-service ETL

Posted by Errin O'Connor on Mar, 09, 2021 03:03

Data Flows refer to the paths by which the data sets travel from one part of the information system of an organization to another. In the contemporary world, the increase in the competition between organizations, the volumes of data being accessed and produced are increasing enormously. Services like Power BI dataflow bring order in these situations.

Along with this, there is an increase in the number of challenges that companies are facing. Moreover, organizing use this data into valuable insights. Power BI Data Flows are the solution to these problems. The service can turn the large volumes of data into visuals, reports and dashboards in a unified pattern and in less time than anticipated.

These data flows are designed to aid the user organization in the following scenarios:

  • Creating such reusable logic with the raw data that it can be shared and used between various departments within a company. This is because the data flows help in reuse of the basic components of the raw data.
  • Transporting the data into the Azure Data Lake Storage Gen2. It further helps in accessing the other Azure Data Lake Analysis Services.
  • Creating a single wave of truth by forcing the analysts to create reports based on the existing data flows and not the underlying components of the raw data. 
  • Supports the performance of analysis activities as it consists of various cloud and on-premise sources.
  • Preventing analysts from having direct access to the raw data of the organization.

What are different ways to use Data Flows in Power BI:

Power BI dataflow are an interesting capacity of the Power BI Services. It enables the user to reuse the Power Query logic between the various files of the Power BI Data Source files. 

These data flows can be used in the following three different ways:

  • Completely managed by Power BI – In this scenario, the complete process is controlled by the Power BI services. The Power BI Query tool is used to put the raw data in the structured format and the Power BI handles the refresh scheduling procedure. The underlying data is stored within the data lake and is not visible to the customer. 
  • Managed by Power BI with Data Lake – This option is similar to the previous one with only one slight difference. In the second scenario the data lake storage of the user is associated or assimilated with the Power BI account. Here, the data behind the account is viewed using an application called the Azure Storage Explorer. The option is very user friendly from the storage point of view.
  • External Data Flows – In the third option the data is maintained by an outsider tool known as the Azure Databricks or Azure Data Factory. Moreover, the role of Power BI gets reduced to being just the consumer of the data and performing basic analytic functions. The Power BI service is not responsible for updating the information. Although, the data can be imported into the Power BI Data Source files. 

What are the Uses and Advantages of Data Flows:

The Power BI dataflow are used by BI users in order to facilitate the smooth performance of organizational functions within the various departments of the company. The use of these data flows provides a lot of advantages to the user organization.

What are the advantages of Dataflows in an organization:

  1. Using multiple tables in Power Query – In a general scenario, it is difficult to use multiple tables in Power Query. But with the creation of data flows, multiple tables can be used simultaneously. The data flow accesses the data source which enables the easier acquisition of data. This leads to the faster creation of business insights that later get converted to actionable business reports and insights aiding in the performance of functions. 
  2. Scheduling refresh patterns – Data flows can schedule the patterns of refreshing the data from various sources.
  3. Centralizing a data warehouse – Data flows can be very instrumental in building centralized data warehouses. Specially for organizations where large quantities of data can be stored and kept under check.
  4. Running an ETL – Data flows are not exactly designed to do so, but they can run ETL processes very easily and store the information in a different output table. 
Power BI Data Flow

What is the differences between Data Flow and Dataset:

Data flow is a component of Power BI. It is used for transformation purposes but a data set is the object which contains the connection to data tables, deep insights, data source. 

The differences between the two are as follows-

  • Data flow is the replacement of the Power Query for the user. And, dataset is the replacement of the DAX Calculations and relationships.
  • Data flow is the ETL layer and the dataset is the modelling layer.
  • Thirdly, data flow feeds data into data sets but data sets feed data into the visualization.
  • Data flow accesses data directly from source while data sets access data from data flows.
  • Lastly, users of data flows are called data modellers while users of data sets are called report visualizers.

Setting Self-service ETL with Data Flow:

The process of setting up a self-service ETL is as follows- 

  • Step 1 : Select the ETL Workspace tab. This to make sure that the user is on the main folder page.
  • Click on Admin, the Folder and then ManagementSelect the ETLs tab.
  • Choose + and insert a row under custom ETL Definitions. 
  • Replace the default XML in the edit panel.
  • Select Save.
  • Select the ETL Workspace tab. This is done to return to the main dashboard.
  • The new ETL with the chosen name is thus created. The new name is visible under the list called Data Transforms. 

Best Practices of Power BI Dataflow:

Power BI is a self-service data prep application. It provides the user the opportunity to work with data from various sources including the cloud based sources as well as premise data sources. This ecosystem of data can be prepped by creating tables, reports and dashboards from the raw data. Data Flows can be used over almost all Microsoft platforms such as Power Query, Microsoft Dynamics 365 and other Microsoft applications.

Some of the best practices related to dataflows in Power BI include the following:

  1. Using Power Query to the fullest to yield its benefits.
  2. Secondly, Utilizing computed entities like tables and reports in data flow.
  3. Creating complex patterns of data follows to deal with large volumes of data.
  4. Creating data flows in the common data model.
  5. Increasing the refresh frequency of the data in the data flows.
  6. Scheduling the refresh pattern according to the need of the organization.
  7. Speeding up the data transformation process by utilizing the source system.
  8. Lastly, Expanding the operations of the tables of data.

What are the features of Power BI dataflow Premium:

The Data Flows are supported only for the users of Power BI Pro and Power BI Premium. Although, between these two, some features are available only to the Premium users. The features available with the Premium subscription are as follows:-

  • An enhanced computing engine
  • Direct Query
  • Computed entities
  • Linked Entities
  • Incremental refresh

These features can be described in details in the following manner –

  1. Enhanced Computing Engine – The model-driven calculation engine is made available to the users of the Power BI Premium. Using this they can use the data flows to their optimum capacity. It reduces the refresh time required to run a single ETL process. The Direct query can be performed on top of the entities.
  2. Direct Query – Secondly, Direct Query can be used to connect to data directly. This saves the user the trouble to import the data before using it for analytic purposes.
  3. Computing Entities – The user can perform in-storage computations related to the raw data while using Power BI dataflow. This makes it easier to use data flows by analysts.
  4. Linked Entities – This enables the user to link or reference the existing data flows. After this the user can either compute upon the existing data flow or create a single truth source. It can later be reused with other data flows.
  5. Incremental Refresh – Lastly, the settings of incremental refresh enables the system to refresh incrementally instead of pulling all the data with every refresh.

Power BI for Business Intelligence: An EPC Group Approach

The EPC group is dedicated towards establishing Power BI as one of the leading services in the field of business intelligence. Microsoft provides an array of services and tools and the same are consulted by the members of the group thoroughly. In the competitive market, if an organization wishes to convert their system into an Microsoft 365 system, the consulting services of the EPC group are an excellent choice. 

As far as the Power BI solutions are concerned, the group has been leading the arena of consultancy regarding POWER BI for a long time. Also, the consultants of this group provide detailed consultancy and help with regards to the deployment and functioning of the Power BI tools. It also aids the organizations to use the data metrics in formulating insights, implanting best Governance practice and reaping the best benefits out of the business intelligence services of Microsoft BI.

Conclusion:

Summarizing the above, it can be said that Power BI dataflow are a benefit for the user organization and Microsoft BI solution is the best choice for it.