best practices
9 TopicsPower BI Wednesday Lunch 'n' Learn
Synopsis: This is a "Lunch n Learn" series called Power BI Wednesday, each Wednesday we will hold a short lunchtime review and discussion on a particular topic. POWER BI ADOPTION SERIES The goal of this series of articles is to provide a roadmap. The roadmap presents a series of strategic and tactical considerations and action items that directly lead to successful Power BI adoption, and help build a data culture in your organization. Advancing adoption and cultivating a data culture is about more than implementing technology features. Technology can assist an organization in making the greatest impact, but a healthy data culture involves a lot of considerations across the spectrum of people, processes, and technology. Host: Greg Nash LinkedIn Sponsors: Servian Pty Ltd (http://www.servian.com/) A big thank you goes out to our sponsor, Servian, for their support of this Meetup; providing the venue as well as drinks for attendees. Servian is regarded as one of Australiaโs most trusted data consultancies and IT advisors. Major organizations have come to rely on our thought leadership on Data Integration, Analytics, Data Warehousing, Application Development as well as the value we provide in support and maintenance. Servian has a proven track record in delivering tailored programs, technological processes, and specialist advice that boost business capabilities, operational performance, and much more. Sirius Technology (https://www.siriuspeople.com.au/) A big thank also to our co-sponsor, Sirius Technology, for their ongoing support of our Meetup and providing us with food for each event. Sirius Technology recruits across all Technology Disciplines from Development (Front and back-end), Testing, Network, and Security, Project Services (PM's, BA's, Project Coordinators) & Data - across all technology stacks. Power BI Mentoring Power BI Melbourne Host and Data Platform MVP Greg Nash now offer 1 on 1 mentoring for Power BI use the link below to make an inquiry: Click here to enquire about mentoring813Views0likes0CommentsSome of the visualization best practices to create a Power BI report
Join us for the next #FREE #ONLINE session of the ๐๐๐ซ๐ฌ๐ข๐๐ง ๐๐จ๐ฐ๐๐ซ ๐๐ ๐๐ฌ๐๐ซ ๐๐ซ๐จ๐ฎ๐ฉ with a great speaker, Hossein Seyedagha. ๐๐๐ค๐ฅ๐๐: Some of the visualization best practices to create a Power BI report ๐๐๐๐๐ฉ๐๐ฃ๐ ๐ก๐๐ฃ๐ (๐๐ ๐๐๐๐ข๐จ): https://bit.ly/3OWShAq ๐๐๐๐ญ๐: ๐๐-๐๐๐ฒ-๐๐๐๐ โฐ๐๐ข๐ฆ๐: ๐ฒ:๐ฌ๐ฌ ๐ฃ๐ ๐๐๐ฆ๐ง ๐๐๐ง๐จ๐๐๐ฃ ๐๐ฝ๐๐๐- ๐๐๐๐ง๐ค๐จ๐ค๐๐ฉ ๐พ๐ค๐ข๐ข๐ช๐ฃ๐๐ฉ๐ฎ: https://bit.ly/3IAg7xT ๐๐๐ฃ๐ ๐๐๐๐ฃ: https://bit.ly/32tGkif ๐๐๐ก๐๐๐ง๐๐ข ๐พ๐๐๐ฃ๐ฃ๐๐ก: https://t.me/PersianPBIUG ๐๐ค๐ช๐๐ช๐๐: https://bit.ly/3hk20RL We speak in #Farsi in this session.137Views0likes0CommentsPower BI Development Best Practices
In this session, Soheil will show you some Power BI development and design best practices, covering topics such as Power Query, Data Modeling, DAX, Data Visualization, Star schema, Data Type, and Relationships,... ๐๐๐๐ฉ๐๐ฃ๐ ๐ก๐๐ฃ๐ (๐๐ ๐๐๐๐ข๐จ): https://bit.ly/3CYM4A8 ๐๐๐ง๐จ๐๐๐ฃ ๐๐ฝ๐๐๐- ๐๐๐๐ง๐ค๐จ๐ค๐๐ฉ ๐พ๐ค๐ข๐ข๐ช๐ฃ๐๐ฉ๐ฎ: https://bit.ly/3IAg7xT ๐๐๐ฃ๐ ๐๐๐๐ฃ: https://bit.ly/32tGkif ๐๐๐ก๐๐๐ง๐๐ข ๐พ๐๐๐ฃ๐ฃ๐๐ก: https://t.me/PersianPBIUG ๐๐ค๐ช๐๐ช๐๐: https://bit.ly/3hk20RL Language: Persian - Farsi660Views0likes0CommentsPower BI Development Best Practices - Part 2
Here is the video of the first part of this session, which was held on 20-Oct-22: https://youtu.be/ocDT_GFOvoE In this session, Soheil will show you some Power BI development and design best practices, covering topics such as Power Query, Data Modeling, DAX, Data Visualization, Star schema, Data Type, and Relationships,... ๐๐๐๐ฉ๐๐ฃ๐ ๐ก๐๐ฃ๐ (๐๐ ๐๐๐๐ข๐จ): https://bit.ly/3CYM4A8 ๐๐๐ง๐จ๐๐๐ฃ ๐๐ฝ๐๐๐- ๐๐๐๐ง๐ค๐จ๐ค๐๐ฉ ๐พ๐ค๐ข๐ข๐ช๐ฃ๐๐ฉ๐ฎ: https://bit.ly/3IAg7xT ๐๐๐ฃ๐ ๐๐๐๐ฃ: https://bit.ly/32tGkif ๐๐๐ก๐๐๐ง๐๐ข ๐พ๐๐๐ฃ๐ฃ๐๐ก: https://t.me/PersianPBIUG ๐๐ค๐ช๐๐ช๐๐: https://bit.ly/3hk20RL Language: Persian - Farsi232Views0likes0CommentsFabric + Databricks: Real-World Architecture Patterns
Join us at the Microsoft Office in Ottawa for a user group meetup exploring how Microsoft Fabric and Databricks can work together to deliver modern, scalable data architectures. This session will dive into real-world architecture patterns that bring these two platforms into playโcovering where each excels, how to integrate them effectively, and strategies for creating a unified data foundation that drives analytics, AI, and business insights. What you will gain: -A clear understanding of when to leverage Fabric vs. Databricks -Practical examples of hybrid architecture patterns in enterprise scenarios -Insights into governance, performance, and cost considerations when combining both tools -Networking opportunities with peers tackling similar challenges in data modernization Who should attend: Data engineers, architects, BI developers, AI/ML practitioners, and technology leaders looking to deepen their understanding of Microsoft Fabric and Databricks. Seats are limited, so secure your spot early, and come hungry for both data insights and pizza. Hosted by Revolution Data Platforms365Views0likes0CommentsNYC Fabric Community โ Featured Speaker: Joey DโAntoni | Architecture Framework
Joey D'Antoni: Building the Fabric Well-Architected Framework What is the best way to architect Microsoft Fabric workspaces? How should your network and security models be designed for scale and governance? In this session, youโll explore best practices across Microsoft Fabric, including naming standards, deployment strategies, capacity management, security, and overall platform governance. Key topics include: Best practices for deployment and management of Fabric environments Implementing standards, controls, and governance models Designing enterprise-ready architecture for Microsoft Fabric This session is ideal for anyone looking to build a scalable, secure, and well-architected Fabric implementation. It will also be valuable for those interested in strengthening best practices around standardization, performance, and long-term operational stability, as well as experienced architects from other data platforms exploring Microsoft Fabric.442Views0likes0CommentsIF/SWITCH measure performance
Hi, I have a general question about the best way to write if/switch measures. Is any of the following examples (1 and 2) more efficient than the other? 1) if_measure = IF(condition_measure = value1, [measure1], [measure2]) switch_measure = SWITCH(condition_measure, value1, [measure1], value2, [measure2], [measure3]) 2) if_measure = IF(condition_measure = value1, DAX code for measure 1, DAX code for measure 2) switch_measure = SWITCH(condition_measure, value1, DAX code for measure 1, value2, DAX code for measure 2, DAX code for measure 3) Thanks!472Views0likes1CommentKeeping corresponding tier data sources aligned with 3-tier development environments on Report Svr
We have a 3-tier Power BI RS environment (Dev/Test/Prod) and corresponding SQL database environments with an organizational restriction that apps in 1 level can only access data sources in the same level. For example, the Prod app tier can only access ProdSvr\Sales, Test app tier accesses TestSvr\Sales and so on. PBI developers can only publish into the Dev environment and the DBA team controls the promotion process through Test and Prod. Is there anyway to abstract the actual data source identifier and include a parameter so the PBIX doesn't have to be manually changed to match the data source with the corresponding environment? Or is there another approach to support this process?862Views0likes2CommentsHelp with Power BI query optimization
Hi All, I need your help to optimize this power BI query. Currently, the query works very slow (query doesnt return result even after 3 days). let Source = Sql.Database("chvpkw8ahsv117", "hmparsdmd"), Staging_Transactions_Summary = Source{[Schema="Staging",Item="Transactions_Summary"]}[Data], #"Removed Other Columns" = Table.SelectColumns(Staging_Transactions_Summary,{"TransactionDate", "TransactionYYMM", "LocationID", "CardTypeDesc", "FuelTypeDesc", "td_acct_no", "PumpNumber", "IndoorOutDoor", "NFCUsed", "PilotSites", "TransactionCount", "Gallons", "FuelDollars"}), #"Filtered Rows" = Table.SelectRows(#"Removed Other Columns", each ([IndoorOutDoor] = "Outdoor") and ([PilotSites] = "Yes") and ([NFCUsed] = "No")), #"Changed Type" = Table.TransformColumnTypes(#"Filtered Rows",{{"LocationID", Int64.Type}}), #"Sorted Rows" = Table.Sort(#"Changed Type",{{"LocationID", Order.Ascending},{"td_acct_no", Order.Ascending},{"TransactionDate", Order.Ascending}}), #"Reordered Columns" = Table.ReorderColumns(#"Sorted Rows",{"LocationID", "td_acct_no", "TransactionDate", "CardTypeDesc", "FuelTypeDesc", "PumpNumber", "IndoorOutDoor", "NFCUsed", "PilotSites", "TransactionCount", "Gallons", "FuelDollars"}), #"Added Index" = Table.AddIndexColumn(#"Reordered Columns", "Index", 1, 1), #"Merged Queries" = Table.NestedJoin(#"Added Index",{"LocationID", "td_acct_no","Index"},#"Staging Transactions_Summary",{"LocationID", "td_acct_no","Index"},"NewColumn",JoinKind.LeftOuter), #"Expanded NewColumn" = Table.ExpandTableColumn(#"Merged Queries", "NewColumn", {"TransactionDate"}, {"NewColumn.TransactionDate"}), #"Renamed Columns" = Table.RenameColumns(#"Expanded NewColumn",{{"NewColumn.TransactionDate", "NextTransactionDate"}}), #"Filtered Rows1" = Table.SelectRows(#"Renamed Columns", each ([NextTransactionDate] <> null)), #"Added Custom" = Table.AddColumn(#"Filtered Rows1", "DaysFromLastTrans", each if [NextTransactionDate] <> null then Duration.Days(Duration.From([NextTransactionDate]-[TransactionDate])) else null), #"Grouped Rows" = http://itopssqldb.database.windows.net(#"Added Custom", {"LocationID", "TransactionYYMM", "td_acct_no", "CardTypeDesc", "FuelTypeDesc", "IndoorOutDoor", "NFCUsed"}, {{"TransactionCount", each Table.RowCount(_), type number}, {"TotalGallons", each List.Sum([Gallons]), type number}, {"TotalFuelDollars", each List.Sum([FuelDollars]), type number}, {"TotalDays", each List.Sum([DaysFromLastTrans]), type number}}), #"Added Custom1" = Table.AddColumn(#"Grouped Rows", "AvgDaysBetweenTrans", each [TotalDays]/[TransactionCount]) in #"Added Custom1"Solved7.9KViews0likes4Comments