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Welcome to this Microsoft Power BI Business Intelligence Training Course for Beginners. This is a Beginner Course on Power BI, Business Intelligence & Data/Business Analysis with Microsoft Power BI.
This is a Power BI introductory course video. In this we will be seeing what is Power BI software? What are the features of Power BI? We will also take a look at Power Bi components and try to compare the recent market trends on the popularity of Power BI and Tableau to compare its popularity. Power Bi is a business intelligence tool that helps to visualize the data in the form of reports and dashboard.
👨🏼💻Contents👨🏼💻
00:00:01 1 - Introduction to Power BI | Getting Started
00:10:23 2 - How to Install Power BI on Windows 10
00:21:17 3 - How To Import Data From Data Source in Power BI
00:32:47 4 - Donut Chart, Line Chart and Pie Chart in Power BI
00:44:02 5 - Data Table Filters
00:55:09 6 - How to Create and Use Maps in Power BI
01:05:50 7 - Filled Map in Power BI
01:17:10 8 - Pie Chart and Map in Power BI
01:27:08 9 - Creating Tables in Power BI
01:38:00 10 - Formatting Tables in Power BI
01:46:02 11 - Conditional Formatting and Aggregation in Tables
01:56:25 12 - How to create Matrices in Power BI
02:06:37 13 - Cards in Power BI
02:17:01 14 - Filtering the cards in Power BI
02:27:45 15 - Drill through and slicers in Power BI
02:38:22 16 - Buttons and Actions in Power BI
02:48:52 17 - Creating A Sample Report In Power BI
02:59:27 18 - Publishing Report in Power BI service
03:07:25 19 - Power Query to Concatenate Columns
03:17:45 20 - Transforming Data with Power Query
03:29:13 21 - Working with Dates in Power Query
03:39:19 22 - Time Functions in Power Query
03:50:35 23 - Power Query on Numerical Data
04:01:09 24 - Append Query in Power Query Editor
04:12:00 25 - Appending tables with different columns
04:22:37 26 - Extracting data from multiple Excel Workbooks
04:33:44 27 - Column From Example Applications 01
04:44:36 28 - Column From Example Applications 02
04:54:47 29 - Conditional Column Application 01
05:04:59 30 - Conditional Columns Application 02
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The short answer, for most of you, is no. However, the complexity and capability of the products could be beneficial depending on what type of position or organization you work in.
In my effort to answer this common question about Power BI I researched the following:
– Power BI Desktop Gateway
– Syncing on-prem SQL server data
– Syncing SharePoint Online list data
– Syncing data from an Excel workbook
– Building, and sharing a dashboard
– Inserting a Power BI visualization into PowerPoint
To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training
The feature spread above gave me the opportunity to explore the main features of Power BI which break down as:
– Ingesting data, building a data set
– Creating dashboard or reports with visualizations based on that data
In a nutshell Power BI is a simple concept. You take a data set, and build visualizations that answer questions about that data. For example, how many products have we sold in Category A in the last month? Quarter? Year? Power BI is especially powerful when drilling up or down in time scale.
And there are some interesting ways to visualize that data:
However, there are a number of drawbacks to the current product that prevented me from being able to fold these visualizations into our existing business processes.
The most inspiring Power BI demo I saw at a Microsoft event showed a beautiful globe visualization within a PowerPoint presentation. It rendered flawlessly within PowerPoint and was a beautiful, interactive way to explore a geographically disparate data set. I was able to derive conclusions about the sales data displayed without having to look at an old, boring chart.
During the demo, nothing was mentioned about the technology required to make this embedded chart a reality. After looking into the PowerPoint integration I learned that not only was the add-in built by a third party, it was not free, and when I signed up for a free trial the add-in could barely render my Power BI visualization. The data drill up/down functionality was non-existent and not all of the visualizations were supported. Learn more from Power bi online course
Folks in our organization spent 50% of their time in Outlook, and the rest in SharePoint, OneNote, Excel, Word, and the other applications needed for producing documents, and other work. Adding yet another destination to that list to check on how something is doing was impossible for us. Habits are extremely hard to change, and I see that consistently in our client’s organizations as well.
Because I was not able to fold in the visualizations with the PowerPoint decks we use during meetings, I had to stop presentations in the middle, navigate to Internet Explorer (because the visualizations only render well in that browser), and then go back to PowerPoint once we were done looking at the dashboard.
This broke up the flow of our meetings, and led to more distractions. I also followed up with coworkers after meetings to see if they ever visited the dashboard themselves at their desk. None of them had ever navigated to a dashboard outside of a meeting.
Creating visualizations that cover such a wide variety of data sets is difficult. But, the Excel team has been working on this problem for over 15 years. When I import my SharePoint or SQL data to Excel I’m able to create extremely customized Pivot Tables and Charts that show precisely the data I need to see.
I was never able to replicate visualizations from Excel in Power BI, to produce the types of visualizations I actually needed. Excel has the ability to do conditional formatting, and other customizations in charts and tables that is simply not possible with Power BI. Because of how generic the charts are, and the limited customization it looks “cool” without being functional.
In conclusion, if you have spare time and want to explore Power BI for your organization you should. However, if you are seriously thinking about how you can fold this product into your work processes, challenge yourself to build a dashboard and look at it once a week. See if you can keep that up for a month, and then think about how that change affected your work habits and whether the data analysis actually contributed value each time. At least half of you will realize that this gimmicky product is fancy, but not actually useful.
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In your search for a Business Intelligence (BI) or data visualization tool, you have probably come across the two front-runners in the category: Power BI and Tableau. They are very similar products, and you have to look quite closely to figure out which product might work the best for you. I work for Encore Business Solutions; a systems partner that specializes in both Power BI and Tableau. We’ve seen more than a few scenarios in which Tableau was being used when the company really should have gone with Power BI, and vice-versa. That was part of the inspiration for this side-by-side comparison.
Unfortunately, the internet is full of auto-generated and biased pages regarding which product trumps the other. The truth is, the best product depends more on you, your organization, your budget, and your intended use case than the tools themselves. It is easy to nit-pick at features like the coding language that supports advanced analysis, or the type of maps supported — but these have a minimal impact for most businesses. I’m going to do my best to stay away from these types of comparisons.
To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training
In writing this comparison, I did a lot of research. The result was more than just this article: I also created a tool that can generate a recommendation for you based on your response to a short questionnaire. It will generate a score for both Power BI and Tableau, plus provide a few other things to think about.
Tableau Software
Founded in 2003, Tableau has been the gold-standard in data visualization for a long time. They went public in 2013, and they still probably have the edge on functionality over Power BI, thanks to their 10-year head start. There are a few factors that will heavily tip the scales in favour of Tableau, which I’ll cover in the next few paragraphs.
Tableau: Key Strengths
Let’s make one thing clear from the start: if you want the cream of the crop, all other factors aside, Tableau is the choice for you. Their organization has been dedicated to data visualization for over a decade and the results show in several areas: particularly product usability, Tableau’s community, product support, and flexible deployment options. The range of visualizations, user interface layout, visualization sharing, and intuitive data exploration capabilities also have an edge on Power BI. Tableau offers much more flexibility when it comes to designing your dashboards. From my own experience, Tableau’s functionality from an end-user perspective is much farther ahead of Power BI than the Gartner Magic Quadrant (below) would have you believe.
Tableau built their product on the philosophy of “seeing and exploring” data. This means that Tableau is engineered to create interactive visuals. Tableau’s product capabilities have been implemented in such a way that the user should be able to ask a question of their data, and receive an answer almost immediately by manipulating the tools available to them. I have heard of cases in which Tableau actually declined to pursue the business of a customer in the scenario that the customer didn’t have the right vision for how their software would be used. If you just want something to generate reports, Tableau is overkill.
Tableau is also much more flexible in its deployment than Power BI. You can install the Tableau server in any Window box without installing the SQL server. Power BI is less flexible which I will discuss in Power BI Weaknesses.
Tableau can be purchased on a subscription license and then installed either in the cloud or an on-premise server.
Finally, Tableau is all-in on data visualization, and they have their fingers firmly on the pulse of the data visualization community’s most pressing desires. You can expect significant future improvements in terms of performance when loading large datasets, new visualization options, and added ETL functions.
Tableau Weaknesses
Unfortunately, Tableau comes at a cost. When it comes to the investment required to purchase and implement Tableau – 9 times out of 10 it will be more expensive than Power BI, by a fair margin. Often, Tableau projects are accompanied by data-warehouse-building endeavours, which compound the amount of money it takes to get going. The results from building a data warehouse and then hooking up Tableau are phenomenal, but you’ll need an implementation budget of at the very least $50k – plus the incremental cost of Tableau licenses. Learn more from Power bi online course
Of course, a data warehouse is not a requirement. Tableau connects to more systems out-of-the-box than Power BI. However, Tableau users report connecting to fewer data sources than most other competing tools. Overall, considering the investment required to implement a data warehouse is a worthy indicator of the commitment required to get the most out of Tableau.
Power BI
Power BI is Microsoft’s data visualization option. It was debuted in 2013, and has since quickly gained ground on Tableau. When you look at Gartner’s most recent BI Magic Quadrant, you’ll notice that Microsoft is basically equal to Tableau in terms of functionality, but strongly outpaces Tableau when it comes to “completeness of vision”. Indeed, the biggest advantage of Power BI is that it is embedded within the greater Microsoft stack, which contributes to Microsoft’s strong position in the Quadrant.
Power BI: Key Strengths
Though Tableau is still regarded by many in the industry as the gold standard, Power BI is nothing to scoff at. Power BI is basically comparable to all of Tableau’s bells and whistles; unless you care deeply about the manifestation and execution of small features, you’re likely to find that Power BI is fully adequate for your BI needs.
As I mentioned, one of the biggest selling points of Power BI is that it is deeply entrenched in the Microsoft stack – and quickly becoming more integrated. It’s included in Office 365, and Microsoft really encourages the use of Power BI for visualizing data from their other cloud services. Power BI is also very capable of connecting to your external sources.
Because Power BI was originally a mostly Excel-driven product; and because the first to adopt Microsoft products are often more technical users, My personal experience is that Power BI is especially suitable for creating and displaying basic dashboards and reports. My own executive team really likes being able to access KPIs from the Office portal, without having to put much time into the report’s creation, sharing, and interactivity.
Power BI’s biggest strength; however, is its rock-bottom cost and fantastic value. For a product that is totally comparable to the category leader, it’s free (included in Office 365) for basic use and $10/user/month for a “Pro” license. This increases adoption of the product as individuals can use Power BI risk-free. For companies that don’t have the budget for a large Business Intelligence project (including a data warehouse, dedicated analysts, and several months of implementation time), Power BI is extremely attractive. Companies that are preparing to “invest” in BI are more likely to add Tableau to their list of strongly considered options.
Power BI is available on a SaaS model and on-premise; on-premise is only supported by Power BI Premium licensing.
Microsoft is also investing heavily in Power BI, and they’re closing the small gaps in their functionality extremely fast. All of those little issues some users have with Power BI are going to disappear sooner rather than later.
Power BI Weaknesses
As I’ve mentioned, Tableau still has the slight edge on Power BI when it comes to the minutiae of product functionality; mostly due to their 10-year head start. But perhaps Power BI’s greatest weakness is its lack of deployment flexibility. For Power BI on-premise you need to install the Power BI Report Server as well as the SQL Server.
I also mentioned that Tableau works well for users with large amounts of data and for users that want on-premise systems. You should be aware that there are some new features being added to Power BI via Power BI Premium that help catch Microsoft up to Tableau in the areas of large datasets and on-premise capabilities – but Power BI Premium adds significant cost, and these features are relatively new. Tableau still reigns in these areas.
To get more knowledge of Power BI and its usage in the practical way one can opt for Power bi online training Hyderabad from various platforms. Getting this knowledge from industry experts like IT Guru may help to visualize the future graphically. It will enhance skills and pave the way for a great future.
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the Business Intelligence (BI) world has been moving towards self-service BI. As expected, several vendors created tools empowering regular users to gain insights from their data. Among the many, there is Power BI. Nowadays, users want to understand the differences between Product X and Power BI.
One of the most common questions in conferences and user group sessions is likely, “can you provide a comparison between this product and Power BI?”.
The answer is almost always, “No, I cannot compare them, because they are too different”. First, one needs to understand the deep difference between Power BI and most other reporting tools on the market. Only later does a comparison make any sense. As a matter of fact, I think Power BI can be compared to only a few products on the market today. I would like to add my point of view to the discussion.
To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training
Indeed, Power BI is a tremendously powerful data modeling tool that happens to come with a pretty face; most other products are beautifully crafted reporting tools with a pretty face. The only thing they have in common is the pretty face. If you stop at what they have in common, you are only comparing a small fraction of the whole product, and that would be unfair.
To go further, a deeper understanding of basic BI concepts is needed.
Beware: this article is biased. I love Power BI and I make my living out of it. Nevertheless, I am a BI professional; I started working with Business Intelligence many years ago and I have gathered experience that I can share. I will try to be as fair as I can in this post, as my goal is not to provide a comparison with any tool. The goal of this post is to help you understand what you really need to evaluate when making (or reading) any comparison between different BI products.
At the top level, any Business Intelligence solution is composed of three layers:
Raw data: these are the data sources that one wants to analyze. Raw data comes as is.
Semantic model: this is where data is re-arranged to optimize it for analysis. Here you also define the calculations required by the reports.
Reports: these are the nice dashboards you can build with the tool.
Power BI manages all three layers: you start from raw data, you can build a semantic layer, and finally you prepare reports. Most other reporting tools are focused on the last layer and are limited in the previous two. In other words, they are missing the capability to build a real semantic layer. It is important to clarify what a semantic layer is, to understand what you would miss by choosing a different product.
In the old ages of BI, there was a clear separation between users and developers. A BI developer would build a project to help users extract insights from their data, and build reports. Users did not need to understand tables, relationships, or calculations. The developer oversaw shaping the tables, providing predefined calculations and giving sensible names to entities. Leveraging the semantic model, users did not have to know DAX, MDX or SQL.
A semantic model lets users interact with business entities like customers, sales, and products. Users would place those entities in reports made with Excel or with other reporting tools. Regular users were happy with just Excel and a Pivot Table. More advanced users wanted more powerful tools, and this led to the creation of several reporting tools with their ad-hoc programming language to create more advanced formulas. Regardless, the important thing is that no matter how powerful those tools are, they were still reporting tools based on the existence of a previously crafted semantic model. No semantic model, no reporting.
Picture this: a BI tool lets a developer build a semantic model. A reporting tool lets a user build a report on top of an existing semantic model. You need both to create a BI solution.Learn more from Power BI online course
Unfortunately, building a BI project takes time. Users were hungry for reports. This led to the start of the Self-Service BI era. Self-service BI is the idea of users building reports themselves, to reduce development time and to build a democratic knowledge about data. Sounds cool and terrifying at the same time.
Anyway, this is where we are today. Obviously, driven by the market several vendors started to build self-service BI tools. A few new products appeared on the market. Rather, existing tools evolved into new ones, targeting self-service BI. Keep in mind: any self-service BI tool requires the functionalities to build both the semantic model and the report in the same tool. Thus, depending on where you start, you have two options to have an existing product evolve into a self-service product:
If you already have a semantic model tool, you need to add reporting capabilities. You need to make it easier to use, because the target is no longer a BI professional but a regular user instead.
If you already have a reporting tool, you need to add the capability to build a semantic model because your users need to massage the data and build calculations on top of the resulting model.
In both cases, in the end you obtain a tool that mixes the capabilities to create a semantic model and to build reports. After this first step, you can add tons of different features like sharing with other users, building wizards to automatically connect to other services, improving the formula language and so on. But the core is always the same: a semantic model and a reporting tool, bound together in a nice package.
Even though we consider Power BI to be a new product, it is actually the evolution of Power Pivot and Analysis Services Tabular (semantic model), Power Query (querying tool), and Power View (the first version of the reporting tool released with Excel and SharePoint). Other vendors took similar steps, with different starting points. It is fair to say that several vendors started from a reporting tool, adding the semantic model to it.
Now, if you need to compare two BI tools, you need to compare at least these two features: the semantic model and the tools to build a report.
Say you want to compare Product X with Power BI; you show me how easy it is to build a gorgeous report on top of an SQL view, much easier and much more powerful than Power BI. Cool, but you are only comparing a fraction of both products. Reporting-wise, sure, Product X is better than Power BI. But there are other considerations: can you load multiple tables in Product X? Can you build relationships between them? Can you use a programming language to author complex calculations that involve scanning different tables? All these operations belong to the semantic model. A fair comparison needs to apply to all the features.
This is what Power BI offers you:
Power Query – a data transformation tool which is easy to use and yet incredibly powerful. It can load virtually anything and join data from different sources.
A modeling environment where you can build different kinds of relationships between tables and build powerful models. It does not hurt that it runs on top of one of the fastest databases I have ever seen.
DAX – a programming language which is not easy, but lets you author nearly any query and calculation. Yes, on this I am biased for sure!
Power BI – a reporting engine which is very good in building dashboards and reports. It can also be extended with custom visuals and third-party products.
Then, there is web-based reporting and sharing, a mobile experience, the ability to load from nearly any data source in the cloud or on premises and many other useful features. Yet, the core is composed of the four features above. If you want to compare apples to apples, you need to compare at least these four parts. Be mindful: you need all of them. A tool that requires you to build a single table because it does not let you relate two tables is nothing but a nice reporting tool. Comparing it to Power BI does not make much sense to me.
Moreover, it does not come by chance that to learn Power BI, one needs to learn new programming languages. Each feature has its own language, and this is just the right thing to have.
Finally, reporting. Reporting is only the last part, even though it is the most visible one. You might find other products are better than Power BI when it comes to reporting. This is fine, if you are aware that you are only comparing a fraction of Power BI with the whole of Product X.
I love Power BI, and I would really love to see a fair comparison between Power BI and any other product. We could learn a lot from the topic. But for it to be fair, it cannot just be based on how easy it is to build a pie chart (just kidding! You are not using a pie chart, are you?). One needs to evaluate everything both products have to offer.
To get in-depth knowledge of this technology and to develop skills to make a great career in this regard one can opt for Power BI online training Hyderabad.
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Every month, we bring you news, tips, and expert opinions on Power BI? Do you want to tap into the power of Power BI? Ask the Power BI experts at ArcherPoint.
Power BI Desktop – Feature List
More exciting updates for August—as always:
To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training
Power BI Developer Update
And the updates continue—this time, for developers:
Multiple Data Lakes Support For Power BI Dataflows
And if that’s not enough, Microsoft also announced improvements and enhancements to Azure Data Lake Storage Gen2 support inside Dataflows in Power BI. Improvements and enhancements include: Support for workspace admins to bring their own ADLS Gen2 accounts; improvements to the Dataflows connector; take-ownership support for dataflows using ADLS Gen2; minor improvements to detaching from ADLS Gen2. Changes will start rolling out during the week of August 10. Read more on multiple data lakes support in Power BI dataflows.
To get more knowledge of Power BI and its usage in the practical way one can opt for Power bi online training Hyderabad from various platforms. Getting this knowledge from industry experts like IT Guru may help to visualize the future graphically. It will enhance skills and pave the way for a great future.
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JIRA Software provides bug tracking, issue tracking, and project management capabilities for teams and organizations. The JIRA content pack for Power BI helps you quickly import JIRA data so you can get an instant dashboard to analyze workloads, see how quickly you’re resolving issues, visualize velocity over time, and more. Power BI helps you quickly filter by project or component to generate new insights into your JIRA data.
To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training
To connect to the JIRA content pack, simply choose JIRA from the list of available content packs. You will be asked to provide your JIRA URL and credentials. Once the connection has completed, Power BI will automatically create an out-of-the-box dashboard, report, and dataset with data from JIRA.
dashboard
The dashboard for the JIRA content pack shows you key metrics about your workloads, velocity over time, and the breakdown of your bugs and issues by status and assignee. Clicking on any of the dashboard tiles will open the JIRA content pack report, where you can interact and explore your data.
You can slice the data in the report using the ‘Item Type’ slicer on the top, so you can find exactly the items you are looking for. Power BI reports are interactive, so if you select a ‘Fix Version’, a ‘Component’, or an ‘Assignee’, the rest of the report page will update per the selection.Learn more from Power BI online course
The report has a second page that focuses on the velocity of creating and resolving issues, and also shows the list of recently resolved items.
After the initial import, the dashboard and the reports continue to update daily so you are always seeing up-to-date data. You can control the refresh schedule on the dataset, and configure it to refresh at the exact times you choose.
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