Shakti Kumar

Yeah. Hello. Uh, my name is Shakti Kumar. Uh, thank you so much for providing me this opportunity. So a brief introduction about myself would be like, uh, I'm a computer science engineer, um, by education, and, currently, I'm working as a senior business analyst at Dell Technologies. I'm associated with Dell Technologies from almost 9 and a half years. And, uh, being a a part of senior member, uh, in the b BI team of Dell Technologies, My prime role and responsibility is to drive sales of Dell, the NCP products across global across globe, driving and designing a different strategies about sales, how to increase sales across globe, collaborating with stakeholders, the project managers understanding their requirement, get in touch with the report users, as in, like, the senior leaderships and designer sales dashboard as per the requirements, What are the KPIs defining and designing new KPIs, which is, uh, important for the business to measure the multiple campaigns running across globe. Apart from this, uh, I do being a senior member of the team, I do, uh, manage our men I do manage the junior college, and my prime role and responsibility is to drive them across, um, um, the sales campaign and make them understand, uh, what is the vision and the mission of our, um, the work, what we are do doing, and how it is improving our in order to drive the sales of building and secured products across globe. So that's about myself. Thank you so much.

So there are different methods that I will use to improve for the query performance in a SQL database. So first of all, I'll see, um, what is the exact issue which is creating a performance, uh, what is what is the exact, uh, I can say, uh, the problem, which is creating a performance issue in our database and in our report as well. Then after identifying that, we have a performance analyzer so that we can get to know which all the graphs whether the graphs or charts or any visualization is creating any performance issue. So or is there any kind of, uh, ways we can fold the query by using a query folding technique in Power BI? And if you are doing any, uh, calculations, like, uh, creating conditional columns or anything, like, before putting the data into the Power BI dataset so that we can remove those unnecessary steps and try to import the the data in more, uh, required format, what we need in our database. So these are the things that I will use. I will try to remove the unnecessary data, which is not a part of the leadership and unnecessary, it's taking its space. So, yeah, these are the techniques. These are the method that I will use to improve the SQL performance or, uh, query performance in our SQL database. Thank you so much.

So, generally, instead of, uh, the method, there are basically 2 methods that Power BI provides the user in order to import the data. 1 is import query, another 1 is direct query. So if I need to enhance the efficiency of data retrieval in Power BI, I will try to use, uh, import query because it will it is it it it is based on the historical data and not on the live data. So we can do anything, and it will be we can do any kind of modification in the data while before loading it into the Power BI dataset. And it has nothing to do with the live data, so it will make, uh, the data retrieval, uh, faster as compared to what we are going to use, uh, the direct query option. So for all these above 3 database, like, for me, Microsoft SQL Server, postpaid SQL, SQL, or Oracle. I'm gonna use, uh, a kind of, uh, direct query from the database in order to retrieve the data to Power BI. Thank you.

Whatever. So when I'm working with any of the complex tax expiration, so first of all, it depends upon, like, what kind of complex city I'm going to use for the tax expiration. It it depends on the business requirement, like, uh, what is the actual, uh, use and, uh, what is the actual data that we want to put in our dashboard. So that's how we define the complexity of any DAX expression. And when it comes to communicate to our team when working with, uh, any of the DAX expressions so, basically, the key consideration would be to why we are using that particular DAX expression and what is the need to use the DAX expression, uh, if we are not able to get it from directly from our data. So, definitely, we are losing the DAX expression. So, yeah, these are the metrics that I will, uh, uh, these are the key points that I will consider in order to explain to my team members. And apart from that, there is there are few more things I would like to, uh, um, inform my team members that whenever we are creating any DAX equation, we will try to make sure that lesser the, uh, what I can say, dependency of lesser the dependency on any column or, like, not using multiple, uh, data to calculate 1 single DAX expression, which will lead to kind of, like, complexity in the relationship. So these are the, uh, things that I will consider when I'm trying to create any DAX expression or when I'm trying to communicate the same to my team whole team members as well when we are working with any kind of, like, complex DAX expressions. Thank you so much.

So, generally, I would like to give this example of, uh, which is very much, uh, directly linked to my day in and day out work. So whenever we try to provide any kind of a security, uh, layer or any kind of, uh, access control to our Power BI dashboard, So, basically, there are, uh, multiple things that we check, like, uh, whether are we going to provide the security on the basis of hierarchy, or it's kind of, like, page level security that we are going to provide or this kind of, like, low level security that we are going to provide to our stakeholders. So these are the, uh, things or the requirement or the key consideration that we will, uh, check with our stakeholder that what kind of security level they are looking for in order to access Power BI dashboard. Because sometimes what will happen, the senior leaders, they will need for, uh, access of each and every, uh, dashboard. But when you are looking for any stakeholders, we don't want to provide them a huge set of data, like the overall numbers. It just only do their program specific, what are the programs they cater to. So these are the things that we will see and we will, uh, look into when we are providing any kind of security lay layers or any kind of security to do that Power BI dashboards. And in order to test that application while publishing it to dashboard, we, generally, we, uh, use a Power BI desktop version where we have an option of manage rules, and then we can get an access. Then we can define on the basis of users that how they're gonna use the dashboard. It's based on the read function, write function, or both. So, yeah, these are the things that we will look uh, in order to provide any, uh, in order to integrate any kind of security layers to our Power BI dashboard. Thank you.

Yeah. That's, just the like, previously, what I said, exactly the same thing I'm going to use here as well. What steps would you take to ensure the security of dashboard being viewed by multiple user rules? So, definitely, uh, being a Power BI developer, so we need to define a certain kind of rules to all the users, uh, in terms of read, write, or both. And, uh, definitely, we're gonna provide them, like, a base level filter, base level view, or, uh, the complete dashboard view. So these are the things, uh, that we will consider when providing or when we are, uh, providing any kind of, like when we are, uh, what you can say, defining any kind of security onto our Power BI dashboard. Yeah. When when the dashboard is going to be used by multiple users. Thank you.

So I guess, uh, in this DAX, basically, what this DAX formula is doing, we are trying to calculate the sales of only 2022 by providing this calculate function into our DAX expression. But I believe for getting this, uh, getting the output for this particular, uh, information, what we are looking for, there is no need of that, uh, formula because definitely we can we can provide a filter here on a visual level filter we can provide and so that automatically, it should give us the total sales of 2022. So I guess here, we we we have an opportunity to save, uh, measure what we have created here by using this DAX formula. And, uh, it's it's it's kind of, like, uh, not required, which will definitely if if we are not creating it and we are just providing a visible filter for year 2022, I think the performance will not be impacted as much as when we are trying to create a tax formula and we're trying to pull out the information by using this formula. Thank you.

I'm sorry. I'm not able to I can see that we're trying to pull out the 2 data. Like, 1 is from the table. Another 1 is our Excel file sales data. We are joining that table from the customer ID. And, uh, all the tables are on the utilizing. No. I have no idea. I need to work on this 1. K. Uh, thank you.

First of all, we need to see, like, what is first of all, we need to, uh, get to the root cause of, uh, the performance issue, whether it's it's it's, uh, the issue is getting, uh, impacted by the DATs, what we have created, or there is some another factor, which is creating the performance issue in our Power BI dashboard. And after that, only we'll try to, uh, build a logic around it, so how to improve the, uh, performance of the report. But when I say, uh, if you I want to design a Power BI reporting solution that actually reflects complex business or logic in that without compromising on report performance, then I would say as I said earlier also, when we are building DAX, we need to be very, very specific. Like, what are the values we need to calculate, and what are the values which are dependent on them. So, basically, we need to identify the dependent variable. And if that our dependent variable, we'll try to create a DAX which is dependent on as minimum as possible. And, generally, when we are trying to use any DAX impression, we first see the relationship between the tables. If it is a bidirectional or 1 too many, generally, 1 1 too many will be I it's it's fine. We can go ahead with the tags. But if it is many to 1 or many to many, we generally avoid creating tax expiration on those kind of relationship. So these are the, uh, I can say, uh, these are the criteria or the things that we need to look into any, um, tax expression when we are creating it or when we are creating any Power BI dashboards, what is the relationship between the data set, and how we can try to, uh, build a dash, like, uh, without dependent on much more dataset. So lesser the dependency, the faster will be the query. K. Thank you. Thank you so much.

So I can say that if you can put the Power BI onto a Power BI service, then it it it is not related to and there should not be, like, uh, if it's kind of database maintenance activity is happening, then we can stop the auto refresh of our Power BI report, whether it is monthly, weekly, depending on the business requirement. But, uh, when the report is on Power BI service, so it has not any dependency on, uh, it it has the dependency on Power BI dataset, but unless Anurag will try to refresh the dataset, it will not create any impact. So if if any database maintenance activity is going on and we break the connection from our Power BI service to the Power BI datasets, then I don't think it will have any impact on our Power BI report during the database maintenance activities. Thank you.

No idea about this. I have never came across such kind of situation in my, uh, day in and day out work, and, definitely, I've I'll I'll I'll look into it. Okay? I'll look into it. Thank you. Thank you so much.