Shin Nix

In this lesson, the focus is on "Conditional Formatting" which is very much similar to the conditional formatting in MS Excel which I could relate to following the making of the joint reporting system for personnel during my second job. Basically, we click the data columns that we want to be displayed in a tabular visualization.  Next, we select the columns that we will be applying conditional formatting to > Right-click on that column > Select Conditional Formatting > Select from among the options which is more appropriate for your application In this particular exercise, we utilized Background conditional formatting using gradient (applied on the first column of the first table) and rules (IF ELSE which was applied on the second column of the first table), Icons conditional formatting (applied on the second column of the first table), Data bars conditional formatting (applied on the second column of the first table and the fourth column of the second table). In the...

It has been quite a while since I wrote an update regarding my Coursehero tutor account. I am personally grateful for the platform as it gave me the opportunity to earn during the trying times of the pandemic and provided the means for me to improve my work-from-home setup. I still remember working with just my laptop sitting on a plastic chair answering questions whenever I have the opportunity. I loved the flexibility and the nature of the work where I got to select the questions that I would answer based on my expertise. It served as an avenue for focused work. During my stint as a tutor, frustrations motivated me to study coding, especially statistics and probability problems that get asked quite often with just different givens. This prompted me to enroll in a Udemy Course entitled, "R Programming for Statistics and Data Science". Using this knowledge, I was now able to answer questions in Statistics and Probability that require R as a programming language.  Then, I stud...

In this lesson, the topic discussed was regarding drill-downs. I can compare it to a "Prezi" equivalent in Power BI. In Prezi, we can zoom in and out of a powerpoint presentation to see details encapsulated in a mother topic. In drill downs, we are shown a summarized graph of the data but if we want to know some of the nitty-gritty stuff within that graph, we can "drill down" further to see the specifics within that summary. As an example, we have the following summarized visualization for the Price by Product and Store. If we activate the drill-down icon and click one of the bars i.e. Costco, we will be able to see the total price of the products that were bought at Costco as shown below. We can further drill down on specific quarters to see how the product sold in those quarters. In this case, more purchases of bottled water were recorded during the first quarter. Note: Drill-downs are specifically useful when conducting presentations and stakeholders want to know...

In this blog, I will be changing my approach to how I write the blog. In the previous blogs on Power BI, I was simultaneously doing what Alex is doing in Power BI and then, whenever I encounter issues, I will be writing it directly in the blog and then continued where I left off with the video once I am done. Here, I will watch the video first, take note of important keywords and lessons that Alex emphasizes, and then replicate what he did on the video. This lesson focuses on DAX or Data Analytics eXpressions. Based on what I understood on the video, DAX can be likened to the formulas associated with MS Excel. And, since Power BI is also a Microsoft product, there are DAX that are similar, if not, the same with what can be found in MS Excel (One example is the IF expression in Power BI). In this exercise, the process of using DAX was explained starting with creating "New Measure" and then using various DAX to be able to visualize the intended outcome in a table. For example, ...

I am now in the third tutorial on Power BI. In this lesson, the topic is on creating and managing relationships. Important concepts that were introduced are cardinality i.e. many-to-1 (*-1) or (one-to-many (1-*), cross-filter where if we select "Both", this means that we can think of many separate tables as one table. I have these three separate tables. Apocalypse Sales: Apocalypse Store: Customer_Information: Notice that each of the values in the Customer ID column of the third table can be seen in the Cust ID column of the first table. But notice that there are only four rows in Customer_Information table while there are many rows in the Apocalypse Sales table. The cardinality of the relationship means having unique or multiple instances per value for the joining field between two tables. This means that the cardinality of the relationship from Apocalypse Sales and Customer_information in terms of Customer ID = Cust ID  is Many-to-one. Conversely, the cardinality of the rel...

Power Query is a  preliminary step in subjecting the raw data to Power BI to create the necessary visualizations. In Power Query, we can transform the data, rename/add/delete columns, change data type among other things. To be familiar with Power Query, we will convert the following Summary Table to the Purchase Tracker table right below it. Summary Table: Purchase Tracker: The first thing that we will do is to import the data from Excel to Power BI. We will only select the "Pivot Table" and the "Purchase Overview" sheets and then click "Transform" so that we will be led into the Power Query Editor. In this particular exercise, we will do most of the transformations on the Purchase Overview sheet and the reason we included the Pivot table is to serve as a reference. We will now perform data cleaning by removing rows that have "null" in its entries. Performing the steps that were outlined on the video, we were able to transform the Purchase Overvi...

Just want to pass by here and update you regarding learning about the data visualization tool - Power BI. By the way, BI is an acronym for business intelligence. I am using the YouTube videos from Alex the Analyst. Hopefully, this works out. I am already finished with video #1 and appreciating how this tool was able to create visualizations (graphs) just from clicks and a few editing and navigation in the software. Currently, I realized that the ones presented can still be done using MS Excel although the same graphs could be quite tedious in Excel than in this platform.