A Step By Step Guide To Data Visualization With Power BI by@47Billion
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A Step By Step Guide To Data Visualization With Power BI

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Business Intelligence enables you to create a narrative around your data and tell a compelling visual story with actionable insights. Power BI is the collective name for an assortment of cloud-based apps and services that help organizations collate, manage and analyze data from various sources through a user-friendly interface. We are using widely used and publicly available data for visualization – “TLC Trip Record Data,” popularly known as “NYC Taxi data.” We can find it over the website, which provides taxi trip records from 2009 to July 2021.

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Data has become the core of the modern business, and it is expanding more than ever. But these large datasets are not of much use unless organizations can make sense of it. That’s where Business Intelligence comes into play.

If you are thinking about utilizing a platform that helps you pluck helpful, actionable insights from your data, then you are at the right place. In this blog, we are describing end-to-end Power BI implementation.

What is Power BI?

Power BI is the collective name for an assortment of cloud-based apps and services that help organizations collate, manage and analyze data from various sources through a user-friendly interface. It enables you to create a narrative around your data and tell a compelling visual story with actionable insights.

Figure 1 – Data Visualization with Power BI

Figure 1 – Data Visualization with Power BI

Below are the Steps for Power BI Implementation

1. Get Data

We are using widely used and publicly available data for visualization – “TLC Trip Record Data,” popularly known as “NYC Taxi data.” We can find it over the website (https://www1.nyc.gov/), which provides taxi trip records from 2009 to July 2021.

Visit the URL mentioned above, which has links to all trip records from January 2020 to December 2020, zone lookup tables, and data dictionary -

https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page

Now download “Yellow Taxi Trip Records” for January, “Taxi Zone Lookup Table” along with “Yellow Trips Data Dictionary.”

2. Extract Data

As you can see, the data is in CSV format. We need to import this data to Power BI as we need to confirm whether there is any requirement for transformations. The file contained 64+ lakh records with 18 columns, and we easily imported it to Power BI. Also, we imported the data from the “Taxi Zone Lookup Table.”

Figure 2 – Extract Data

Figure 2 – Extract Data

Figure 3 – Extract Data

Figure 3 – Extract Data

Figure 4 – Extract Data

Figure 4 – Extract Data

3. Transform Data

At this stage, we checked the data superficially and found that some columns had few nulls. Thus, they require transformation operations. We used the following Power BI transformation features –

  • Replace Values– To replace nulls with some acceptable values
  • Conditional Column– To add additional columns of “Vendor Name” & “Rate Type” based on their numerical values. (“Yellow Trips Data Dictionary” provides these details)
  • Add column from Examples – To add additional date columns to have only date values from trip pickup DateTime & trip drop DateTime columns.

Figure 5 – Replace Values (Transformation)

Figure 5 – Replace Values (Transformation)

Figure 6 – Conditional Column (Transformation)

Figure 6 – Conditional Column (Transformation)

Figure 7 – Add column from Examples (Transformation)

Figure 7 – Add column from Examples (Transformation)

Also, Power BI has a feature to create a date table. We created a date table having date hierarchy columns like the year, quarter, month, week, and day. Timeline-based reports have drill-down features which use the columns mentioned above. We can drill through a date hierarchy report from “Year” to “Day.”

Figure 8 – Date Table

Figure 8 – Date Table

4. Data Modeling

Data modeling is used to connect multiple data sources in Power BI using a relationship. A relationship defines how data sources are related, and based on these; you can create exciting visualizations on various data sources.

We have the following data sources ready with us now.

  • Yellow taxi trip data

  • Taxi zone lookup table

  • Date

Thus, we created a relationship between the LocationID of the zone lookup table and pick and drop LocationIDs of Yellow taxi trip data.

We also created the relationship between the Date column of the date table consisting of pickup and drop off date columns from yellow taxi trip data.

Figure 9 – Data Modeling

Figure 9 – Data Modeling

Figure 10 – Data Modeling

Figure 10 – Data Modeling

5. Data Visualization

Power BI has got several visuals such as stacked, line, pie, donut, map, and scatter charts. Using the easy-to-use interface and visual, we prepared data visualizations.

Figure 11 – Data Visualization

Figure 11 – Data Visualization

Figure 12 – Data Visualization

Figure 12 – Data Visualization

Power BI has got several amazing features, and one of them is the “Cross Highlighting” feature. Suppose you have multiple visuals over a single interface. In that case, we can click over any visualization element, highlighting all other visualizations on the page corresponding to the part clicked. Check the pictorial representation-

All Elements Highlighted in the Below Diagram

Figure 13 – All elements highlighted

Figure 13 – All elements highlighted

A Single Element is Highlighted from the First Visual in the Above Dashboard

(All other visuals got impacted corresponding to the highlighted element)

Figure 14 – Single element highlighted

Figure 14 – Single element highlighted

Slicers

In addition to graph plotting visuals, it also provides slicers to create data filters.

Figure 15 – Slicers

Figure 15 – Slicers

Page Navigation

Power BI has also got some cool features like bookmarks, buttons & selections. We can create page navigation similar to the web interface.

Figure 16 – Page Navigation similar to the web interface

Figure 16 – Page Navigation similar to the web interface

The Path Ahead

Power BI has several other features like Direct Query, DAX functions, themes, tooltips, custom backgrounds, and conditional drills. They help make more meaningful reports and dashboards that bring value to businesses. We will be covering them as well; till then, stay tuned with us.

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