ITC Pre-release for Week III Quiz
Stuff you need to review to prepare for end of week assessment for week III.
It’s that time of the week again. The selected dataset for this week’s quiz is the SBP payments systems dataset. Your quiz this weekend will be based on the SBP systems dataset shared earlier this week with you.
This is the dataset that track internet banking, mobile banking and ecommerce transactions on a quarterly basis using summarized data reporting by the banking industry to SBP. The report is published on a quarterly basis. Your dataset includes the series from 2017 to 2023.
To prepare for the quiz, you should read and review the following articles, build an analysis model for the dataset along the lines of the one you have done for FTC. Pay special attention to identifying relevant, data, the distribution of data, the analysis and drivers of data, the relationships between different data elements, metrics, intelligence and actionable intelligence. See the lectures for this week (week III) uploaded to YouTube.
The quiz will test you on the frameworks and materials presented and shared this week as part of the I in BI lecture series. It is not just limited to the dataset, models or study guide shared with you earlier in the week. So be prepared for questions that mix and match concepts, analysis and computational thinking.
You should be comfortable with analyzing the SBP dataset, responding to questions dealing with insights and applications that can be derived from the dataset, working through challenges and frameworks identified in the first three weeks of instruction and applying computational thinking techniques to the posed questions.
Best of luck.
What should you do with the SBP data set?
In the FTC dataset your analysis focused on one column only. Revenues. Revenues was the central driver and theme. You looked at country, city, reference source, new vs returning, but it was all centered around revenue.
In the SBP dataset you have only 22 rows. But each of the columns starting from POS (Point of Sale machines) to EC Mobile Banking Value (column AE) is essentially open to analysis and dissection, just as we dissected FTC’s revenues.
There are also implicit relationships in place, some of which you can trace by going through how the values in certain columns are calculated.
The essence of your analysis needs to focus on what was covered in the class room this week. Data. Distribution. Relevance. Benchmarks. Baselines. Metrics. Insights. Intelligence. As they apply to the SBP dataset.
For instance consider the following two screen shots
How is ECVal_USD_T (Ecommerce transaction value per quarter in USD equivalent amount) calculated. What are the sources of its growth? How would you model that growth? What is the likely growth going to be in the next quarter?
What do you need to answer this question? Build that model using the dataset, the tools and techniques we have covered between the inclass lectures, the study guide, the case study and the lecture recordings shared with you this week.
SBP Table field guide
What do the field (column) headings on the SBP summarized table mean?
Read and review
- Tracking Growth.
2. Sizing Markets
SBP Payment Systems Reports — FYI and for reference and context. https://www.sbp.org.pk/psd/reports/index.htm. You won’t be directly tested on these reports. These are being shared to provide context and background to the assignment and test materials.
Week 3, lecture 3 recordings on the ITC playlist. Only focus on Week III lecture series.
Specially focus on Part II (Distributions), III (Data, insights and metrics) and IV (relevance and baselines).
The I in BI — The original framework and reference materials
What should you expect?
One. Classification and grading.
From the lecture slides, where does a given field in the SBP dataset fall? On the scale below?
Two. Rates of change and distributions
For the fields where rate of change has been calculated (growth), what is the likely rate of change in the next quarter. What is the average rate of change. What is the underlying distribution? Build pivot tables and histograms.
How to build a histogram? And why?
How to read a histogram?
How do you read that table on the side?
Three. Is it data, metric, insight or intelligence?
Is a field or an analysis considered data, metric, insight or intelligence?
Four. How do you read / grade / scale and review multiple dimensions in one plot or chart?
You don’t have to plot it, but you should be able to read, decipher and interpret it. How do you keep, balance and track more than a three dimensions in your head? Each of these skills below represents one dimension.
Five. What is the right baseline or benchmark?
Given a dataset, what is the right benchmark against which growth should be measured?
Six. What is the trend? Where is it heading?
Use the Excel chart trendline function to predict and forecast growth.
Right click on the line plot to open the plot options. See the circled Add trendline option.
Then click on Add trendline. Pick linear and forecast for 4 periods.
Seven. Relationships. Dependencies. Linkages
How does it all come together. How are values calculated. If you change one driver how does that change the outlook. This is mostly contextual based on your understand and work above. What is the relationship between ecommerce growth and its core sub drivers. Is that customers, orders, or average order value?
