Dimensions and measures are the keys, defining the critical centricity of data points. These form crucial parts of every business intelligence software and data analytics software. Let’s first understand the basic definition of ‘Dimensions’. They are categorical data points or attributes around which the numbers or factual numbers revolve to build different analysis story points. Let’s consider we have 5 different data points in a fictitious data set: Region, State, Product, Sales and Quantity. Now given these fields, the Region, State and Product fields are what make the dimensions for this data set. We could further categorize, aggregate, slice and dice to answer business questions. They are like the powerhouse for any data set. A wiser term to use could be they are qualitative in nature, and help:
- Categorize
- Build data-related understanding
- Answer business-specific questions
- Questions related to where, which etc., are more broadly to be assessed using them
- Build trend/pattern-related storyline
Measures are quantitative in nature. Using the above fields, we can easily say that Sales and Quantity define the measure of our fictitious data set. On the measure, we quantify the data from above and ascertain what sales are (aggregated value right) and what quantity is sold in a particular region. Here, the quantity being a measure and region, being a dimension, are combined to answer business-specific questions. Measures are what add validity to the dimension-related data points.
Combining Measures and Dimensions
Now that we know what dimensions and measures are, a more purposeful discussion area is the combination of both. Together, dimensions and measures are what make an analysis of purpose. Both form an essential part of business intelligence software. Measures can be calculated, or new ratios and further questions could be answered based on the data granularity. To put in simple terms, measures are the numbers that define the key characteristics for a given dimension which we could further slice and dice to reach a business-specific ask being made. More concepts revolve around dimensions and measures like dimensionality, continuous and discrete, aggregations, relationships etc. Our core object here is just to familiarize you with these terms.
An Example
Recall any of the cricket matches. Now to decide which side gets to bat or ball we used to toss, right? The deciding factor in eliminating the bias. We all have seen a coin (in case you have one right now, just flip it). Like there are two sides to a story, much like a coin (pun intended); let’s relate to it with our dimension and measure here. To build a more understanding point, I would say the ‘Head’ side of the coin is a dimension right above which state, currency, logo etc., more of a qualitative data point. The ‘Tail’ side of the coin, which has a number on it, is what a measure is, as that is what adds significant numeric value, quantitative data.
In Conclusion
It’s of key interest to explore more just ahead than the basic understanding of Dimensions and Data. Quick points to summarize our blog:
- Together dimensions and measures add potential to data understanding and develop meaningful insights
- Measures can be computed using defined logic calculation to further understand business objectives
- Perform aggregations with your measures at different data granularity
- Track KPI metrics using measures
- The more likely measure being quantitative fields help to analyze and compare data at different points
- Using Dimensions to slide and dice the data to understand patterns and answer different business questions
- Dimensions help define characteristics of data
- Create a hierarchy from your dimensions to view how a particular class of products or geography mapping adds to the data-related question
This brings us to the end of our blog post. We are certain these inputs could help you understand the dimension and measures terminology and help define your KPI metric and analysis. The ideal approach would be to start with a few points and march toward the progress of the end goal. This requires cloud business intelligence and data warehouse visualization capabilities.
As a Tableau Gold Partner, Uneecops can jumpstart your analytics journey. Our cloud business intelligence solution experts can show you how to embed dimensions and measures within data points and visualize data. Further, we can integrate Tableau business intelligence software into your business and help you explore data warehouse visualization using the data analytics software. Get started now and keep vizzing!
