HTML5, CSS3, SQL, R, Python

CompareTrends - Ad Hoc Comparisons

CompareTrends provides the ability to compare any trend to another trend with precision to help with comparisons.  The lion’s share of companies have metrics in different systems, with trend comparisons built in Excel for one-off comparisons (for example, figuring out how a company’s revenue trend looks compared to the gross domestic product for its industry).  CompareTrends makes determining trend direction (growth or decline) and discovering similarities or correlations easy and quick by providing business people a ready-to-use facility with all company-related metrics included.

The CompareTrends Copyright © Registered solution below can be used as-is or changed to include additional dropdown menus or formatted for different uses.  For example, dropdowns could be added for country, zone, region, district, site, customer, and product, which would allow for aggregated comparisons.  Dropdowns can have large lists of values for fine-grain analysis, as well.  The example below has 15.4 billion+ comparison combinations available for users.

15.4 billion+ comparison combinations above

The CompareTrends screen example above has 1,300 metrics loaded for each country.  There are 135 Countries.  If we take 135 Countries times 1,300 metrics, the result is 175,500 total metrics.  The square number result minus self-comparisons divided by 2 is 15.4 billion+ comparison combinations, which is staggering considering the analysis that can take place when comparing each metric to another.  We have also added additional United States related metrics below the country level for Los Angeles, Boston, and New York.  Although it does not make sense to compare every trend to another trend, it does open the door for business people to make that decision and to do the comparisons or trend analyses themselves versus waiting for an analyst or another organization to provide data for the needed one-off comparison.

The example above also contains data from 1980 to 2010 (31 periods).  The charts and tables above have been tested at 19,000+ periods (data points) for X-axis values (one could use seconds versus years depending on the metric).  The application can scale for web-browser analysis.  All of the calculations and computations are done in the database so only clean/aggregate data sets are shown in the browser (compatible with Big Data and Modern Data Science).  Users can also copy raw data from the browser to perform additional analysis in Excel or other tools (see Raw Data, above).

Trend direction, correlation, similarity, and analogies (key skills for business people)

CompareTrends in a business setting is best integrated with an EDW.  It acts as a high-level and deep dive statistical ad hoc facility for analyzing and comparing different metric trends in or outside a Company.

In business, the term “correlates” is used often in general discussions.  For example, “this correlates to that,” which means that this behaves like that because there is a relationship or similarity.  Usage of the term is often based on intuition and has no true mathematical measure.  Aside from correlation, the same kind of speculation is employed when determining if a trend is headed up or down - especially when trend data has high variation or many ups and downs, which can make it difficult to gauge direction with precision.

This solution speeds overall organizational thinking because trend direction and/or comparisons are quick and at the users’ fingertips when thoughts occur.  In fact, by surfing comparisons with quick response times, users are able play with hundreds of comparisons within minutes or hours, which expands the creative mind and creates more questions and a better understanding of trend direction, similarities and relationships.  Connecting the dots this way takes Enterprises to the next performance level by providing access to details that make up the “Big Picture.”

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