Our Top 5 Commands/Functions in Data Analytics

Oct 5, 2021 | All Articles, Arbutus, Top 5 Tips | 0 comments

Beta Software consultants have been working in the ‘All things Data’ world for more than 20 years. This article will focus on our Top 5 Tips on how to Analyze/ask questions of your data using easy to use Commands and Functions within Arbutus Analyzer.

When analyzing freshly imported data it may be of some benefit to run a few easy commands and functions to set the scene of the data, paint the story of the company the data is telling you. In running the commands/functions in this article we can obtain:

  • Data Preview – Browse the data before importing it 
  • Trends – Some telling trends of our data (seasonal, event driven, reporting periods, etc.)
  • Groupings – Relating to Users, products, months, days and even custom comments.
  • Statistical Information – Bounds, totals, averages and more.
  • Exporting – Easily send the data to different file types for easy reporting

When using these commands/functions we will get the answers to the above quickly and easily. Furthermore, this gives us a great understanding of the data we are working with and allows us to ask more questions and even allows the data to ask questions as well.

Please note: That all data shown here is fictitious and is used for demo purposes only.

Now let us not keep the suspense any longer and begin our Top 5 Tips on our Top 5 Commands/Functions  beginning with…

Tip 1: Statistics are fun

Working with Statistics is fun and it’s how I like to spend my Sundays… ok this isn’t true… I don’t spend every Sunday working on statistics. However, working with our favourite analytic software Arbutus Analyzer we can run a powerful statistics command to ‘collect’ and record some statistical information from our data.

By simply highlighting a field and a click of the mouse a Statistics command can be run on a numeric or date field. On a date field we can obtain:

  • Valid and Invalid data entries 
  • number of Blanks date entries 
  • number of date entries on the weekend and more

Additionally, what we also note are the 5 (adjustable) highest and lowest date entries. Giving us the date bounds from which we are working with.

Running statistics on a numeric Field we can obtain:

  • The number of entries with Positive values
  • The number of entries with Negative values
  • The number of entries with Zeros
  • Totals, Averages, Range and Absolute Value

Additionally, what we also note are the 5 (adjustable) highest and lowest numeric entries.

Below Payments table where the Statistics command was run

Statistics on Date field 

Statistics on Numeric field 

Furthermore, the results are recored into an easily accessible and interactive log file. The blue values above serve as hyperlinks allowing us to zoom in or drill-through to the initial table easily on the data we wish to isolate.

There are many, many more statisitcal functions that can be run within Arbutus Analyzer. What was shown above are our… Sunday favourites. 

Tip 2: Classify, the herd dog of data

In addition to the above, the Classify command within Arbutus Analyzer allows us to herd or group our data per unique value. Classify is very powerful, rounding up large data sets quickly and easily.

Running Classify on character fields gives us the number of transactions as well as accumulated numeric field(s) per grouping. 

Running a Classify on a Vendor Name field accumulating the Net Payment field with it. Gives us insight where the largest Payments occur as well as the lowest and the number of transactions per a given Vendor. 

Results in the Command Log

Results can be outputted to a table as well (also Drill-Through enabled)

Below shows another example of a classify/grouping per Transaction Type:

The Classifying of our data allows us to view how many transactions occur with a specific vendor, customer, document type, payment terms, products and so much more. 

Highlighting not only groupings with many transactions and accumulated amounts but also those outliers where few transactions occur or uncommon products/Vendor/Entries. 

Classify… good doggie. 

Tip 3: Summarize, easy to digest

The Summarize command not only groups all and any field(s) in your table per unique value, regardless of data type or size. It also allows you to process any field based on a parameter of your choice. 

Using the Summarize Command in Arbutus Analyzer on Table AR Invoices we can achieve the following (one example of many):

Grouping the data per Customer per Quarter and choosing the earliest and latest date per groupings as well as the Sum and Average of the Total Amount per Groupings.

The end result is a Summarized table that you can Analyze further and it is Drill-through enabled. 

Summarize allows for easy trend analysis, spotting outliers as well as creating elapsed time fields from the earliest and latest date fields. The use cases for the Summarize command are many. It allows you to group your data easily on any field and process any field(s) according to the parameters selected.

Summarize one of our favourite commands, it goes down well. 

Tip 4: Import: Database Explorer… just window shopping, thanks

One of the many Import options in Arbutus Analyzer is the Database Explorer, Browse ODBC data sources and create and issue Select statements for importing data from ODBC-compliant data sources.

Preview and browse the data by creating a select statement and filter the data you only need before importing the data into Arbutus Analyzer or simply browse. 

Tip 5: Export, sharing the love

Exporting the data is easy to accomplish, there are many options or file types to export your results to in Arbutus Analyzer. Some of our favourite options are Exporting to an Excel workbook where you can export to individual worksheets. 

Another favourite is exporting to any ODBC compliant Database. This allows direct table exports to SQL-based ODBC drivers and relational databases.

Making it easier to communicate your results and for your Dashboard solutions to consume your data to visualize. 

In Closing

We hope you enjoyed this article and gained some insight into the Commands explained here. What was mentioned here were just a handful of many other Commands and Functions found within Arbutus Analyzer. If you would like more information, please get in contact with us. We would love to present or Demo what Arbutus Analyzer can do! 

Author/Consultant’s Bio:

Terence Olivier has been in the BI?Data analytics world for 15 years. He has worked with a vast array of BI and Data analysis software. He has enjoyed being involved in projects in the Mining industry, Logistics, Retail and many more. Data Analytics, Fraud detection and Data Analytics Training is his specialty as well as visually displaying the data into trends that tells a story about your data and ultimately your company. 

Please feel free to contact us if you have any questions, challenges or obstacles you would like to overcome. Thank you for reading!



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