Tuesday, October 25, 2016

Dilbert on Why Self-Service Reporting, BI & Analytics Takes Faith

The term 'self-service' has been applied to reporting, business intelligence and analytics over the past few years.  While there are many business use cases for agile, 'self-service' approaches; it is a BI myth to believe that the need for a single consolidated source of truth is going away.  

So, why do I say that self-service BI takes 'faith'?  

Whether you trust sales person 1 who prepared a report in Excel or their favourite BI tool based on the centralized data warehouse that has ingested the raw sales data, applied consistent rules to modify the data and provide it in an easy to use and understand model or sales person 2 armed with an exported sales report, Excel to modify the data and a data discovery tool to report accurately on last month's sales, you need to trust the initial data quality, interim transformation process and final aggregation and visualization. 

Neither process is wrong, but there are obvious benefits to each approach and organizations should take a bi-modal approach to leverage the strengths of each.

My experience working with clients supports this.  There are several types of people who work at organizations, but at a bare minimum, there are data analysts (those trained and experienced working with data) and data consumers (those who either lack this training and experience or simply don't have the time).  We are not moving forward if we expect those in the second category to supernaturally 'help themselves'.  

Monday, February 8, 2016

Dilbert Sensors IoT Big Data Employee Hat

We've been hearing a lot about Big Data for years and big data sources getting increasing attention these days are smart machines and sensors. 

Sensors, like the one in Dilbert's stylish hat, can be embedded in wearable technology, enhancing what traditionally has been low tech clothing with numerous data points to be harnessed to create new and better products and solutions, ultimately better serving customers and improving profits.

Now, back to work!

Thursday, January 7, 2016

Dilbert Spreadsheet Error Ethics

I feel compelled to post this latest Dilbert strip on spreadsheet errors, as a follow up to yesterday's post.
I suppose this same type of question could apply to machine learning and other advanced analytics that could also be easily misapplied.

Do you have spreadsheets with critical errors that you're overlooking because they give you the answers you want?

Or, perhaps you have error free spreadsheets that are manually updated periodically (every day, week, month, etc.) that are an inefficient use of time?

Either way, there are both Excel-based and non-Excel based solutions to help!

Wednesday, January 6, 2016

Dilbert Spreadsheet Errors

There have got to be more posts on the problems with Excel and spreadsheet errors than pictures of cats on FaceBook at this point.
But, now that Dilbert has chimed in, we all know the issues are real!

Monday, February 23, 2015

Real Life BI: Science Fair Data Presentation

This year, one of my sons participates in the Science Fair for the first time.  All in all, this was a good experience for both him and us parents.  

Now, I didn't take a lot of science myself, so I am not sure that I was particularly helpful in that regard.  Having an iPhone, I was able to Google search and perform mobile research on the affects of heat on an elastic band as we performed the experiment.

My greatest contribution, in my opinion anyhow, was this graph.  I was proud to use my real world knowledge of graphing and presenting data to recommend that my son use separate axis for both temperature and length, allowing the relationship between the two to be comprehended nearly instantaneously.  With only one axis, this was not clear at all as the length appeared to be constant.

Now that Science Fair is almost over, its time to get back to work helping organizations make use of Enterprise visualization and analytic tools that help people understand their business and make good decisions, fast!

Please let me know if I can help you!

Monday, May 5, 2014

Real Life BI: Time Saving Benefits of Jet Enterprise

One of our clients recently implemented Jet Enterprise in their organization to improve reporting on a third-party Dynamics GP module.

They had previously used both Crystal Reports and SSRS; however, neither enabled the client's finance and engineer users the ability to easily create and maintain their own reports.

So, on to the story...

A finance user was struggling with filtering a report and producing the same results as an existing custom SRS report.  Part of the problem practically, is that a number of tables, unions (i.e. between open and historical data) and joins (i.e. to link the tables together) needed to be understood and configured properly before adding the filter.

I have no idea exactly how many hours this finance user had poured into creating this report; however, I do know that from the time she reached out to me via email to ask for help, to the time I received an email back saying that the report was working was nearly instantaneous.

What did I tell her?  I can tell you that I did not give her a crash course in table buliding, report building or anything of the sort, I simply said the following:

"Have you considered using Jet Enterprise for this? You already have the data summarized there. It would just need the filter."

That was all that was needed.  Simple, quick and accurate since the third-party data was already configured in an MS cube in an easy to use tool in full accordance to Kimball's best practices in dimensional modeling. 

If you or your organization are interested in leaving the office early, contact me.

Dilbert on Big Data

Big Data is definately here to stay, but as Dilbert points out below the ethics of Big Data analysis also need to be considered.