Modern Analytics and Business Intelligence

In a prior blog post I mentioned the limitations of traditional business intelligence and business analytics. One of the more significant limitations of traditional business intelligence is the lack of support for semantics by traditional business intelligence and business analytics platforms.  

To address this limitation, traditional business intelligence is adding what is being referred to as a "semantic layer".  A semantic layer is the governed business meaning layer that defines the "things", the "associations between things", and other stuff necessary for a analytics systems and artificial intelligence systems speak the same language.

An example of adding a semantic layer can be seen by checking out Google Looker. Looker uses something called LookML or Looker Modeling Language.  Looker Modeling Language is described as the language that is used in Looker to create semantic data models. Looker says that a "semantic model is the foundation for trusted AI".

Now, others refer to this "data warehouse" or "data marts" or "data lakes" (e.g. a bunch of relational databases tied together) plus that semantic layer that sits on top of that data as an "enterprise knowledge graph".

But there are entirely new approaches to storing data that have appeared over the past 25 years.  RDF triple stores, graph databases, vector databases, modern logic programming databases, document databases, and other such data storage alternatives.  Each one of these alternatives has a basket of PROS and CONS. None is perfect for everything.

And then you have the electronic spreadsheet. There is a lot of enterprise data and information stored in those electronic spreadsheets.

Now, all of these approaches are trying to arrive at the same point. That common point is to maximize what artificial intelligence can do for you.

There is one common situation which everyone has.  That common problem, as pointed out by The AI Ladder, is that their data is a mess.

In terms of traditional business intelligence and business analytics, there is another thing that a lot of companies have in common: Microsoft, Oracle, Google, IBM, Salesforce, Amazon. These are the entrenched goliaths that want to persist the current paradigm by making incremental improvements.

One thing that is certain is that the status quo will change.  That is a given; artificial intelligence is too powerful to ignore.  But, will the "normal science" persist with incremental changes to the current paradigm such as retrofitting a "semantic layer" onto that current business intelligence platforms; or will "new science" disrupt that current paradigm, creating a new paradigm?

From where I sit, I can see that there appears to be three paths to the future of business analytics and business intelligence:

  • PATH #1:  Additional incremental improvements to the current traditional business intelligence and business analytics paradigm.
  • A completely new modern paradigm to business  intelligence and business analytics.
    • PATH #2: This completely new modern paradigm is based on proprietary approaches.
    • PATH #3: This completely new modern paradigm is based on global open industry standards.
Having each enterprise express there semantics in different ways and each using different terms will cause problems down the road.

The reality is that all three approaches will very likely be explored by the market.  Then, down the road, there will be a "sorting out" that occurs.  It also could be the case that entirely new categories of products are introduced.

Personally, I am betting on a modern business intelligence and business analytics that is based on global open industry standards that rebuilds everything from the ground up rather than introducing retrofits that address current limitations. I am betting on XBRL International's Open Information Model (OIM) and OMG's Standard Business Report Model (SBRM) as the global open industry standards based approach.

I am betting on ISO/IEC Accounting and Economic Ontology, Data Centric Accounting, REA, XBRL. We need to think beyond the document. Artificial intelligence has a hard time with all the different ways humans create documents.  We need to separate the document "costume" and the information those documents convey.

Additional Information:

Comments

Post a Comment

Popular posts from this blog

Professional Study Group for Digital Financial Reporting

Image
Digital financial reporting is a thing.  The IFRS Foundation explains digital financial reporting  in an article, Digital Financial Reporting - Facilitating digital comparability and analysis of financial reports . OFFICIAL VERSION : The IFRS Foundation publishes an XBRL taxonomy for IFRS for SMEs (2024).  You can find official information about that XBRL taxonomy here on this web page, IFRS for SMEs as Published by IFRS Foundation (2024) . (Also see this PDF, IFRS Taxonomy Illustrated .) Since that official XBRL taxonomy is effectively a "pick list" created from the perspective of standards setters (i.e. not very practical, easy to use, and intended for ease of use by reporting economic entities);  ENHANCED VERSION : I have created an enhanced version of that same XBRL taxonomy, see  IFRS for SMEs 2024) - ENHANCED (Work in Progress) . The enhancements make the IFRS for SMEs XBRL taxonomy more useful in many different ways.  The enhancements are driven...
Read more

Big Idea for 2025: Semantic Accounting and Audit Working Papers

Image
I began my career in accounting in 1982 as an auditor with Price Waterhouse when accounting and audit working papers and schedules were 100% paper.  But within three months, I was creating many of those same working papers and schedules first in VisiCalc and then Lotus 1-2-3.  I would create those schedules and working papers electronically, then print them out, and tape them into the bundle of paper that supported our audits. The Compaq luggable computer was invented and electronic spreadsheets where even more compelling. Today, accounting and audit working papers tend to be 100% electronic proxies for those paper documents created in Excel or some other electronic spreadsheet, Word or some other word processing document, PDF generated from some word processing document, and maybe HTML.  All of these are presentation oriented proxies for documents and none of them is truly understandable by a computer based process. The next step in the evolution of accounting and audi...
Read more

Rethinking Financial Reporting: the Model-driven Financial Statement

Image
It is time to rethink the design of financial statements. Clay tablets worked well and they had a good run which ended many years ago when the clay tablets were replaced by papyrus and then ultimately paper.  Paper had a good run also but paper financial statements were ultimately replaced by what amounted to an electronic version of that paper; PDF, HTML, and such. We can do better.  Today's demands call for more modern accounting tools . Idealized design  (a.k.a. greenfield project ) is the notion of designing a system without imposing constraints of prior work.  This technique may, or may not, work for rethinking the financial statement. Idealized design might be a harder path in the short term, but taking this approach has very positive long term ramifications. Here are a number of ideas that I would throw at the wall if I were in charge of rethinking the financial statement to make such tools modern: Digital first : The first thing that I would do is abandon the...
Read more