Finishing up some content on the BI - business intelligence level for the adilas value add-on core model.

Here is some of the new content, just for fun.

The fourth layer is the BI or business intelligence level. This is where you start seeing trends, patterns, and even identifying possible problems. Often people tend to think of the BI level like a giant dashboard that shows charts, graphs, quick counts and totals, however business intelligence is far more than graphs and charts. In this section we want to discuss what creates business intelligence and why it is so valuable to companies.

The first thing you have to do to get business intelligence is catch and centralize all of the data. This creates your pool of possible information. We call this pool of information transactional data. These individual transactions hold the details for what is happening in every level of your business operations. Everything starts here at this point. Then, similar to a cook with a pot of stew, you have to start boiling things down. The technical term for this is called aggregated data. This produces things like sums, averages, counts, maxes, mins, etc. These aggregates also become part of the available data pool for quick access and usage later on in your reporting.

Once you have your data pool you can start creating business intelligence through a process called "E.T.L". This ETL process is an acronym for extract, transform, and load. That may sound pretty simple but in real life, it is a pretty involved process. Extract means, let's look at the full data pool, decide what pieces are needed, and at what intervals. Then you pull that desired data out of the system. This usually comes from multiple places within the database. At this point, the data is somewhat raw but ready to be used. Next, we need to transform it.

The transform process takes data, which often has unnecessary pieces with it, and trims it down to just the needed pieces. This process is making the data into what you want and may take multiple steps in the transformation. Along the way, the load process involves taking the new pieces or sub products and putting them into a new holding container. For business data, that may be categorizing things by location, by date, by category or sub category. You label things, you place them in known areas within your database, and you pull certain values for certain reports. This is making business intelligence available for use both now and in the future (looking back).

The whole reason that we do this ETL process, and try to automate it, is because viewing transactional data breaks down when there are too many transactional pieces or when you are trying to span too long of a time interval. Automating your collection of business intelligence becomes a continual background process that we do for you as you continue to run your normal operations.

Without getting super technical, we'd like to introduce the rule of 0's here. This is just to help you see why aggregates and the BI level are needed. If you are looking at one piece of something, say an invoice, it's not a big deal. If you are looking at 10 invoices, it's not a big deal. When you start looking at 100 invoices that starts becoming a little bit more of a chore. You can see as you keep adding zeros it becomes harder and harder. If you went to 1,000 invoices that would become a major chore. What if you went to 10 thousand, 100 thousand, millions of invoices? You can get lost in the details and the time it takes to look at each one. Anyway, you can see how aggregated data or business intelligence becomes essential for seeing the patterns, trends, and summary of what is happening in your business.

One of the end goals of this BI level is called digital storytelling, being able to see and know your company's story as it unfolds over time. Imagine if you could see your entire business, almost flowing as if it were on a video screen or a miniature movie of sorts. You could see things as they go up and down and change. If you have questions, you could stop and you could drill in and see all of the underlying transactional data. That is where we are headed. The business intelligence that you could get from this would be amazing. Whether it is graphs, charts, targets, trends, or details, you could quickly see the business data to help you make decisions in running your business.

There could also be some excellent industry specific options here for 3rd party solutions that work with BI technologies. They may specialize in doing data analytics, predictive models, just in time reporting, trending, or other BI technologies. They could harness the transactional data from the adilas core to produce great BI results. Along those same lines, current AI, artificial intelligence or large language models, are becoming an increasingly valuable tool in working with large data sets. Lots of possible options are rising to the surface as technology continues to improve.

Often, companies pay big money and go to great lengths to get this business intelligence. This BI data adds great value for individuals and companies. They may pay for BI in many ways. Some examples could be: paying for extra people to help gather data from different software packages, business consultants, spreadsheet teams, people who do data analytics, and so on. This manual process of extra people and consultants happens over and over again. Companies want to know what is going on, how to plan ahead, and what decisions to make right now that will affect and/or help them in the future. Think of the value of having all of those processes automated and right at your fingertips in real time. That is invaluable and becomes a huge business asset to help your company. The adilas BI level will fill these business intelligence needs. As we continue building, more exciting possibilities will become realities.