Simplifying Business Intelligence

Business Intelligence (BI) is a hot topic. But what does it really mean? This maiden post is the origin on our journey together to find answers. To start off right, let’s begin with my definition of Business Intelligence, which is the foundation of this blog:

Business Intelligence is the convergence of technology and analysis to enable effective decision making.

In the traditional sense, Business Intelligence describes technology. We must take the definition further… technology alone cannot solve the one and only purpose of Business Intelligence: enabling effective decision making. Let’s discuss the definition piece by piece.

Convergence

A computer can be programmed to make decisions based on a set of rules. What happens when a scenario comes along where no rules are written? This is where intelligence comes to play, particularly human intelligence. The human brain is an amazing device which has the ability to process numerous different inputs, resulting in an outcome.

Unfortunately, the brain has limitations. For example, if I had 1,000,000 visitors to this blog every day and wanted to understand what content is most popular, my brain could not digest that much data at once. Technology to the rescue! A database can process massive amounts of data with ease.

Ultimately, convergence is required to solve the limitations of technology and our brains. Together, the goal of Business Intelligence is possible.

Technology

The technology side of Business Intelligence is often comprised of multiple layers. Depending on what your BI goals are, you may add or remove layers. In future posts, I’ll deep dive into different layers. But let us start with the basics.

Data Sources are typically the transactional systems used to run your business. This can include ERP systems, web server logs, manufacturing systems, etc. In some cases, it could be data collected manually on a piece of paper. Keep in mind however, at some point all data must reside in a system where it can be accessed by the Data Movement layer.

Data Movement is the beginning of a robust technical solution. By moving data out of your data sources, you are isolating the performance impact on the critical systems used to run your business. There is another key: you’re not only moving data, but also reorganizing it in a fashion that makes retrieving data for reporting much easier and faster. Data movement is also referred to as ETL (Extract Transform Load).

Data Storage . You have to store the data you moved out of your source system somewhere right? Of course you do! Besides minimizing the impact on your transactional systems, moving data to a new storage location provides the opportunity for further performance tuning for your data queries. A database configured for a transactional system is radically different than a database configured for BI. In a transactional system, the goal is to retrieve 1 record as fast as possible. Meanwhile, a BI database will acquire millions of records, summarize, then return a concise result. I’m a fan of analogies, so here you go: Imagine if UPS delivered packages with a Corvette. They could deliver 1 or 2 packages really fast, but they would have to drive the Corvette back and forth to the distribution center so many times, it would not be efficient for the hundreds of packages delivered in a given region. So, a slower, yet big truck can hold many packages is more efficient (although not nearly as fun for the delivery driver! ).

Data Presentation is the user interface to your data, which provides the capability to retrieve data from data storage and process it into the output the user is looking for. The output comes in many forms, which includes reports, dashboards, RSS feeds, desktop widgets, mobile apps, etc.

Analysis

All too often reports are simply “data dumps” and not effective information to make decisions with. That is the role of analysis. Data is not useful on its own, so it is important for human intelligence to play a role in transforming data into decision enabling information.

Business Analysis is the process of taking data and applying human intelligence to create information. You might wonder the difference between data and information. Data is like raw ingredients, egg, flour, sugar. Information is all of the raw ingredients mixed and baked into a yummy birthday cake. While you could eat the raw ingredients, the birthday cake tastes much better! The same is true for data and information. Data can be used on its own, but information is far more useful. Information is raw data combined with knowledge of the business climate and processes to produce actionable information and recommendations.

Enable Effective Decision Making

One of the most important aspects of business are the decisions which drive execution. Business Intelligence is nothing more than an enabling function. It does not make decisions, people do. But, by utilizing the outputs of BI, decision makers can absorb key metrics, apply tribal knowledge and gut feel to result in effective decisions to drive their business forward.

So there you have it… Business Intelligence in a nutshell. How would you define Business Intelligence? Please join in and share your perspectives!

Tune in next week for: Data Warehouses vs. Data Marts