Easily Amused for No Apparent Reason

The word “integration” is bandied about so frequently and in such a cavalier manner, it is assumed that everybody knows what integration is.  However, integration means a lot of things to a lot of people.

The Merriam-Webster online dictionary definition of integration says:

1: the act or process or an instance of integrating: as a: incorporation as equals into society or an organization of individuals of different groups (as races) b: coordination of mental processes into a normal effective personality or with the individual’s environment2 a: the operation of finding a function whose differential is known b: the operation of solving a differential equation

The first definition describes one of the great socio-political accomplishments of the latter part of the twentieth century, and the latter definition refers to a complex mathematical equation.  However, this doesn’t really work for our purposes.  A more useful definition from TechDictionary.com:

Putting diverse hardware and/or software components together to work as a system.

That’s a little bit better.  However, when we narrow the term down to data integration, and we get my favorite definition, one provided by Georgetown University on a glossary page on Data Warehousing:

Data Integration The movement of data between two co-existing systems. The interfacing of this data may occur once every hour, once a day, etc.

That’s it, it’s as simple as moving data between two co-existing systems. This can be done in four different ways:

Migration: moving data from a legacy application, with data stored in a legacy format such as Cobol or Isam, to a modern CRM or ERP application. This is usually a one-time movement of massive amounts of historical data.

ETL: Extract, Transform and Load of data. Extracting data from operational applications, such as CRM, ERP, accounting, manufacturing, or other systems into a database used for the sole purpose of manipulating the data and reporting on the data, usually for business analysis purposes. This is usally the movement of large amounts of data in a batch process, durng certain intervals such as hourly, nightly, weekly, etc.

Application Integration: The movement of data in small chunks between two business systems, such as from a CRM application to an ERP system, or from a manufacturing system to an accounting system.  This is usually done at an API level, as opposed to through the database or text interface as is more typical of the first two scenarios, and is usually event-based and real-time, or near real-time.

B2B: Integration of data between trading partners, such as wholesalers, manufacturers, retailers, transportation companies, etc.  This also is usually real-time or near real-time, and event based, and entails transforming EDI documents or documents in any other format, transported over the internet, ftp, EDI VANS, etc.

There are many tools out there that do one or the other of the above scenarios, and some even do all of them.  The best integration tools for a company usually depends on what their primary focus is, how much data is being moved, the required frequency and speed of data integration, among others. Integration tools are usually not a one-size fits all solution; however, there are some tools that are very flexible, or rather agile, that can be used for almost all data integration scenarios. Most companies, if they’ve been around for any length of time, usually have diverse integration needs, and so sometimes it makes more sense for them to acquire a tool that can span the breadth of integration scenarios so as to capitalize on a one-time investment in software as well as knowledge.