When thinking about fathers of information technology, topics like data warehousing, business intelligence and relational databases come to mind The people most often viewed as the fathers of these technologies are Bill Inmon, Howard Dresner, and Dr. Ted Codd, respectively. While there is no question that these people have made major contributions to the industry and brought each of their respective technologies to the forefront of people’s thinking, did they really “create” and “invent” the technology?

Let’s consider DW appliances first. As I stated in my previous blog, Netezza was one of the prime movers in getting DW appliances accepted in the industry. Before moving to Dataupia, Foster Hinshaw was the CTO of Netezza, and therefore played a major role in the birth of the DW appliance.

Appliances of course have been around for a long time. Think of toasters, for example (the bread kind, not the Battlestar Gallactica kind). In IT, Network Appliance was one of the first vendors to introduce a hardware appliance. Cisco routers and telephone switches can also be thought of as appliances.

I personally think DW appliances go back to the days of database machines. The creators of those machines were people like Phil Neches who designed the DBC/1012, which became Teradata’s first offering. Other key people at that time were David Britton and Geoffrey Lee who created the Britton-Lee database machine. Their company and technology was later renamed Sharebase. It was subsequently acquired by Teradata who buried it.

Howard Dressner, formerly with Gartner and now CSO of Hyperion (recently acquired by Oracle), is often associated with the term business intelligence. The wikipedia entry for business intelligence states, “In 1989 Howard Dressner, a Research Fellow at Gartner Group popularized “BI” as an umbrella term to describe a set of concepts and methods to improve business decision-making by using fact-based support systems.” I really like the word “popularized.”

On the data warehousing front, Bill Inmon is viewed as the father of data warehousing. The concept of data warehousing was actually invented largely in IBM by Barry Devlin, who (somewhat tongue in cheek) describes himself the “grandfather” of data warehousing.

Nobody would question that Dr. Codd is the father of the modern day relational DBMS. He was after all the inventor (and thus creator) of the relational model. Chris Date also played a major roll in making the world aware of Dr. Codd’s work. I don’t think he would mind me saying he “popularized” relational technology. He would be appalled, however, if I described him as the father of relational database.

The bottom line for me is that there are the inventors who create new technologies, and there are people who popularize them. These roles may be performed by the same people, but often they are not. Rather than people saying they are the “father” of something, I would prefer they said they “popularized” something. This is a less loaded term and has the same impact on the industry. I of course wouldn’t say I popularized my children!

The problem for the DW appliance vendors is that this market is becoming crowded. Not only are there new entrants like Datallegro, Dataupia and Paraccel, for example (company names don't get any easier do they!), but also system vendors such as IBM and HP are waking up to the fact that the appliance vendors are starting to erode some of their market share, and are now fighting back with one package and one install solutions.

While interviewing DW appliance customers for the study Richard Hackathorn and I are doing on DW appliances, one user remarked, "We don't use the term appliance, we just see it as a big computer." The bottom line here is that the vendor that produces a "big computer" for data warehousing with the best TCO, most flexibility, and best price is going to be the winner!

This point was brought home to me while teaching a class on operational BI with Claudia Imhoff at the recent DAMA conference. It became obvious that some people came into the seminar thinking of operational BI in terms of data warehousing. When I started talking about the concept that operational BI should be process driven and tightly integrated with (and possibly embedded in) operational processes, it came as somewhat of a surprise to some attendees that data warehousing didn’t appear in the picture.

I also discussed master data management (MDM) on the seminar. It would be reasonable to ask what MDM has got to do with operational BI. Well the problem is that some so-called operational BI applications are not really BI applications, they are MDM applications. An example would be creating a single view of the customer. This has nothing to do with BI. It’s an operational issue, not a decision support one. This doesn’t mean to say that integrated customer master data cannot be used in business intelligence processing.

Hub products that frantically move data into an operational data store or data warehouse to create a single view of something add latency to the data, and are simply papering over the cracks of master data problems, rather than trying to solve the issue at the source, i.e., in the operational systems.

We should be aiming to put less data into the data warehousing environment, not more. Our long term objective should be to eliminate the data warehouse. The first step in this process is to remove master data from both operational transaction systems and from the data warehouse. This data should be stored in a separate master data store (MDS) that is maintained by separate master data applications. We can start to do this as we redesign our operational systems and move to a services-oriented architecture. The MDM system simply becomes a service. In this scheme, the MDS contains both current and historical master data. Both operational and BI applications can access the master data by calling the MDM system as a service. Initially, for performance reasons, business view subsets of the master data may be replicated into a data warehouse to act as dimension tables.

Removing master data from the data warehouse has the advantage of also removing much of the complexity and many of the data quality problems from data warehouse design. A separate MDM environment also simplifies the operational data store (ODS). The ODS now only needs to contain integrated business transaction data. The ODS effectively becomes an operational transaction data store, or OTDS.

The concept of splitting an ODS into an MDS and an OTDS was well accepted by many of the seminar attendees. I have seen several companies in both the US and Europe do this. In some cases the decision support environment consists of an OTDS, MDS and data marts, i.e., there is no enterprise data warehouse. Heresy, I hear people say. My answer is that we have to start thinking outside of the box. For example, there are some very viable search technologies appearing that also enable organizations to build BI applications without the need for an data warehouse.

Some of my comments above are a little tongue in cheek. The objective is to get people to accept that a data warehouse is not always required for business intelligence, and as I said earlier, the long-term objective should be to eliminate the data warehouse. Comments?