Einstein made that famous statement many decades ago, and it's still relevant today for building superior software systems. Unfortunately, as anyone who has been in the IT industry for long can point out, far too many software systems have failed Einstein's test. Some are made too simple to carry out the duties they are supposed to perform. Others are made too complex, and the costs of building and maintaining them have rocketed, not to mention the nearly impossible tasks of integrating different systems together
Businesses nowadays operate in a fast changing and highly complex environment, with more competitors fighting for potential clients. This environment calls for businesses that have the ability to rapidly react on changes and thus are highly flexible in their nature. With the high amount of knowledge available to businesses it
becomes harder to identify changes in the market and make the correct decisions. This is where Business Intelligence comes into discussion which aims at supporting exactly this process of evaluating the data and knowledge available and making decisions. But knowledge is often stored in different locations throughout the
business, especially in international businesses with many different country offices the issue of different IT-applications used that can not communicate with each other appears to be a major problem. This creates a demand for service-oriented architecture.
Overt the last four decades IT systems have grown exponentially, leaving companies to handle increasingly complex service architectures. Traditional architectures have reached the limit of their capabilities, while traditional needs of IT organisations persist. IT departments still need to respond quickly to new business
requirements, continually reduce the cost of IT to the business and an integrate new business partners and customers.
In this paper I would like to take a closer look at the concept of service-oriented architecture and examine the role of it with regards to Business Intelligence.
At first I will introduce the topic of business intelligence, in the second part of the paper which is my main focus, I aim at providing deeper insight on service-oriented architecture. I will then concentrate on the question how this architecture is connected
to Business Intelligence, giving a case study of Deutsche Post as example.
INDEX
1. INTRODUCTION
2. BUSINESS INTELLIGENCE – DEFINITIONS AND TASKS
2.1 THE VALUE OF BUSINESS INTELLIGENCE
2.2 THE BUSINESS INTELLIGENCE PROCESS
3. SERVICE ORIENTED ARCHITECTURE (SOA)
3.1. WHAT IS UNDERSTOOD BY A SOA?
3.2. REQUIREMENTS FOR A SOA
3.3. CHARACTERISTICS OF A SOA
3.3.1. The SOA Temple
3.4. DEFINITION OF „SERVICE“ FOR SOA
4. SOA FOR BUSINESS INTELLIGENCE
4.1. THREE PROCESS PHASES OF BI WITH SOA
4.2. BENEFITS OF SOA FOR BUSINESS INTELLIGENCE TASKS
4.3 WHAT THE TRANSFORMATION OPPORTUNITY LOOKS LIKE
5. CASE STUDY: IMPLEMENTATION OF A SERVICE ORIENTED ARCHITECTURE AT DEUTSCHE POST MAIL
6. CONCLUSION
7. REFERENCES
FIGURES
Figure 1 Close up Look at SOA (source: CAPGEMINI, 2005)
Figure 2:The n(n-1) integration problem (source: Channabsahavaiah Kishore; Holley Kerrie; 2004)
Figure 3: The SOA Temple (source: Dostal et al. 2005)
1. Introduction
Things should be made as simple as possible, but no simpler." -- Albert Einstein
Einstein made that famous statement many decades ago, and it's still relevant today for building superior software systems. Unfortunately, as anyone who has been in the IT industry for long can point out, far too many software systems have failed Einstein's test. Some are made too simple to carry out the duties they are supposed to perform. Others are made too complex, and the costs of building and maintaining them have rocketed, not to mention the nearly impossible tasks of integrating different systems together
Businesses nowadays operate in a fast changing and highly complex environment, with more competitors fighting for potential clients. This environment calls for businesses that have the ability to rapidly react on changes and thus are highly flexible in their nature. With the high amount of knowledge available to businesses it becomes harder to identify changes in the market and make the correct decisions. This is where Business Intelligence comes into discussion which aims at supporting exactly this process of evaluating the data and knowledge available and making decisions. But knowledge is often stored in different locations throughout the business, especially in international businesses with many different country offices the issue of different IT-applications used that can not communicate with each other appears to be a major problem. This creates a demand for service-oriented architecture. (Channabsahavaiah Kishore; Holley Kerrie; 2004)
Overt the last four decades IT systems have grown exponentially, leaving companies to handle increasingly complex service architectures. Traditional architectures have reached the limit of their capabilities, while traditional needs of IT organisations persist. IT departments still need to respond quickly to new business requirements, continually reduce the cost of IT to the business and an integrate new business partners and customers.
Now, service oriented architectures (SOAs) are being promoted as the next evolutionary step to help IT organisations meet their ever more- complex challenges.
In this paper I would like to take a closer look at the concept of service-oriented architecture and examine the role of it with regards to Business Intelligence.
At first I will introduce the topic of business intelligence, in the second part of the paper which is my main focus, I aim at providing deeper insight on service-oriented architecture. I will then concentrate on the question how this architecture is connected to Business Intelligence, giving a case study of Deutsche Post as example.
2. Business Intelligence – Definitions and Tasks
Business Intelligence is an often discussed topic in the last decade. Business Intelligence can not be understood as a new product or method, it is rather a concept. There are many definitions of Business Intelligence to find in literature. Business Intelligence is about utilizing data from internal and external sources in such a way that helps making better decisions. It is about large amounts of data (which then leads to topics as data mining, data warehouses, etc.), how one can get useful information out of this data and then use it for making better decisions in order to gain competitive advantage.
Business Intelligence (BI) gives the ability to gain insight into the business or organization by understanding the company's information assets. These assets can include customer databases, supply chain information, personnel data, manufacturing, and sal]es and marketing activity as well as any other source of information critical to your operation.
Business intelligence software allows the integration of these disparate data sources into a single coherent framework for real-time reporting and detailed analysis by anyone in the extended enterprise – customers, partners, employees, managers, and executives.
The first time the term was used was in September, 1996, when a Gartner Group report said:
“By 2000, Information Democracy will emerge in forward thinking enterprises, with Business Intelligence information and application available broadly to employees, consultants, customers, suppliers and the public. The key to thriving in a competitive marketplace is staying ahead of the competition. Making sound business decisions based on accurate and current information takes more than institution. Data analysing, reporting and query tools can help business users wade through a sea of data to synthesize valuable information from it- today these tools collectively fall into a category called Business Intelligence” (Channabsahavaiah Kishore; Holley Kerrie; 2004)
2.1 The Value of Business Intelligence
According to the PricewaterhouseCoopers Data Management Survey of 2001, “Companies that manage their data as a strategic resource and invest in its quality are already pulling ahead in terms of reputation and profitability”.
This statement implies a quite subtle yet radical notion: Data should be treated as strategic resource. According to a traditional view, data is the “fuel”, driving the automation of a business operation, implying that a company uses computers to help run its business. The forward looking view of data internalizes the notion that strategic knowledge is embedded in the collection of a company’s data and that extracting actionable knowledge will help a company improve its business.
This leads to another intriguing idea- that a company may acquire a competitive edgy by viewing itself as an information business instead of taking the traditional industry- or vertical- view. Consider: Is a supermarket chain a business that sells food, or is it a business that exploits knowledge about customers preferences, geographical biases, supply chain logistics, product lifecycle, and competitive sales information to optimize its delivery, inventory, pricing, and product placement as a way to increase margin for each item sold. The answer to that question (and its corresponding versions in any industry) may ultimately determine your company’s long term viability in the Information Age.
“So how do you transform data into a strategic resource?. A part of that process involves properly applying new technology to your data, but the most important part is being able to understand and subsequently build the business case for the value of information.” (Fielding, 2003)
As mentioned, most companies collect a large amount of data from their business operations. Business Intelligence refers to in depth analyses of company data for better decision making. The technology and processes that make this analyses possible take unwieldy collections of information and translate them into organized, readily- accessible, human readable compilations of data. With an effective Business Intelligence tool, companies can easily track their own operations, their customers’ activity patterns, and industry trends.
2.2 The Business Intelligence process
The business intelligence process can be broken down into the following three stages:
1. Data
2. Information
3. Knowledge
Raw data is gathered and processed into information. The information must be filtered and arranged into meaningful patterns. The knowledge drawn from that data analysis helps to form the business intelligence of a corporation.
Business intelligence varies across industries. The functional area and particular processes under examination play a role in the type of date gathered and the range of knowledge sought. Common functional areas include: Sales and Marketing, Human Resources, Operations and Finance.
Sales and Marketing department track products, customers, demographics, promotions, sales forces, order type, and other related fields. Human resources groups often look to measure employee, organisational and department issues. Assembly speed, warehouse stock, manufacturer and supplier cost, and shift productivity are the domain of operations management. Finance departments wills closely watch data on topics such as currency standards, account information, and industry trends.
“Good business intelligence means balanced information. Too much or too little data is not useful. Corporations can focus in the most crucial improvements by setting reasonable limits on the information gathered, coordinating the efforts around a company wide strategy, and employing business intelligence systems.” (Fielding, 2003)
3. Service Oriented Architecture (SOA)
3.1. What is understood by a SOA?
In the last decades a tremendous number of different software technologies have been developed, with always new and different programming languages and different interfaces that can not communicate with each other easily. There was not one standard to use thus creating a manifold pool of different techniques.
With the many different systems we artificially created a high dependency. The trouble with this dependency is that it is not a real dependency where one system relies on the functionality of another system, but it is an artificial dependency, which means that it is a real challenge to achieve communication between two different systems, making it complicated to create a connection from one system to the other. (Hao He 2003)
A Service-Oriented Architecture can be seen as an architecture that aims to achieve this loose coupling among software agents. This loose coupling in SOAs is based on communication between different applications. Due to the fact that communication does not necessarily happen between human beings or between one human being and a computer, but also moves towards a communication between applications, the approach of service-oriented IT-architecture becomes necessary. (Dostal et al. 2005)
Dostal et al. (2005) define this architecture as being an abstract concept, with the tasks of providing, searching and utilizing “services” through a network :
“An SOA can be understood as a system-architecture that represents manifold, different and possibly incompatible methods or applications as reusable services with open access and therefore provides a platform- and language-independent utilization and reuse.”
To clarify the idea of how a SOA works Hao He (2003) uses the example of CDs. CDs can be played with any CD player which offers the service of playing CDs. This is a perfect example of a SOA. In contrast if each CD would require its own player and would not work with other players, this resembles how many software systems are built. This example shows that building service-oriented architecture makes perfect sense.
Also, most businesses today operate with a project based integration approach. This approach is characterised by the use of native application technology and embedded data and process management. It also assumes little or no change, makes limited use of common resources and focuses on “big bang” application deployment projects.
A project based integration approach:
- Results in risk, costs and delay for the first delivery
- Resist in change
- Prevents a process centric approach
- Precludes end to end process/information visibility
Therefore, architecture is the key of bringing coherence to an organisation. SOA knocks down barriers and creates a more open system. It is characterised by an extensive reuse of common data and processes, a process centric approach with supervisory process management, and an assumption of continuous change. As one CEO recently told: “We have a lot of projects going on now where people are using Service Oriented Architecture. The problem is that I’m pretty sure all of those turn to be incompatible and potentially explode on us” In this citation lies the danger: The lack of coordination and direction. Consider what happened in the case of the rampant process re engineering that took place in recent years. Enthusiastic and empowered departments and business unit leaders achieved great improvements in individual processes, but the transformation programmes were usually not robust enough to create lasting change across the entire enterprise, not to mention between the enterprise and its customers and trading partners. (CAPGEMINI; 2005)
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