Information Systems Development
This essay investigates the current trends in Information Systems Development. It is rare to find an organization in any industry that does not maintain numerous databases to support core business processes. In today's knowledge-base economy, the information compiled and created in an organization is often amongst the company's most valuable assets. Knowledge, its structure, organization and accessibility are commonly acknowledged as key strategic differentiators for many organizations. The development of large-stand alone databases (or data repositories) is no longer the norm for many organizations. Stand-alone databases are being replaced with out-of-the-box database application solutions such as CRM or ERP systems. Legacy stand-alone databases that support key operational processes are being linked to other stand alone or vendor databases in order to support business operations. The development of database systems is rapidly becoming a collaborative effort across enterprises. The true value of organizational information is its ability to inform and empower employees across the company and along processes. In most companies today, databases and the information contained within them are accessed by hundreds or even thousands of employees during the course of the workday. Database development has become the responsibility of every employee who inputs or extracts information from the system in order to support business processes. The issues associated with maintaining database integrity and data stewardship will be discusses in the context of today's shared database development environment.
Information systems have three components: data, processes, and people. The development of information systems requires that users determine what data or information needs to be captured along with associated attributes. The data stored in an information system is only valuable if it provides information about a given process (manual or automated) or activity that is being recorded. The analyses of data and the associated processes are evaluated by a person who completes the "system."
Relational databases provide the data structure for many information systems. Relational databases are made up of a number of tables that have information arranged in rows and columns. The true value of this type of database is that records from one table are related to records in other tables, which allows for easy extraction of related information or records. Prior to the development of the relational database model, data was stored in flat files or computer files that could only be read sequentially. A person reviewing a flat computer file cannot intuitively relate information in a meaningful way. It is important to note that a person is a required element of an information system as opposed to merely the digital information contained within.
Legacy Information Systems
A number of organizations rely on legacy information systems to run core operations and key business processes. Their standalone information database systems were developed in-house to meet production and data management needs. Integrating information systems has become a requirement of today's business world, however. Thus, legacy systems can be viewed as a liability to business process integration and can put a company at strategic risk in the marketplace.
Portfolio management of IT assets is a critical task for many IT departments. Compiling an IT portfolio requires a thorough assessment of all applications and systems within an organization and can be a sizable undertaking for an IT department. Portfolio assessment to ascertain business risk involves several steps. Once a list of assets has been compiled, each application should be reviewed for the risk it poses to business operations should it fail. The two biggest risks to business operations are: catastrophic failure of a key system and the constraints placed on an organization to support new business initiatives due to inadequate systems. Knowing the business risks posed by legacy systems allows CIOs and other executive management personnel to make decisions about whether to migrate or replace legacy information systems.
Migration StrategiesCIOs have multiple options for migration strategies, but systems should be migrated selectively and only after a thorough portfolio analysis. CIOs can adopt a strategic approach that leaves core legacy functionality intact and just adds functionality by using newer tools and technologies. Or legacy functionality can be replaced with modern technology by installing packages, replacing the legacy application with an external service, custom-coding a replacement, or a combination of these (Head, 2007).
Vendor Solutions to Information System Development
The implementation of vendor solutions in information systems development has become a common business practice. Vendor solutions require fewer in-house resources for implementation and deployment and allow IT and development staff to work on other strategic solutions. Vendor applications also offer the advantage of interoperability with many other software solutions. Because applications need to mirror business processes from end-to-end, integrated applications are quite desirable.
The biggest factors influencing information systems development are driven by the business requirements of an organization. The following topics are discussed within the business strategy/information system development context:
- Increased user interaction with information systems;
- Examples of information systems;
- Data migration from legacy systems (ETL-extract, transform, load);
- Data governance; and
- Information lifecycle management.
Explosion of Digital Data
Organizations have been documenting corporate knowledge at an unprecedented rate. There are several reasons for the explosion of digital data being created within organizations large and small. An increasing number of workers have been directly involved with capturing or creating information about business processes, customers, or products. Many organizations have also been converting historical data to digital format and thus have been making the information easily accessible through information systems. Estimates from some industries put the growth of digital information at between 60% and 200% a year in 2007; this includes data in relational databases and unstructured content such as email and network files and other non-relational databases (Enterprise Content Management, 2007).
Organizations have responded to the explosion of digital data by creating a new generation of information systems that allow for better storage and retrieval of knowledge-based assets. Enterprise data warehousing (data marts), management information systems (MIS), and content management systems (CMS) are a few of the information systems that have been deployed in organizations.
An enterprise data warehouse is a large database that is meant to store a company's historical data and corporate knowledge. The data warehouse is an information database that may be surrounded and accessed by any number of enterprise systems including: a customer relationship management system (CRM), supply chain management system (SCM), or corporate performance management system. Data warehouses have been popular because they collect vital company information in one central information system and can eliminate the need for multiple information database systems.
Many first generation data warehouses have not lacked in raw data, and many have done a good job of supporting enterprise systems that are highly transactional in nature. For instance, these systems have done a good job of linking together financial transactions (accounting records) with their associated operational transactions (purchase orders, deliveries, inventor movements, invoices, etc.), creating a joined path back to the data points needed to determine the actual cost of acquiring a product from a supplier (Foulkrod, 2007). Where most data warehouses have not done such a good job is in aligning financials to business operations on a granular level. This "content deficiency" has been caused by a lack of ability to tie a business context to much of the data in the warehouse (Foulkrod, 2007). Business rules need to be associated with data in the warehouse -- the process of applying context to enterprise data can be described as tailoring or content enrichment. In other words, a person must interact with the raw data and apply design principles, with the ultimate objective...
(The entire section is 3833 words.)