Friday, December 4, 2009

Business Intelligence Status Report

Economic and regulatory pressures have made a broad set of technologies called business intelligence (BI), more important than ever for all enterprise application users. Users rarely feel satisfied with the amount of information they can extract, if they can extract any at all, from their enterprise applications. Enterprise resource planning (ERP) and BI (sometimes called analytics, which is specialized analytical software) are inseparable concepts, but they have taken different trajectories and evolved differently.

ERP systems have positively transformed many enterprises' business processes, yet many users feel oversold because ERP appears to inhibit access and lock up vital information. I In most traditional ERP systems operational activities are grouped together to form artificially created processes, which bear little resemblance to the actual business activities. For example, the focus of ERP has often been to get the correct figures into the general ledger (GL) and create a transactional glut (for more information on the genesis of enterprise applications, see Enterprise Applications—The Genesis and Future, Revisited.).

Conversely, BI, which has for few decades been called executive information systems (EIS), offers a new breed of similar, but more insightful and functional tools to help enterprises operate more efficiently and profitably. Many manufacturing and distribution enterprises of all sizes are amenable to leveraging software that would not only sense the daily pulse of the operations, but would also spot incongruities, analyze the performances of multiple areas, and initiate corrective adjustments. BI tools promise to help "rank and file" employees harness data too complicated for manual manipulation. For instance, few departments are as hard pressed for new tools as purchasing and sourcing, where rapid increases in materials costs, greater deviations in lead times, and supplier base growth and instability require ever increasing buyer dexterity. BI can provide this dexterity.
Enterprise software systems are designed as transaction processing tools and, nowadays the main job is to optimize an informed decision-making process for users at all levels of the organizational hierarchy. Recent trends seem indicate that access to key operational data is no longer under the purview of executives alone. Many manufacturing executives today are allowing (if not pushing and encouraging) access to operational performance data to the shop floor and in distribution centers to enable better and more timely decision-making by operators.

Most operational data in ERP systems—and in its younger siblings like supply chain management (SCM) or customer relationship management (CRM) is stored in what is referred to as an online transaction processing (OLTP) system, which is a type of computer processing where the computer responds immediately to user requests. Each request is considered to be a transaction, which is a computerized record of a discrete event, such as the receipt of inventory or a customer order. In other words, a transaction requires a set of two or more database updates that must be completed in an all-or-nothing fashion. The opposite of transaction processing is batch processing, in which a batch of requests is stored and then executed all at one time. In other words, transaction processing requires interaction with a user, whereas batch processing can take place without a user being present. Still, both approaches result with an immense number of records in the database.

To further refresh our memory, a database is a collection of structured data that is application-independent. This data processing file-management approach was designed to establish the independence of computer programs from data files, whereby redundancy is minimized, and data elements can be added to, changed, or deleted from the file structure without changing existing application programs.

Relational database are most commonly used in enterprise applications nowadays. A relational database is a software program that allows users to obtain information drawn from two or more databases that are made up of arrays of two-dimensional data (tables). Contrary to this, a hierarchical database is a method of constructing a database that requires that related record types be linked in tree-like structures. In this instance, no child record can have more than one physical parent record.

Relational databases are more powerful than the others because they require few assumptions about how data is related or how it will be extracted from the database. As a result, the same database can be viewed in many different ways. Another important feature is that a single database can be spread across several tables, which differs from, for example,, flat-file databases, where each database is self-contained in a single table. Accordingly, relational databases are prevalently deployed within enterprise applications.

Bundled with this are database management systems (DBMS) that access data stored in a database and present multiple data views to end users and application programmers. They are a collection of software programs designed for organizing data and providing the mechanism for storing; maintaining or modifying; and retrieving or extracting data on the database. A DBMS separates data from the application programs and people who use the data, and permits many different views of the data.

From a technical standpoint, DBMSs can differ widely, since terms such as relational, network, flat, and hierarchical all refer to the way a DBMS organizes information internally, which can affect how quickly and flexibly users can extract information. For example, a relational databasee management system (RDBMS) is a type of DBMS that stores data in the form of related tables, whose architecture is based on a formal method of constructing a database in rows and columns using rules that have formal mathematical proofs. In these systems, which originated in the work of EF Codd, relationships between files are created by comparing data, such as account numbers and names. In addition, an RDBMS has the flexibility to take any two or more files and generate a new file from the records that meet the matching criteria.

No comments:

Post a Comment