Evolution of ERP Data Warehousing | Business Information Warehouse for SAP (Prima Techs SAP Book Series)

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One of the most difficult problems in building a data warehouse is selecting the right mix of data warehousing products and tools. The continual rapid evolution of data warehousing tools makes the determination of a short list of products even more difficult. By now, you realize that a data warehouse consists of several architectural layers, each requiring a unique set of functionality, and hence several tools/technologies for each layer providing unique services. A typical data warehouse may have data extraction tools from one vendor (or homegrown), databases from a different vendor, and data warehouse construction tools from another vendor, with end-user data access applications built using several development tools. This situation becomes worse when individual organizations within a company select their own tools to develop data warehouses or data marts. Managing, training, and supporting several technologies, negotiating contracts for each product, and dealing with several vendors becomes a very expensive proposition.

The data warehouse construction scenario sounds very familiar to what happened to the earlier OLTP applications. Take a look at a typical applications landscape in a corporation.

Typically, a corporation may have one application for human resources, one for order administration, one for finance, one that tracks manufacturing, one for planning, and another to track deliveries-each serving a unique and discrete function. Fortunately, the OLTP world has some industry standards for business communications and technologies. Though the OLTP applications vendors provide similar products and speak common terminology to build mission-critical applications, they seldom use the same technologies. Integrating business processes among several OLTP applications to build a seamless supply chain management solution is still a major challenge. Here comes ERP to address the very same issue: business process integration.

Let's take a quick look at the evolution of ERP. Figure 1-5 shows the convergence of ERP industries over time. During the 1970s, manufacturing resource planning (MRP) systems evolved in the manufacturing industries to manage inventories. These applications worked but were not business-process-aware. Then, during the 1980s, MRP II was developed to improve process efficiency and data integration. During the late 1980s, Internet technology flowed out of the academic world into the business community; all the application vendors started to patch Web front-ends onto their applications, and the nightmarish task of integrating legacy applications over the Internet befell IT workers. Supporting hundreds of applications-sometimes similar in functionality-within a company, as well as the interfaces among them, became a very expensive proposition.

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Figure 1-5: Evolution of ERP Applications and Data Warehousing.

A few application vendors took this opportunity and packaged common business applications under one technology framework. The essence behind such packaged applications was integration and optimized resource utilization. Thus ERP was born. Most ERP vendors were also quick to declare their products to be Y2K-bug free. The early to mid-1990s were very good years for ERP vendors. That these applications were Y2K-bug free and provided integration had much to do with their acceptance in the business community.

The data warehousing industry, like ERP, has gone through its own evolution. In the 1970s, as shown in Figure 1-5, data warehouses existed just to track business processes and print those famous "greenbar" reports in batches for distribution to managers, who usually needed only a few sheets off the thick stack of reports.

Then, in the mid-1980s, a few companies launched departmental data warehousing projects, and a new term, "data mart," became common in the data warehouse industry. These data marts were quick to build and were used to understand business processes. Then, mostly spreadsheets were used for data storage and analysis, which in the 1990s led to extensive use of multidimensional and data mining technologies to analyze large amounts of data to improve business processes. Toward the late 1990s, the data analysis trend began shifting from business process improvements to prediction of business trends and provision of almost real-time feedback to OLTP processes to complete an in-progress transaction, such as detection of a fraudulent transaction.

This brings us to the beginning of the new millennium, when mission-critical applications and analytic applications are converging on a common infrastructure to provide robust enterprise information-supply-chain frameworks. This tight integration between OLTP and data warehousing is the essence of ERP data warehousing.

Today, the business world is characterized by an environment in which responsiveness and globally integrated operations are key to success. This success is achieved by using Enterprise Resource Planning (ERP). Software packages that support ERP are known as Enterprise Applications. Enterprise Applications, such as SAP R/3 and PeopleSoft, are sophisticated software suites that enable an organization to automate and integrate its supply-chain processes. ERP vendors have bundled several business-critical applications in an integrated fashion under one framework that is configurable based on individual company business models (rules).

Until recently, ERP vendors focused mostly on enhancing the infrastructure to deliver high-performance OLTP solutions. Very little attention was given to providing business intelligence applications to analyze massive amounts of data collected, or "jailed," within the ERP applications data repositories. Customers were left to building data warehousing and reporting solutions without any help from ERP vendors.

As stated earlier, one of the most difficult problems in constructing a data warehouse is selecting the right mix of data warehousing products and tools. Today, ERP vendors have recognized this need and have launched major development programs to deliver data warehousing solutions. Along with the ERP vendors' data warehouse initiatives, a wave of traditional data warehouse tools providers have launched ERP data warehousing initiatives. These ERP data warehousing initiatives extract data from ERP package applications to build reporting and data analysis environments, called ERP data warehousing. But what is ERP data warehousing?

ERP data warehousing is a framework of information objects that become the foundation of business intelligence and knowledge support systems across the enterprise, leveraging the infrastructure of ERP applications.

Note

Simply extracting data from an ERP application package is not ERP data warehousing. An ERP data warehouse supports a collection of integrated applications to report, analyze, and control business events across the enterprise, not just the data extractions.

True ERP data warehouses leverage the OLTP applications' infrastructure. But what is an ERP infrastructure?

ERP infrastructure is much more than a hardware configuration or networking gears; it is defined and characterized as the following:

System Configuration and Support. Similar methods and technologies to manage OLTP and data warehouse environments.
Development Life Cycle (Development-Quality Assurance-Production). Similar methodology between OLTP and data warehouse application development, change management, release control, project management, and path-to-production procedures.
Administration and Monitoring of Data Warehouse Operations (Performance, Logs, Backup, Restores, Batch Processes, Real-Time Processes, EDI). Similar tools and technologies to monitor and administer OLTP and data warehouse environment.
Enabling Technologies (DBMS, Middleware, Client), Multi-Tiered Architecture, Load Balancing, Debugging, Problem Tracking and Reporting, Intra-Instance Communication, High Availability, Database Performance Monitoring, Security Models, Metadata, and More.
Similar Implementation Methodologies and Support Structures.

These are just a few characteristics of an ERP infrastructure. When OLTP and data warehousing solutions are based on similar architectures, tools, technologies, and development and deployment methodologies, you do not need to build teams dedicated to support unique applications.

Among all ERP vendors, SAP is leading the ERP data warehousing initiatives with its offering, SAP Business Information Warehouse (SAP BW). Note that the SAP BW scope and function is not limited to traditional data analysis and reporting, but that SAP BW is the core product among SAP's New Dimensions product set (which includes Customer Relationship Management and Advance Planning Optimizer). SAP BW will support several business processes within an enterprise as well as the information needs of partners, vendors, and customers. SAP BW is truly an extraprise data warehouse.

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