Enterprise Data Warehousing and The Future of Business Software Systems

Enterprise data warehousing, a technology that powers organizational databases that are used mainly for reporting and analysis purposes, is not among those technologies that fuel media gossip but its importance for the future development of business software applications is nonetheless considered essential by all and every industry expert. Organizations, both government agencies and private enterprises need business software tools to analyze data and take insightful strategic decisions, while business intelligence tools largely rely on data warehouses to provide the necessary data integration and data access layers that make it possible for raw data to be transformed into readable reports in the application's interface.

To put it simply, data warehousing is an important element of all and every business software application in a global business environment where information is collected from numerous sources in real-time and where vast amounts of data must be stored, processed, and analyzed before taking an informed managerial decision. The technical details concerning this method and technology to store information in a reliable way and retrieve data for further reporting and analysis are not that important, but the main point is that data warehousing is now considered a must-have technology when the matter in question is to design and implement a reliable business application like an enterprise resource planning (ERP) system and other kinds of enterprise-level software tools.

Usually, a large organization would deploy different source systems while enterprise data warehouses allow for integration of data from multiple sources, thus enabling managerial staff to get access to all data involved in strategic decision making. A great part of the functionality of business software systems like ERPs and customer relationship management (CRM) applications involves dealing with databases on top of which complex reports are produced. Therefore, all those systems incorporate data warehousing functionality to store, catalog, and retrieve data and meta-data.

All those business intelligence tools, like any other similar tool in the past, are essential in running a successful business, business analysts agree. Systems that feature enterprise data warehousing functionality are still evolving, adding collaboration and industry-specific capabilities, while analytical software applications are now provided both as standalone solutions and software-as-a-service tools. Nevertheless, the core functionality of those systems is all the same and enterprise data warehousing is the technology that allows those business intelligence tools to operate as intended.

Analytical processing and market research are so important in a global business framework that business intelligence is more decisive than ever before. In a fast-changing online environment it is not only about storing data in a reliable fashion but to process those data fast and produce trustworthy reports and analysis. Modern organizations simply cannot afford to save on data warehousing technologies and tools for enterprise data warehousing as a technology and a method provides one of those competitive advantages that would be decisive for the overall success of an organization in the years to come.

Major Benefits Provided by Enterprise Data Warehousing

Enterprise data warehousing is a topic rarely discussed in non-specialized mass media simply because the subject is not very attractive to inexperienced writers, not because the very method to store, process, and analyze data is not business-critical to a great number of enterprises worldwide. As its name suggests, data warehousing deals with enterprise databases that are used primarily to store essential business data and generate reliable reports based on these data. As a rule, most enterprise data warehouses use a software architecture layer where information is transformed into data that can be further processed to produce comprehensive reports provided to managerial staff within an organization.

The most obvious benefit of enterprise data warehousing is that data is cataloged and cleaned to to create a uniform database where business information is stored and retrieved when a report is generated. Creation of metadata provides great advantages when the matter in question is to make compatible different databases, for example following a corporate merger. In addition to metadata creation, enterprise data warehousing functionality includes methods to maintain data history, which is a crucial functionality since a good number of source transaction systems do not support such functionality.

Software developers and software vendors often take advantage of data warehouses, incorporating the above functionality into operational business applications to increase their added value. Those business applications may include customer relationship management (CRM) systems, while enterprise data warehousing is widely used in enterprise resource planning (ERP) systems used across a variety of industries. Business software applications that deal with databases usually require consistent codes to be assigned to every piece of information, which is made through migration to an enterprise data warehouse.

In the long-term, all and every functionality listed above adds to the benefits provided by data warehouses used in business by presenting the information belonging to an organization in a consistent fashion. Many industries, both manufacturing businesses and financial institutions, cannot operate smoothly without such databases and an extremely reliable method to process the information contained in these data warehouses. The same applies to a single common data model required by large businesses and government agencies across the world, while data warehousing as a method is able to provide the required functionality to all interested parties.

Another advantage, often underestimated, is that data warehouses are the main tool used to restructure information stored by organizations into data that can be easily read and understood by users. That said, data warehousing is really business-critical when under scrutiny is the ability of a business application  to present data in a way that makes sense to users, both novice and experienced customers. Data restructuring requires serious software development efforts to provide reliable results and secure the flawless operation of the respective business software system, thus those systems can be a costly investment, which, of course, depends on the size of the business and the complexity of the databases to be covered by the software.

Last but not least, data restructuring methods applied in enterprise data warehousing give a marked boost to query performance when analytic queries are performed, this is a common operation that sometimes causes corporate servers to go down. Those computer crashes often occur at operating system level, while data warehouses are designed to reduce operating system load usually experienced when computers process large volumes of database data. Therefore, enterprise data warehousing is undoubtedly a major factor in securing a business system's uninterrupted operation while the data warehouse itself deals with the zillions of bits of information a large organization usually stores on its servers, thus providing marked benefits to both businesses and their respective customers.

Main Applications of Enterprise Data Warehousing in Business Applications

Enterprise data warehousing is used in a wide variety of business applications that deal with processes and info used in decision support, logistics and inventory management, forecasts in the field of financial data analysis, and trend analysis across virtually all and every business sector. Data warehouses are used to generate reports and analyze certain data, and although this is a very broad definition of data warehousing in the context of business software applications the nature of those databases can easily be described in a broader context since business data is only bits of information stored in digital format.

Business data, actually any data, is stored in those databases with the aim to catalogue information that may come from different sources and to transform it into data that can be processed for later use by managers at any level. Decision making is a process where data warehousing may be of great importance when at stake is to take a decision that could affect the overall business strategy of an organization, for example. Market research is another field where enterprise data warehousing is widely used. Enterprise resource planning systems (ERP) are good example of business software that rely heavily on principles and methods used to store and analyze through the means of data warehouses. Those systems have to deal with large volumes of information that have to be retrieved from a database, processes in a specific manner, and then loaded into an analytical software module.

Actually, enterprise data warehouses have to deal also with meta-data, or data on other data, which is quite a challenging task to perform in the framework of large and complex business systems which may contain tones of information on different topics or myriads of items. A large multinational organization usually have data repository containing millions of records which have to be catalogued thus creating quite a complex meta-data object.

Business intelligence tools are considered crucial instrument for designing successful organizational strategies and rarely a high-class business intelligence application will lack functionality to connect to a data warehouse and get data from such a system. Consequently, software developers and software vendors have to design and implement complex software architecture to cope with the challenges offered by enterprise data warehousing. One of the main challenges is related to data coming from a variety of sources, often times in different formats, while the outcome should be data that can be used for analytical and reporting purposes.

As far as business intelligence is concerned, data warehouses will always play an important role in the overall process of creating a reliable business software application. Enterprise data warehousing is not simply a market niche where only large corporations can be considered as prospect customers but a must have tool that should be incorporated into applications used by small and medium sized businesses that do not want to see their competitiveness decrease. Naturally, the use of data warehouses is not limited to business intelligence but most market analysts agree that this is the segment where deployment of complex data warehouses will be crucial for eventual business development.

Bearing in mind that decision making has always needed adequate support by business intelligence the vast majority of market analysts are of opinion that future enterprise software applications will not be viable without a sort of enterprise data warehousing functionality. Business software solutions that feature such functionality are not necessarily cheap but investing in a software system that is enabled to take advantage of enterprise data warehousing will pay off in the long term through improved decision making process which in turn will boost overall performance of the organization.

Positive Effects of Data Warehousing in Business Intelligence of Enterprises

Contemporary software systems aimed at helping managers in the decision-making process usually incorporate Data warehousing in business intelligence applications developed to identify, extract and analyze business data. High-quality and valuable data can be analyzed in a manner that helps enterprises gain competitive advantage over their rivals, enjoying all benefits predictive analysis can provide. Actually, business intelligence systems rely on historical data in large volumes, thus providing neutral view on information collected, while utilizing such data to forecast trends and estimate future market movements, for example.

A major property of business intelligence is its ability to equip corporate executives with valuable tools that facilitate and enrich decision making through analysis of large volumes of data that is otherwise non-analyzable. Data warehousing plays an important role in this process, providing the basis and means for retrieving such data and loading it into a repository, where the information can be cataloged and analyzed. Professionals and scholars are well aware that the ability to analyze huge volumes of data can produce amazing results in terms of future trends predictability and customer behavior forecasting. Data warehousing and business intelligence, in a broader context, provide the essential principles on which modern-day systems facilitating decision-making are made.

Using data warehousing and business intelligence tools, managers and business owners can track how projects and business programs are progressing and compare their progress against a previously adopted broader corporate strategy. Predictive analytics and predictive modeling have proved to be invaluable instruments when the matter in question is to design a working sales strategy or a targeted marketing campaign, for example. Business process modeling is another technique used in business intelligence, which also relies on data warehousing to collect enough historical data on which models are based.

Collaboration was the word of the day in the past decade, with a growing number of software vendors offering business intelligence systems that feature collaboration capabilities through data sharing tools and other instruments designed to provide collaborative virtual workspace. Even the rapidly gaining popularity of social networking platforms rely on data warehousing technologies; and a number of software vendors and developers offer business intelligence platforms that run entirely online, software-as-a-service, or SaaS, where business users can benefit from social networking functionality, in addition to traditional functionality characterizing such systems.

Usually, business intelligence systems are highly configurable reflecting the need to deal with different data and regulations across various industries. Data protection is another well-developed feature of most business intelligence systems due to the sensitive nature of business data gathered and managed through data warehousing techniques and systems. Access of third parties to such data can give them marked competitive advantages; thus, software developers pay special attention to data protection and security in the field of business intelligence systems.

Data warehousing is well known for adding value to other systems as well, most notably to customer relationship management (CRM) systems. Another valuable benefit is the ability of such systems to integrate data from multiple sources and across different systems into a single database, allowing data warehousing and business intelligence techniques to be used to give a broader perspective on what is really going on within an enterprise.

Basic Advantages Provided by Enterprise Data Warehousing

Modern-day enterprises have to deal with large amounts of information, often processed in real-time, thus enterprise data warehousing emerged as technology aimed to satisfy the needs of rapidly growing number of business customers. Data warehousing is applied in various business software solutions designed to support and facilitate overall decision-making process, enabling managers to easily retrieve and analyze data. Initially, data warehousing solutions have been regarded as relatively costly technology, affordable only to large corporations, but the maturing of this type of software architecture and the emergence of software outsourcing reduced markedly the cost of implementation of data warehousing solutions.

Low entry and maintenance costs determine a major benefit enterprise data warehousing solutions provide to both small and large corporations. Furthermore, data warehousing can be applied in, and is a required element of, a wide range of software applications designed to support financial forecasting, call record analysis, trend analysis, logistics and inventory management, etc.

The three-layer software architecture of a data warehouse and its ability to maintain a copy of information obtained from the source transaction systems used within a broader software solution enables the software to integrate data from multiple source systems. This functionality is extremely advantageous for fast developing businesses witnessing noticeably growing flow of information from various data sources that cannot by easily processed by average customer relationship management (CRM) systems. Thus, a single common data model is introduced and utilized, which provides obvious competitive advantages to business customers.

In fact, contemporary business analytics can hardly cope with the increasing information flow without the help of data warehousing solutions, which also provide data warehouse encryption required by an overwhelming majority of large business customers. Furthermore, business data should be restructured in a way that makes sense to business users, while spreadsheet solutions are not able to deal with the complexity of the task in the framework of medium-sized and large businesses.

An enterprise can do well without deploying data warehousing solutions and still enjoy sustainable business development if the long-term corporate strategy does not envisage expansion to large and crowded markets and rapid growth of customer/supplier relationships. Actually, this is true for most small-sized enterprises that can run their day-to-day business with the help of common CRM solutions.

On the other hand, medium-sized and large businesses cannot cope with increasing pressure from competitors without deployment of some type of enterprise data warehousing solution to improve the overall data management and analytical capabilities of their respective business management software. Integrated data warehousing systems are therefore becoming widespread within a variety of industries, ranging from retailers, to manufacturers, to financial institutions.

Only a limited number of large corporations were able to afford an expensive business software solution incorporating data warehousing technology during the late 1980s and early 1990s; but two decades later the IT industry has also matured and software vendors from Asia/Pacific region and Central and Eastern Europe provide cheaper alternatives to solutions offered by Western software developers. Application development outsourcing and the emergence of software-as-a-service (SaaS) and infrastructure-as-a-service (IaaS) offer opportunities to businesses to further lower costs of enterprise data warehousing and obtain both ready-to-use and tailored hardware and software solutions in a very competitive market.

Benefits Offered by Deployment of Software for Business Intelligence Data Warehousing

Enterprise data warehousing (DW) is applied in virtually every corporation, with enterprises usually taking advantage of specialized applications to perform business intelligence data warehousing, whereas data warehouses solutions are made of servers, storage space, operating system, and specialized software. Software vendors also provide ready-to-use solutions that can be installed and run on a predefined set of hardware configurations, thus allowing enterprises to apply data warehousing in business intelligence without vast investment in new hardware and software. In addition, some software vendors have developed products that combine or run on various hardware platforms. For example, business intelligence data warehousing in Oracle systems enables managers and business owners to select from a variety of hardware platforms on which the software is able to run.

In fact, data warehousing is a process and procedure that allow managers and corporate executives to get easy access to valuable data and analyze these data for the purpose of market research or analysis of various market processes and trends. Business intelligence tools are an integral part of decent systems for data warehousing, which is often referred to as storing of data, with growing number of experts acknowledging that tools to extract data, and manage and get metadata should also be considered part of data warehousing business intelligence.

Enterprise data warehousing can be applied to support businesses in various elements of their day-to-day activities. Data warehouse applications can be applied successfully in decision support, financial forecasting, trend analysis, financial fraud analysis, etc. In fact, customized data warehousing solutions can be implemented by companies involved in any business, assisting managers in decision making process while storing valuable data for further analysis.

On the other hand, initial entry costs of data warehouse vary from $10,000 to $150,000 per terabyte; therefore, data warehousing is aimed mostly at medium-sized and large businesses that need their business intelligence tools to run smoothly, taking advantage of large volumes of data collected for analysis. Overall, implementation of data warehousing systems offers marked reduction in costs, securing low entry and maintenance costs.

Data warehousing is used in business intelligence applications partly because the performance offered by such solutions is usually better than the performance provided by other products for data storing, data retrieving, and analysis of data. Modern data warehouse platforms are able to secure high-performance using advanced analytics methods that were previously known for their low performance due to software and hardware issues that software developers and vendors were not able to solve in the past.

Scalability is another factor that plays an essential role in cost reduction with many software vendors offering data warehousing systems made of modules, which helps businesses in lowering upfront costs related to over-provisioning. In addition, scalability allows database administrators and IT managers to deploy solutions in line with company needs and requirements, following an analysis of business process and procedures within their respective enterprise.

In general, data warehousing applications provide visible results and cost reductions within months after implementation. Recently, software vendors started to provide solutions that are designed with business intelligence data warehousing in mind, thus enabling corporations to utilize such software products as strategic tools in running their day-to-day business activities.