jueves, 28 de junio de 2007

Data Warehouses and Data Mart

Because data can come from various sources, like OLTP, ERP, CRM, legacy applications, and external data sources, data can be stored in a diversified database, in different formats and structures. As a result, a data warehouse (DW), is the most important and expensive player in the whole BI system because it captures data from these diverse sources, and unifies them. The data is then ready to be accessed by BI system. As a central repository of business, DW contains data used for decision support systems (DSS) which focuses on the lower and middle management and makes it possible to look at and analyze data in different ways. Such data also used for executive information systems (EIS). Data extracted from the DW by departments are collected and put into smaller repository for easy and fast access are called data mart. Like data mart for marketing data, sales, production etc.

martes, 19 de junio de 2007

Five Steps to Business Intelligence Project Success

This is an interesting article that was published in the Technology Evaluation Center site.

Five Steps to Business Intelligence Project Success
Lyndsay Wise

Successful business intelligence (BI) projects encompass more than implementation of a solution on time and within budget. True success should be measured by how the BI solution improves the organization's overall performance through increased efficiency in reporting, planning, financial functions, and performance measurements. This will help ensure organizations' BI projects fall into the estimated 30 percent success rate.

Much has been written about measuring return on investment (ROI) for BI, and the general conclusion is that gaining tangible insight into the initial benefits is not easy. Identifying long-term benefits becomes more practical as planning and analysis, compliancy, and forward-looking approaches become more mainstream within organizations. To gain insight into how to implement a BI solution successfully, organizations should benchmark the success of other organizations, including their implementations and use of BI, against their own current initiatives. It is equally important that organizations learn from other organizations' failures—and avoid repeating them.

This article identifies and explores five steps that organizations should take to avoid the common pitfalls encountered by many businesses when implementing a BI solution. These areas include the identification of the business problem, BI tool use, the delivery of data, training initiatives, and development of a framework toward choosing the proper solution for the organization. These five areas provide an overview of items that should be identified before implementing BI within an organization or business unit.

Step One: Identifying the Business Problem

Identifying the BI business problem is the first step to ensuring a successful project. Once an organization knows what is broken, not only can it start to find ways to fix the problem, but it can also identify the proper resources, create buy-in, and prioritize how to tackle the project. To produce an ROI, a BI solution needs to correspond to an organizational business problem; otherwise, implementing an ad hoc query tool, online analytical process (OLAP) cube, or dashboard will not create lasting benefits.

Unfortunately, it is common for BI solutions to be pushed onto a business unit in order to meet an information technology (IT) objective rather than an organizational need. Sometimes, organizations get caught up with general initiatives and lose sight of the actual benefits BI provides in terms of performance management, collaboration, workflow, process improvement, etc. To attain buy-in, the user community should be a part of the problem identification process. An implementation decision that comes from management still requires input from users as to what their requirements are, and this information can make the difference between the implementation of a tool that works as a value proposition and an implementation that may be seen as useless.

Step Two: Determining Expectations of Use

Once BI is implemented within an organization, its usage usually grows beyond initial expectations. For example, an organization may assume that its BI implementation will involve 10 to 20 users, when in reality, over 400 users query data on a monthly basis. Based on the initial design of the platform, the system may not be built to sustain such a high number of queries, and will most likely "crash" (fail), causing users to lose faith in the new system and potentially revert to their pre-BI environment for stability.

In addition to a lack of confidence, getting an unstable system up and running may not seem worth the effort, delays, or time it would involve. With unrealistic expectations, frustration may cause the organization to rethink its use of BI. Generally, once BI adoption occurs within one part of the organization, other departments or business units see the benefits, and adoption begins to spread throughout the organization. For an organization to meet these needs, the anticipated use of BI should be determined beforehand.

Another consideration is the type of BI tool use. For example, if a sales manager needs to increase sales and wants to analyze trends, product distribution, and sales performance, creating a set of static reports will not produce the appropriate results. A data visualization tool to manage these items and develop a plan based on trend analysis will more likely produce the appropriate results.

Step Three: Understanding Delivery of Data

The collection of the right information for reporting and analysis becomes essential to deliver value to organizations. Although the identification of required data is time consuming, it is the backbone of BI. Additionally, identifying how data will be delivered, what the appropriate data cleansing activities are, and whether data is delivered in batch or in real time should be defined in advance. If data is not cleansed or delivered when needed, then the front-end BI tools will not provide the proper value to the organization. BI solutions impart value through the analysis of data, so it is essential for data to arrive when required, in the proper format, and at the right time. In addition to extract, transform, and load (ETL) tools, data quality and data cleansing need to be inherent aspects of the delivery of BI within the organization. In reality, short of an organization-wide master data management (MDM) initiative, the responsibility of providing accurate data will fall on the shoulders of the business units implementing BI.

Some organizations are misguided and think that their BI solution will provide them with the tools to fix their data problems. BI solutions can provide ongoing data quality processes, but these are not innate to software offerings. Some BI tools include enhanced data quality and integration features, and some vendors assume this responsibility should fall to the organization. Organizations should implement data management structures to minimize frustrations that result from data issues.

Step Four: Rolling Out Training Initiatives

Deciding when to roll out training contributes to project success. Training initiatives should begin right before or during the implementation phase. However, in many organizations, training is rolled out months before actual implementation, creating hype among the employees about the new system and what they will be able to do with it. By the time implementation actually occurs—months later—the initial excitement and buy-in has subsided, and more importantly, users have forgotten their newfound skills. To build momentum again, training needs to be repeated—wasting time and money.

Buy-in related to change is never easily achieved within organizations. Users become attached to their current processes whether or not those processes are productive. Buy-in does not occur immediately upon showing users the inherent value of BI, as their whole way of doing business will change. Creating a training program and delivering that training in a timely fashion helps users apply their newfound skills immediately, and helps to increase user buy-in.

Step Five: Choosing a Vertical- or Horizontal-based Solution

Organizations should identify whether more value will be provided by a vertical solution that is built specifically for the organization's industry or department, or by a horizontal solution that can grow with the organization. For example, does the organization need a generic reporting, querying, and analysis tool that will extend across the organization, or does the organization need to develop a process and compliancy that will adhere to the US Sarbanes-Oxley Act (SOX) or Health Insurance Portability and Accountability Act (HIPAA) standards? The answer will help the organization define which type of solution will best meet its needs.

In addition, the use of BI in the future and its anticipated usage may help determine whether a horizontal or a vertical solution will best meet the organization's needs. Organizations requiring compliance should take advantage of vertical-based solutions because vendors have developed solutions to meet specific compliance requirements. Horizontal solutions need intense customization to bring them up to par, leading to extra time and money spent on developing the solutions.

Organizations in key vertical industries should strongly consider vertical-based solutions that will meet their needs out of the box. Vertical-based solutions are likely to meet the general requirements of a specific industry or department, but since horizontal BI solutions do not base themselves on specified data models, they may be more versatile to the changing demands of the organization. Therefore, if an organization anticipates rapid BI growth across the organization, having the ability to develop solutions based on individual needs may be more beneficial. This relates to identifying the business problem and anticipating the future needs of the organization.


All too often, BI projects fail to meet an organization's expectations. But with research, planning, and a solid methodology, such failure can be avoided. To help ensure BI project success, organizations should work through these five essential steps: identifying their business problems, determining how they will use their BI solutions, knowing how and when data is delivered, rolling out user training initiatives at appropriate times, and developing a framework for selecting the type of solution that will best fit their organizations' needs.

jueves, 14 de junio de 2007

Why BI

BI has a tremendous impact on business once installed. It produces the right information at the right time, which is key element for the success of any business enterprise. BI is the art of knowing and gaining the business advantage from data. Whether it is marketing competition, customer retention, inventory control, financial modeling, or even in national security, BI is the answer. BI can answer a company’s critical questions such as, why market shares are going to competitors; which products contribute the most to profit; how can business become more profitable; why some divisions are not profitable; which plants produce at the lowest cost; how can productivity improve; which parts of the world are the most profitable; who are best and worst customers; where is money being lost or made, etc.

BI answers these questions by analyzing and comparing business historical data. Data is created by business activities or data from outside sources like Excel, customs data bases, competitors information, etc. to study a particular group of people or customers. Such information is used by businesses to understand their business trends, their strengths and weakness, and to analyze competitors and the market situation.

In addition to determining trends, another push to implement BI comes from, the Sarbanes-Oxley legislation, which affects corporate financial reporting, and accounting rules for publicly-held companies. To be in compliance with Sarbanes-Oxley, BI systems will be needed to insure the timely and accurate analysis of business data. Thus real time BI is not only relevant but key to achieving compliance.

lunes, 11 de junio de 2007

BI for Dummies

Due to the idea of the blog is to discuss about Business Intelligence (BI), there is a little explanation maybe from the technology side that the business areas side about what is BI.

We could talk about BI for dummies.

BI is neither a product nor a system. It is an umbrella term that combines architectures, applications, and databases. It enables the real-time, interactive access, analysis, and manipulation of information, which provides the business community with easy access to business data. BI analyzes historical data—the data businesses generate through transactions or by other kinds of business activities—and helps businesses by analyzing the past and present business situations and performances. By giving this valuable insight, BI helps decision makers make more informed decisions and supplies end users with critical business information on their customers or partners, including information on behaviors and trends.

Businesses generate a sea of data. Every datum carries a small piece of the business’ story. This data is scattered everywhere, in disparate systems and in different departments. It is held captive in dead hard drives, and can even be situated in geographically different regions. However, it is in data, where the true nature of business—its trends, strengths, and weaknesses—lie. BI gathers all the related data to turn it into information and information that is analyzed properly can be used for decision making which can finally go into action.

In other words, BI transforms data into information, information into decisions, and decisions into action.

jueves, 7 de junio de 2007

A normal day

Why BI solutions and to have an integrated company could be very valuable for the business areas of a corporation?

Imagine a country like Argentina, at the end of 2001, where from one day to another, reference prices did not exist anymore, where was very difficult for companies to say which was the right price for they products, analyzing different market values

BI solutions help some companies to make decisions in a question of hours about the right price of products depending on the region, transportation, how many stores still open and so on. Decisions that in other way should last weeks, followed by loosing money, market and customers credibility.

Now, imagine a painting products company, who was used to sell 10% more each year but, they didn’t make in account that this year the rainy season was ended one month before than planned, which produce that people begin painting their pools before.

That climate issue broke the seasonality, having a strong impact not only in sales, but also in the production area, due to it produces an important change in the production plans.

In this case, data mining solutions, let companies to work with different scenarios in order to be able to anticipate itself to situations that could happen, doing that as a normal process, following a established plan, allowing the company to save time and earn more money.


How to analyze information for the decision making process, and how to make it in the best way possible. How to generate value for the company and predict the business behavior?

That’s the objective of this blog, to have a space for everybody, from business areas and consulting people to technology people where we can find interesting articles and the right contacts to make successful BI projects that fulfill planned objectives.