Business Intelligence: Why is¨it important

Business intelligence (BI) simplifies information discovery and analysis, making it possible for decision-makers at all levels of an organization to more easily access, understand, analyze, collaborate, and act on information, anytime and anywhere. This definition for BI demonstrates that traditional analyst-driven BI applications have evolved to include multiple initiatives to measure, manage, and improve on the performance of individuals, processes, teams, and business units
Business intelligence is achieved with the following actions and corresponding tools.
Provide quality data: Business intelligence is built on the scalable and reliable SQL Server platform with a powerful relational database management system, SQL Server Integration Services, SQL Server Analysis Services, SQL Server Reporting Services, and SQL Server data mining capabilities.
Gain deeper insight and facilitate better decision making: Reporting and analysis are the capabilities that allow you to gain deeper insight from your data. To learn more about reporting and analysis,
Align decisions with corporate goals: PerformancePoint Server is a powerful performance management application that provides the infrastructure to link executives, line-of-business managers, or individual contributors to the overall corporate strategy.


Business intelligence, as defined in What is business intelligence?, provides a broader view that covers the data warehouse, tools, and applications that show data from various sources like the data warehouse. This article and the following diagram introduce Microsoft Office PerformancePoint Server 2007 as it relates to the data warehouse.

What is a data warehouse? A data warehouse is a repository for storing and analyzing numerical information. Core data in the data warehouse are typically numeric values that can be summarized or aggregated. One reason a database structure differs from a transactional database structure is that pulling data can otherwise prove to be very resource expensive. Data warehouses allow you to store aggregated data rather than performing ad-hoc queries to sum. This simplified definition is explained further in many books written specifically for data warehouse professionals.

What is OLAP and how does it relate to a data warehouse? Online Analytical Processing, or OLAP, usually describes specialized tools that make warehouse data easily accessible. An OLAP cube is a logical structure that defines the metadata. It is a borrowed term to describe existing measure groups and dimension tables. A cube is a combination of all existing measure groups. A measure group is another logical structure that defines metadata so that client tools can access the data. It is the group of measures that share the same grain. Each measure group contains the detail values stored in the fact table (copied or dynamically retrieved values). OLAP cubes contain lots of metadata; metadata in its simplest definition is data about data. Multidimensional expressions or MDX is a metadata-based query language that helps you query OLAP cubes.

What is SQL Server Analysis Services (SSAS) and how does it relate to OLAP? SQL Server Analysis Services, once called OLAP Services, provides server technologies that help speed up query and reporting processing. Analysis Services implements OLAP with technologies that simplify and quicken the process of designing, creating, maintaining, and querying aggregate tables while avoiding data explosion issues.

How does PerformancePoint Server relate to data warehouses, OLAP, or SSAS? SQL Server Analysis Services data supplies the client tools in PerformancePoint Server with data that feeds into the larger business intelligence (BI) suite provided by Microsoft.

  Business intelligence is all about getting insight out of data, but what happens when that data is inconsistent across the enterprise?

A myriad of business intelligence tools exist on the market today, and the truth is most hospitality organizations have a mixture of these within their enterprise. For example, marketing is probably running ePhiphany; finance has Hyperion; and other departments are utilizing Cognos or Business Objects. As a matter of fact, most companies I talk to are running between six and 10 different business intelligence applications.  No wonder it’s a common occurrence to be in a meeting and have two very different takes on the very same information. Are all these front-end analysis tools just hiding the real problem? In hospitality, we’re certainly not lacking data. Quite the contrary: we’re struggling with too much of it. Whether it’s coming from the PMS, onsite POS, Web applications or one of many proprietary line-of-business applications, we’re flooded with information. The problem is consistency across databases and establishing one point of truth for any particular data set. No matter the size, hospitality organizations are drowning in the complexity of BI and this ultimately increases the cost of business. The root of this problem is simple. Application developers continue to develop applications based on their own databases because of a perceived need to trust the data at the point of development. In fact, it’s quite common to develop an application first and then think about the data model. Yet, as systems grow and new applications launch, the amount of duplicated data grows exponentially. And for those advanced organizations that have a data architect and instill an enterprise data model, there is still a major problem of rewriting applications to connect to the system of record for verifying information such as site ID or location or many other duplicated records. But what about the data warehouse? Wasn’t that the solution for data management? One would expect so, but as hospitality organizations grew and, in many cases, acquired other companies, the data warehouse itself exacerbated the problem, rather than solving it. I see this myself – and you probably do too –  in the many identities I bear when traveling . Even among sister or partner hotels, I’m listed as Sandra Andrews, Sandy Andrews, S.M. Andrews and many other permutations. It’s easy to experience the complexity of the hundreds of systems each hospitality organization runs, whether franchised or managed, across chains and partner networks. It’s no wonder BI vendors are so hot on the hospitality market. Of course, BI has been around for more than 10 years, and IDC reports it to be a more than $13 billion market, forecasted to grow more than 8 percent annually for the next three to five years. Hospitality executive surveys have shown the tremendous return of BI and that it remains a top spending priority for many companies. At Microsoft, we worked with IHL Consulting to analyze the top IT spending trends in the industry. Across North America, Europe and Asia, hospitality firms spend $420 million on line-of-business business intelligence, breaking down into several specific areas: $159.12 million–data warehouse implementation suites $63.57 million–customer relationship management $57.01 million–data warehouse design and administration tools $43.44 million–analytical applications $25.64 million–data mining tools $20.57 million–inventory optimization $18.88 million–executive scorecard $14.31 million–database administration and management $18.44 million–other Given the high IT spend in business intelligence, the next thing to determine is the total cost of data. Whether this is defined as the costs of acquiring and operating data storage or the amount spent for tracking, managing and storing one parameter in one database. The explosive growth of data in the industry escalates this cost dramatically. As for business intelligence, I think we need to divide it into traditional BI and next-generation BI.  Traditional BI offers simple analysis and reports on what hopefully is a single version of the truth. And, unfortunately, most BI vendors get to that single version by implementing their own applications, with their own databases, pulling from what they believe to be the systems of record. Next generation business intelligence, however, involves gaining business insight from data and turning that insight into action. It means optimizing and predicting the business, giving users desktop and mobile dashboards with real-time information alerts to help enhance the guest experience, make better decisions and ultimately impact business performance. It’s powerful stuff. So, in order to get the true benefits of business intelligence, the hospitality industry needs to focus on data management first. For example, Harrah’s has been upheld as a leader in business intelligence, but ultimately I believe the company is superior at identity and data management. Understanding that the horse comes before the cart, in this case, has led to Harrah’s success. How does the industry accomplish this data management task, especially with the increasing complexity and sheer volume of data? The good news is there are experts out there. The role of the data architect is less than five years old, and it’s becoming a crucial role in the success of hospitality enterprises. The other good news is that the market is evolving and the next generation of BI targets every user in your organization, empowering line-of-business executives to make real-time decisions based on accurate data and enabling staff to have the right insight to personalize and enhance a guest’s experience.  With this in mind–and as long as the right steps are taken to manage data before BI is employed–I believe hospitality organizations are poised to succeed. Sandra Andrews is the hospitality industry solutions director for Microsoft. To learn more about Microsoft’s hospitality initiatives and business intelligence platform visit http://www.microsoft.com/hospitality or contact Sandra directly at sandraa@microsoft.com.