Education: Lecturing and New Tech

Another sign that the college lecture might be dying: Harvard University physics professor Eric Mazur is championing the "flipped classroom," a model where information traditionally transferred during lectures is learned on a student's own time, and classroom time is spent discussing and applying knowledge to real-world situations. To make it easy for professors to transition out of lecture mode, Mazur has developedLearning Catalytics, an interactive software that enables them to make the most of student interactions and maximize the retention of knowledge.
 Mazur said, college students don't learn by taking notes during a lecture and then regurgitating information. They need to be able to discuss concepts, apply them to problems and get real-time feedback. 
The program then helps create either multiple choice or "open-ended questions that ask for numerical, algebraic, textual, or graphical responses." Students then respond to these questions using electronic devices they're already bringing to class, like a laptop or smartphone.
Learning Catalytics was so successful in Mazur's physics classroom that it's being rolled out across Harvard, but it's also open to other users on an invitation-only basis. If this tech-based flipped classroom approach takes off, maybe we'll end up with a generation of students that retain what they've learned, long after the final is over. 


Passive lecturing is a mode of teaching used by many instructors at the college level. This style of educating entails students playing a non-active role in the classroom setting as they learn. In passive learning, the professor presents the material through lecture or presentation and the students listen and typically take notes on the information given.

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.