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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

Monthly Archives: February 2011

02/28
2011

The ABCs of Enterprise Analytics

Enterprise Analytics The ABCs of Enterprise AnalyticsA:  What is it?

“Enterprise analytics” is a widely used term these days.  As often happens, though—it’s being used in different ways, by different groups, for different reasons.  Enterprise analytics can refer to any or all of these three concepts:

1. Access to analytics capability (so users throughout the enterprise can perform their own local analytics)
2. Access to enterprise-level analytics (so some users can see reports or dashboards that incorporate data from the whole enterprise)
3. Analytics platforms that can function at an enterprise level  (working with multiple data sources and formats)

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02/25
2011

Six Characteristics of Best-In-Class Business Intelligence

Best In Class Business Intelligence 214x300 Six Characteristics of Best In Class Business IntelligenceMetrics are at the core of business intelligence. They are arguably the most important aspect of a business intelligent project and probably the most difficult as well. A recent whitepaper from Booz & Co. observes that most companies have not put enough thought and rigor into establishing the metrics used to measure itself, sometimes measuring thousands of key performance indicators rather than a few metrics that really make a difference.

Establishing the right metrics requires a deep understanding of where a company is today and where it wants to be in the future and should be customized to fit the organization’s strategy and goals. From expert interviews, research and analysis, Booz & Co. established the following six criteria to use when selecting metrics and performance measurement criteria and implementing them in a business intelligence solution to ensure a best-in-class business intelligence implementation.

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Filed under: Enterprise

02/24
2011

How Data Analytics Helps Sports Teams Win

Basketball Team 150x150 How Data Analytics Helps Sports Teams WinFor sports teams, analyzing and visualizing data — on-field and in the stands — is still an emerging discipline.  In the past year, we’ve highlighted a few examples from leading-edge practices at the Boston Red Sox, a pioneer in analyzing video, and various teams using data analytics and predictive tools to plan ticket pricing .  Just before the NBA All-Star Game, one analyst found that the 18 teams that employ analytics departments are winning more games than those without — as much as 7 percent more.

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02/23
2011

What Data Visualization Reveals About Your Own LinkedIn Network

My LinkedIn profile says I have 305 connections. I have a sense of where they have all come from – former employers, clients and colleagues, classmates – but, without data visualization, it’s hard for me to get a sense of what my network looks like, who my key connections are and what kind of crossover or links there might be between the different groups that make up my network. What’s the solution?  Visualize your LinkedIn network with LinkedIn Lab’s InMaps.

As I expected, my LinkedIn network reveals that I have several clusters of connections which are color coded.  Towards the bottom of the screen is a color key where you can label the different groups of connections in your network. The larger circles within a group show the people who are most connected within that cluster, and you can hover your cursor over a circle to view each individual plotted in the network.

According to this LinkedIn blog post, there are several ways you can use this information. The visualization allows you to better identify where you might be able to pass along job opportunities or get advice from your colleagues. It also helps you to identify opportunities to connect other people, either within a cluster or between your clusters.

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Filed under: Data Visualization

02/22
2011

Data Mining Improved Company’s Revenue By 187%

Call Center 150x150 Data Mining Improved Companys Revenue By 187%Assurant Solutions sells insurance policies on credit card payments, for example if you lose your job or become disabled. Their customer service center takes calls from people who see the monthly add-on fee on their bill and call to cancel.  Metrics are simple. If a customer does not cancel, the customer is “saved.” If a customer is saved by downselling or upselling to a different plan, a percentage of revenue is saved.  Assurant’s objective was to increase the percentage of saved customers and to increase the percentage of saved revenue. To do this, they agreed to abandon their assumptions about how the customer service center should operate in favor of what data mining revealed. MIT Sloan Management Review published this article detailing their astounding results.

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Filed under: Data Mining

02/18
2011

Watson Won Jeopardy, But Humans Still Key to Business Intelligence

Jeopardy Watson Humans and Business Intelligence Watson Won Jeopardy, But Humans Still Key to Business IntelligenceIs artificial intelligence enough to win Jeopardy? It was elementary for Watson, IBM’s super computer designed to take on former champions, Ken Jennings and Brad Rutter, this week. He won by a lot – more than $50,000 separated him from the humans.

With his four terabyte library and ability to complete multiple processes at once, Watson’s data analytics and technology were impressive. However, the computational research lacked a human element, which we feel is the key to data analytics.

As Casey Johnston reported in ARS Technica on Tuesday, Watson lacked an understanding of the nuances in the human language and the ability to hear what is happening around him. He has to be fed the information in text form, which he processes at the same time as the other contestants. He is not hooked to the Internet, so running the answer through his databases is very similar to that of the human response.

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02/17
2011

Resilience and Agility – Brought to You By Analytics

spotfire Resilience and Agility   Brought to You By AnalyticsChoosing between ‘performance management’ and ‘process management’ using analytics data and business intelligence tools is like deciding on a favorite child. You need BOTH, according to Joseph Raynus, who advises organizations on how to measure and manage the always shifting streams of data.  Raynus shared some ideas on creating agility at a Boston meeting of the Association of Business Performance Management Professionals, ABPMP.  The group is part of a national organization for IT and operations professionals exploring both the process and design/measurement of each step in a company or organization culture.

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02/16
2011

Social Network Analysis Can Reveal Secrets About Your Customers

social network Social Network Analysis Can Reveal Secrets About Your CustomersThere is an old saying that a man is known by the company he keeps. Today, the company men and women keep is much easier known – or at least pieced together through online activity. It’s called a social network and, just as the adage states, your social network is a reflection on you. In 2010, Gartner designated social network analysis technology as the second most strategic technology warranting significant investment by businesses. According to this article in The Economist, whether you know it or not, social network analysis technology is being used everywhere, and that trend will only continue as it reveals deeper insight into everything from consumer to terrorist behavior.

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02/15
2011

The ABCs of Desktop Data Mining

desktop computer 150x150 The ABCs of Desktop Data MiningWhat is it?

“Data mining” can be described as the process of finding patterns and relationships in data.  There are several different flavors of data mining, using different methods and pursuing different results.  For example, a data mining project might look for:

  • associations (interconnected events or information items)
  • sequential relationships (one event leading to another)
  • affinities (events that occur in clusters, information items that are frequently found together)

There are also two levels of approach to data mining.  “True” data mining is an IT-intensive process, using complex algorithms and very sophisticated procedures to discover deep and/or unexpected patterns in data.  At the business level, however, data mining is often viewed more generally, as a way of exploring data to answer questions and support analysis.

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02/14
2011

Data Visualization Weeds Out Social Pollution on Twitter

truthy1 300x211 Data Visualization Weeds Out Social Pollution on TwitterIn our #followfriday series, we look at how social BI and data analytics professionals used Twitter during the previous month. Twitter has become a source to get a pulse on the latest ideas and topics of most interest to the community at large. We create hashtags to represent ideas and tweet and retweet these ideas to raise awareness and create a discussion.  Unfortunately, some of the buzz on Twitter isn’t real – it’s fabricated. But a group at Indiana University is using data visualization of social network connections to identify and weed out the fabricated “social pollution.”

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