Trends and Outliers
TIBCO Spotfire's Business Intelligence Blog
Category Archives: Advanced Analytics
2013
Spotfire 5.5 Release Addresses Growing Market Trends
Companies that want to be competitive, productive as well as innovative have to get the right information to the right people in real time. But at the same time, they have to control access to their sensitive business data.
With the Spotfire 5.5 enterprise-class data discovery platform companies can secure their corporate assets, and provide instant self-service analytics to support the competitive, agile organization.
In our upcoming blog posts, we’ll delve into the major issues companies are facing accessing data – especially unstructured data – from different data sources.
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2013
Making Better Decisions with Big Data
Big data may be all the rage. But if the quality and integrity of the data that’s collected and used from structured and unstructured data sources is suspect, then business leaders won’t be properly armed with the insights they need to make well-informed decisions.
When business leaders can access company performance data faster, react more nimbly to business events, and be more accurate in their decision making than their competitors, “then your company can begin to distinguish itself in the marketplace,” notes Aberdeen Group researcher Nathaniel Rowe in a recent report about gaining accurate information from big data.
According to Aberdeen’s survey of 125 organizations, 56% of best-in-class organizations, or the top 20% of aggregate performance scorers, report they’re using faster, more complex analytics to gain a competitive advantage over their peers.
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2013
5 Areas Where Predictive Analytics Can Help Insurance Firms
The insurance industry’s past success has been due, in part, to its cautious and risk-averse nature. But to succeed in the future, insurance companies have to adopt new technologies like predictive analytics, according to a blog post by Joe McKendrick in Insurance Networking News.
In the post, McKendrick points to a paper written by Deloitte’s Howard Mills that makes a strong business case for advanced or predictive analytics within insurance organizations.
Mills’ opinion is that predictive analytics will help insurance companies better understand future threats and opportunities. And Mills believes that insurance companies will be more successful by embedding analytics into their business processes, McKendrick explains.
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Filed under: Advanced Analytics, Insurance, Predictive Analytics
2013
Why Businesses Without Analytics Are Non-Starters
Thinking back on last week’s Gartner Business Intelligence Summit in Barcelona, I’m struck by how important context is to what we take away from conference presentations.
For example, one of the Gartner keynoters drew the analogy between cars on the road 30 years ago and analytics today.
“Remember how back before the mid-1980s cars wouldn’t always start when you needed them to? Then the auto manufacturers applied technology and innovation to ensure that their products always started up as a matter of course, he said.
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2013
Cool News: Customer Feedback Moves TIBCO Spotfire to Gartner BI MQ for 2013
What moved Spotfire to a Leaders position in the 2013 Business Intelligence and Analytics Magic Quadrant from Gartner, Inc.?
While you’ll need to review the entire report to see all the details, we can share a few highlights and insights as to why Spotfire customer feedback helped move the product into the Business Intelligence Magic Quadrant Leaders category.
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First, it’s important to know how the survey works. Gartner defines vendors in the Business Intelligence and Analytics Magic Quadrant as having “a software platform that delivers 15 capabilities across three categories: integration, delivery and analysis.”
2013
Sharpening Media Advertising Through Advanced Analytics
As television, Internet, and other forms of media continue to converge, advertisers and media executives are striving to find the most effective ways to reach desired customer segments with the right messaging at the right time to generate optimal conversion rates.
Thanks to the capabilities and strengths of advanced analytics, media minds no longer have to rely on mass marketing and advertising approaches in the hopes of potentially engaging and converting just a fraction of the intended target audience.
Customer data, including information that customers share in online surveys, contact center interactions, transactions, and social media channels, can be mined by media marketers to identify the customers they’re trying to reach and the type of messaging that’s most likely to resonate with them and lead to conversion.
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Filed under: Advanced Analytics, Data Analytics, Marketing, Vertical Markets
2012
Harnessing the Power of Data Analysis, Intelligent Sensors for Predictive Maintenance
The expanding use of intelligent sensors and data analysis by companies and government entities is helping leaders predict when equipment needs maintenance before it actually breaks down.
Oil platforms, telecommunication network infrastructure, rail systems and even vending machines are producing a wealth of data that can be analyzed to enhance risk management or maintenance processes for virtually any type of equipment, Ronny Seehuus notes in a recent article for Capgemini.
Seehuus points out that intelligent sensors that are used to measure the physical condition of equipment – temperature, humidity, etc. – can help manufacturers and companies in other industries detect trends and patterns to predict a failure or breakdown of a mechanical part before it actually happens.
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Filed under: Advanced Analytics, Data Analytics, Energy, Predictive Analytics
2012
Understanding How Customers View Your Company with Data Discovery
Data discovery is enabling companies to capture a 360-degree view of their customers by compiling and assessing customer behavioral, transactional, and sentiment data across the many channels customers use to interact with companies.
However, this data doesn’t necessarily reveal how customers perceive your company. Fortunately, there are ways to use data discovery to help decision makers walk in the customers’ shoes, as the saying goes.
Before executives use data discovery to understand the customer’s perception of a company, a great starting point is by actually being a customer of your company.
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Filed under: Advanced Analytics, CRM analytics, Data Analytics, Data Discovery
2012
Arming Employees with Data Analysis
A new study from The Economist Intelligence Unit reveals that most business executives (77%) want to give their employees greater access to big data and data analysis capabilities in order to help them make more informed decisions.
Moreover, 63% of executives say they believe that if big data and data analysis capabilities are expanded to more employees, the most important outcome would be better decisions made faster.
We’d like to think that at least a subset of the executives in the study recognize the value of leveraging big data and data discovery techniques from their own experiences with dashboards and other tools.
We’d also like to think that they acknowledge that employees’ uses of this information and capabilities can help drive more efficient and effective decision making throughout all corners of the organization.
There are several benefits to providing employees of varying levels and responsibilities with access to the big data and data analysis tools they need to make informed decisions. First and foremost, they and the company will be more productive.
Organizations that adopt “data-driven decision making” achieve productivity gains that are 5% to 6% higher than other factors can explain, according to an article in Mobiledia that cites a study of 179 large companies done by several MIT professors. The Mobiledia article points out another critical trend that should provide incentive for more senior executives to empower employees with big data and data analysis capabilities – the shortage of skilled workers.
US companies and government agencies will need 140,000 to 190,000 new workers with “deep analytical expertise” and 1.5 million more “data literate managers,” according to the McKinsey Global Institute. University and college graduates will help fill part of this demand but there are only a finite number of data scientists currently in and coming into the market. And that means more companies will seek to fill the void by arming more of their own employees with data discovery and data analysis capabilities.
Big data and data analysis not only help employees make better decisions, but they help employees be more productive. In fact, federal agencies are increasingly using data analysis to identify opportunities for improving employee performance and productivity, notes Tom Fox of the Partnership for Public Service in a recent blog post.
For instance, Fox says the Transportation Security Administration is using these techniques to assess the performances of airport screeners conducting security activities, then using the information they glean to identify training opportunities for employees.
Next Steps:
- Subscribe to our blog to stay up to date on the latest insights and trends in data analysis and big data.
- To hear how organizations that have adopted in-memory computing can analyze larger amounts of data in less time – and much faster – than their competitors, watch our on-demand webcast, “In-Memory Computing: Lifting the Burden of Big Data,” presented by Nathaniel Rowe, Research Analyst, Aberdeen Group and Michael O’Connell, PhD, Sr. Director, Analytics, TIBCO Spotfire.
- Download a copy of the Aberdeen In-Memory Big Data whitepaper here.
Filed under: Advanced Analytics, Big Data, Data Analytics, Data Discovery
2012
Data Analysis: Explore New Territory (Part 2)
We’ve already discussed the dangers big data can create by luring organizations into complacency – organizations that only experiment with data that’s close at hand instead of venturing into the unknown and exploring new territory.
But the immense promise of using data analysis to uncover the secrets of big data is best suited to the types of companies that lean toward innovation, an area that can be challenging for companies struggling just to survive in the rocky economy and – as Harvard Business Review notes – the largest companies.
Large companies tend to just create operational efficiencies instead of experimenting with innovative new products, services or approaches. This is a result of the natural business life cycle, HBR notes.
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Filed under: Advanced Analytics, Big Data, Big Data Analytics
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