Here’s what’s hot in advanced analytics for 2012.

Advanced Analytics is All the Rage

According to the “2012 Business Intelligence, Analytics and Information Management Survey” from InformationWeek Reports, we learned that “interest in analytics in general and advanced statistical and predictive analytics in particular rose for the third year in a row.”

A few insights from the report:

• 58% of those surveyed are “very interested” in advanced analytics
• Advanced analytics is the No. 1 leading-edge technology
• Cloud analytics systems are hot because they are easier on the pocketbook; yet 63% of users have privacy concerns
• Data pros just can’t get good data – data quality still ranks as the top barrier to adopting BI products throughout the company
• 25% of those surveyed are mobilizing their data analytics with dashboards and data visualizations
• 40% of data pros are struggling to stay above the big data wave

Want more trends on advanced analytics? Follow the report’s editor Doug Henschen (@dhenschen) for more on this topic.

The “What” is Unique to Advanced Analytics

James Taylor (@jamet123), CEO of Decision Management Solutions and an expert on advanced analytics, recently wrote in an Information Management column that “advanced analytics are valuable for one reason and one reason only – because they allow you to improve the quality of decision making in your organization.” He says that advanced analytics help you improve decision making best at the operational level – especially when you’re making “decisions about a single question or transaction.”

But the hurdle is that most organizations can’t pinpoint “what these decisions are.” It’s that same old story of untold territory –  businesses have never been there and done that so they don’t have a starting point. Yet, Taylor writes “to be successful with predictive analytics the gathering of requirements in terms of these decisions is critical.” Read more on how to do this in your organization.

Advanced Analytics Takes Madison Avenue

According to Dave Morgan’s column at AdAge.com, “Moneyball” resonated with more than just data geeks. The men and women of Madison Avenue are finding the value of analytics to help them answer the age-old advertising problem – Who are we reaching with the $70 billion we spend on TV ads each year in the U.S.?

CEO and founder of New York-based Simulmedia Morgan (@davemorgannyc) predicts that analytics will give us a better understanding of where the frequency is wasted, where to find new audiences and metrics similar to those we experience in Web-based advertising.

Could this be the sexiest data geek job of all time? Morgan’s picture of the new Sterling Cooper Draper Pryce partner as “a digital-savvy math-driven quant” is more data scientist in stilettos than the three-piece-suited Don Draper we’re used to seeing on “Mad Men.” The said “quant” will rely on “Wall Street-like data analysis to spot low-hanging fruit in the gut-driven world of buying and selling spots and will change the rules of the TV ad game.”

Next steps: Join us for a webinar with Forrester Senior Analyst James Kobielus (@jameskobielus) and Spotfire Product Marketing Manager Syed Mahmood, this morning at 11 a.m. EST as we explore how leading-edge organizations everywhere are integrating advanced analytics into multichannel CRM to drive marketing campaigns, prospect for new customers, retain and grow customer relationships, create consistent cross-channel experiences and achieve operational efficiencies.

Amanda Brandon
Spotfire Blogging Team

Most Popular Discussions for January, 2012

2012 got off to a good start in the Videoconferencing Professionals LinkedIn group with the announcement that the 10,000th member had joined mid-way through January. This indicates just how vital the group has become in the video conferencing and telecommunications industry, and it also illustrates the depth of knowledge that is represented by its members.

David Danto, Director of Emerging Technologies at IMCCA (@NJDavidD), posted a link to a controversial New York Times article describing security issues surrounding poorly-implemented video conferencing installations. The article, which has also been discussed on the KBZ Communications blog, generated a number of responses from group members who, for the most part, expressed the hope that readers would understand that the issue had to do with the lack of security precautions taken by IT managers and not any flaws inherent in the technology itself.

Most of the other activity over the course of January focused on specific questions about video conferencing, such as the query posed by Darren Aspinall (sector manager AV/VC at Colebrook Bosson Saunders, @darrenaspinall), regarding the best way to implement a cloud video conferencing system for 25 users dispersed around the world. Pete Woodworth, network analyst at Cal Poly State University, also asked for recommendations for a worthy upgrade over a retail-level high-definition web camera, which garnered a long list of suggestions from group members, ranging from Logitech to Canon units. Moving past the tech perspective, Thomas Aquilone, programs manager at Lockheed Martin (@taquilone), got people talking about how to connect Tandberg and Radvision video conferencing endpoints to Android tablets.

Top Influencer for January, 2012

January’s top influencer title sees a two-way tie between David Danto and Thomas Aquilone. Danto’s post about video conferencing security issues led to some interesting responses from a number of industry leaders, while Aquilone was able to stimulate an impressive list of suggestions to his question about Android video conferencing connectivity.

Benjamin Hunting
KBZ Communications Blogging Team

And CRM vendors will have to offer analytics through mobile devices so companies can have instant access to various kinds of analytics that were pretty much limited to being on computers in their offices.

To improve customer satisfaction, productivity, and financial performance, sales teams want to be able to transfer information via their mobile phones wherever they are—they don’t want to have to find Wi-Fi hotspots in public locations to access their companies’ CRM systems, according to the Selling Point article.

Companies will also use more analytics tools to get the most out of their CRM systems. These tools can predict the monetary value of various customers by using their purchase histories to predict their future purchases as well as determine cross-selling opportunities. These analytics tools, delivered via mobile devices, will allow sales teams to more rapidly analyze what’s happening within their businesses, and that will enable managers to make more informed decisions in real time.

Moving forward, CRM vendors and practitioners will have to pay close attention to social computing, mobile and customer analytics.

“We have facing us, social, mobile, an explosion of channels and an explosion of data,” says Gene Alvarez, (@galvar60) research vice president for Stamford, Conn.-based research firm Gartner Inc.

Alvarez says consumers have more technology than businesses have—something that has to change if they want to remain competitive. Gartner says that through 2015, analytics applications will remain one of the fastest-growing categories for business apps. And the research firm also predicts that by 2015, 80% of businesses will lose money if they don’t support Web-based customer service on mobile devices.

Next Steps

Register now for our Spotfire webinar “Advanced Analytics in Customer Relationship Management” featuring Forrester Advanced Analytics Analyst James Kobielus (@jameskobielus).

Linda Rosencrance
Spotfire Blogging Team

As such, it’s critical for companies to be able to follow the thread of a customer’s interactions from one channel to the next (e.g. product research on a company’s web site, followed by a call to the company’s contact center). When customers have inconsistent experiences across the different channels they use, this can lead to frustration, dissatisfaction, and desertion.

Leading organizations are integrating advanced analytics into multichannel CRM to identify and target high-value prospects, deliver relevant marketing campaigns to customers, and optimize the customer experience to tighten customer relationships and build loyalty.

Unfortunately, too many other companies struggle to achieve this as customer data is often siloed between different functions and channels, thus preventing decision makers from gaining a 360-degree view of their customers. This prevents business leaders from developing a full understanding of their customers’ preferences and needs, as well as the types of channels they prefer to use for different actions and the experiences they’re seeking.

The need for cross-channel integration has to be championed and driven by senior leadership. CEOs and other CXOs must consistently communicate the benefits of pooling together customer insights from multiple channels and other sources, including transactional data and unstructured data from customers’ social comments. This can be accomplished, in part, through pilot projects where customer data is shared and analyzed between channels and by building on successful deployments.

To help convince line managers and other stakeholders the value of sharing customer data across channels, companies can also recast their incentive programs. Instead of applying historical models where employees and managers are rewarded solely for the success of growing customer revenues in their own channels, companies can create rewards programs where multi-channel customer growth is encouraged and rewarded among managers and other stakeholders.

Companies that are able to analyze and act on the full range of insights that customers share through their multichannel experiences position themselves to deliver more relevant and meaningful customer experiences that lead to greater credibility with customers and ultimately tighter, more loyal relationships. Companies that are able to use advanced analytics with CRM data effectively create opportunities to beat their competitors to market with products and services being demanded by their customers.

Next Steps

To learn more about ways in which companies can apply advanced analytics to CRM data, register now for our complimentary webinar at 11am EST on February 2nd with James Kobielus (@jameskobielus), Forrester’s Advanced Analytics Analyst.

How about Meld? Meld describes itself as “a visual diff and merge tool targeted at developers,” and in this author’s opinion, is vastly more intuitive than Git’s built-in diff tool. Meld allows versions of documents to be compared side-by-side, with color-coded highlighting and arrows indicating additions, deletions and modifications.

Because Git and Meld are so great at what they do, let’s integrate them to work together so that when we need to perform a diff operation Meld is launched automatically with the appropriate files.
Keep reading for my how-to guide on Integrating Meld with Git under Linux to learn about pairing up these great tools!

David Hubbell
SPK Software Engineer

For instance, two years after the devastating earthquake in Haiti, a new study shows that Twitter and HealthMap (a project at Children’s Hospital in Boston that creates a worldwide data visualization of disease outbreaks on an interactive map in nine languages) tracked the cholera epidemic, which killed 7,000 people and affected over 500,000, up to two weeks faster than traditional reporting methods.

The research team led by Dr. Rumi Chunara, a research fellow at HealthMap and Harvard Medical School, had a simple goal – to determine if social media analytics could tell us more about epidemic disease faster than traditional reporting.

According to Chunara’s report in the American Journal on Tropical Disease and Hygiene, it seems so. Chunara writes, “During infectious disease outbreaks, data collected through health institutions and official reporting structures may not be available for weeks.”

This means that early assessment of the situation is weakened. So, the researchers sought new sources of data to speed up the analysis of outbreaks. Chunara’s team discovered that “trends in volume of informal sources significantly correlated in time with official case data and was available up to two weeks earlier.”

In a recent interview with Victoria Nicks of Decoded Science, Chunara says there is real promise for the health community thanks to this study. The main benefit is “this data is available in real-time, so it could be used in a program in real time, so that response measures can be focused and timely.”

Our Take

Chunara’s study is just one example of how time matters in making decisions. In this case, understanding the enormity of the outbreak can speed aid and help treatment teams focus their efforts and possibly reduce the enormity of the situation.

This type of analytics falls right in line with what Vivek Ranadivé, TIBCO’s founder and CEO says about the two-second advantage, “A little bit of the right information, just a little bit beforehand – whether it is a couple of seconds, minutes or hours – is more valuable than all of the information in the world six months later . . . this is the two-second advantage.”

Chunara says she hopes this study inspires more research and development around using real-time data in tracking disease. Our hope is that data analytics plays a major role in reducing catastrophe and saving lives. As we saw last month on the Spotfire blog, the consumerization of data is playing a major role in humanitarian relief and we predict that unofficial, real-time data sources will fuel the same outcomes in reducing disease.

Subscribe to our blog to stay informed.

Amanda Brandon
Spotfire Blogging Team

Any company that uses server farms or engineering compute farms needs to manage those machines efficiently and effectively to reduce the total cost of ownership and increase value for money. However managing a compute farm isn’t as simple as managing a simple web server or as straight forward as administrating a domain controller. If the right skills can’t be found in-house then outsourcing server and computer farm management can be the best solution. Using the people with the right skills will save money and boost performance.

Here are five reasons why server farm or engineering compute farm management and administration should be outsourced:

1. Server Farms Vary In Size

Not all server farms are equal. The beauty of server farms is their ability to scale. But as more computing resources are added, the complexity of the server farm increases, this in turn increases the complexity of managing those machines. A small server farm with less than a dozen machines is a very different thing than one with a thousand machines. As the farm size increases so does the complexity of planning for disk failures, hardware failures and backups.

2. Bad Load Balancing Will Kill A Compute Farm’s Efficiency

Depending on the architecture of the compute farm, a degree of load balancing will be employed either at the application level or lower. Bad load balancing will kill the efficiency of a compute farm. In a completely homogeneous farm, where every server is identical, this load balancing can be somewhat easy. But in a heterogeneous farm where servers differ in terms of computing power, memory resources and I/O, getting the load balancing right can be difficult. As farms scale over time they become more diverse with earlier servers generally being less capable than new servers. Correctly balancing the load in such an environment will yield greater performance results.  Properly configured job scheduler applications such as LSF or Oracle Grid Engine efficiently distribute user jobs to available compute resources.  These applications can raise the resource utilization of a farm from 15% (average) to 75% or even 90%.

3. Software Licensing Can Be Costly

Depending on the software used, a server farm can cost a significant amount of money in terms of license fees. Outsourcing the management of licensing can reduce overcharging by ensuring that only the correct number of licenses are bought. In addition, customers don’t have to worry about the legal issues because too few licenses have been purchased. Many software companies offer different volume licensing models including special cases for servers under the day-to-day management and control of an outsourcing company.

4. A Misconfigured Network will Limit Usability

Underlying any engineering compute farm is a complex infrastructure including a network. As a server farm grows so must the available bandwidth. To achieve this, switches need to be configured correctly, network addresses need to be allocated effectively and the network topology needs to remain balanced. Understanding and creating an efficient network will allow the maximum amount of computing resources to be used by the engineering staff.

5. Bad Security Policies Leave Servers Vulnerable

All servers need security auditing and patch management. An unaudited, unpatched machine is a danger to a company but rolling out patches for an entire compute farm can be a difficult task. Similarly security auditing requires professional input from security specialists. Either of these two tasks merit the use of an outsourcing company, more so when both are considered together.

Conclusion

These are just a few of the reasons why using an outsourcing company with experience in managing and administering a server farm can be beneficial, particularly when in-house skills aren’t available. This list is by no means complete, other problems to consider include server monitoring, virtualization deployment and storage management.

But is that the right way to view these two technologies? Is sentiment analysis a component of text analytics or is it an application on its own? And either way, what about the human element?

Recently, analytics visionary Seth Grimes (@sethgrimes) indicated that sentiment analysis draws on, but isn’t a subset of, text analytics. “Strong sentiment analysis relies on semantic analysis — on application of natural-language processing (NLP) techniques to identify sentiment objects (entities, topics, and concepts), opinion holders, and the sentiment, attitudes, and emotions that the opinion holders attach to the sentiment objects. But sentiment can also be inferred without any semantic analysis. For instance, the Consumer Confidence Index (CCI) and the Michigan Consumer Sentiment Index.”

In a post earlier this week, Grimes continued to break down why sentiment analysis doesn’t depend on text analytics.

Grimes says sentiment analysis draws on, but isn’t a subset of, text analytics. Although text analytics can help companies determine how consumers feel by analyzing their words, Grimes says there are many more sentiment sources out there than just text. Not only that, but Grimes says you don’t really even need text analytics to get at sentiment in text.

In Grimes’ view, if sentiment analysis is a text analytics subset, then a smile, yelling, an angry gesture, and dwell-time on a Web page wouldn’t mean anything.

“They express mood, attitude, and emotion that are conveyed visually, audibly, and via movement, but they’re non-textual and thus can’t be parsed directly via text analytics,” Grimes says.

When it comes to social media, companies can use customers’ unstructured feedback to analyze their sentiments and feelings because people don’t control their emotions as much when they interact in social environments. That way businesses can try to understand consumers’ real feelings behind the feedback they leave and use it to achieve their goals.

“Text analytics is great stuff, but it’s not the be-all and end-all of sentiment analysis,” Grimes says.

One of the many comments responding to Grimes’ post was from Cordell Wise (@cordellwise). He says the problem occurs when companies try to capture all these forms of communication as data.

“I agree there will be inevitable loss of fidelity (meaning) but data is rarely perfect,” he says. He speculates that the focus on text analytics stems from the fact that it’s the most prevalent form of communication captured as data at the moment. “Perhaps as we attach emoticons, images and video to the text we’ll get a more complete picture, but we have to start somewhere.”

Beth Schultz (@beth_schultz) says since Grimes’ take is that text is the largest source for harvesting sentiment, it stands to reason, then, that it’s often the starting point for a sentiment analysis program. “Or do we also see sentiment analysis initiatives launching with audio and video sources in mind, as well as images – typically, that is?” she asks.

And Ariella Brown (@AriellaBrown) says she likes to apply concrete examples to principles. So she wants to know if this post on social position with its map of Tweets would constitute sentiment analysis.

Linda Rosencrance
Spotfire Blogging Team

I recently performed some DIACAP Compliance testing using Gold Disk on one of our products, which was built on Windows XP Embedded.  That process is fairly straightforward, even though Gold Disk is somewhat clunky (no search function) but it did work.  When our latest product was built on Windows 7, I quickly discovered that Gold Disk does not support Windows 7.  What’s worse, it is not being updated to work on anything past Vista and it is being retired in favor of something called SCAP-based benchmarking tools.  Without one of these tools, the only way to test a Windows 7 system is to check it manually using a STIG.

STIG stands for Security Technical Implementation Guide.  It is a human-readable checklist that is used to verify and document compliance with DISA standards.  The current STIGs and the SCAP benchmarks can be downloaded here: http://iase.disa.mil/stigs/index.html.  At the time of this posting, there is a scrollable box that will contain both the human-readable STIG manual checklist (Windows 7 STIG – Version 1, Release 6 – Updated October 31, 2011) as well as SCAP Benchmark files.

SCAP stands for Security Content Automation Protocol, and is sort of like a successor to Gold Disk, except that DISA is not developing its own tool for use in performing compliance scanning.  Instead, DISA releases SCAP benchmarks, which are like parameter files which can be loaded by a list of validated scanners in order to perform the role Gold Disk did.  DISA lists many vendors, but they recommend McCafee HBSS.  My organization tried QualysGuard Policy Compliance and E-Eye Digital Security’s Retina, which are both on the validated scanners list, which can be found here: http://nvd.nist.gov/scapproducts.cfm .

The steps to perform a SCAP scan would be similar for any SCAP scanner.  In broad strokes, there should be some way for the scanner to import the benchmark files, which are a set of XML files downloaded from DISA’s website.  Once the benchmarks are imported, set up a scan and point it at the device you want to test.  All of the SCAP scanners I tested were network-based, which is different from how we used Gold Disk, where it was run locally on the machine we were testing.  This makes scaling much easier, but it creates additional challenges, because the scanner will have to authenticate with the device in order to scan properly.  All the products I tested had good documentation and support that allowed me to set that up.

One final note: SCAP scanners will not work on the Windows Embedded family of devices.  DISA does not publish benchmarks that are compatible with them.  Each benchmark looks for a very specific OS fingerprint, and it will not run if it is not a perfect match.  To make matters worse, most of the scanners rely on services and features that may not exist in a given embedded OS.  This was a huge blow that resulted in me having to test our latest device by hand, and I’d like to save someone the headache of trying.

Josh Tuttle

SPK Systems Integration Specialist