Marketers Finding what to Measure in Big Data

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A major challenge with big data is finding what to measure in the vast sea of unstructured data. In “Data Analysis for Marketers: Measuring what Counts, Telling the Story,” the author discusses this challenge and turning data it into a visual story. It is pointed out that all decisions can’t be based on real-time, infallible data. Similarly, companies cannot always attribute sales revenue to social media outreach efforts. Instead, the author shares this advice:

Thus, companies should focus their data analysis efforts on areas that have more readily available measures that can track performance against strategic objectives.

For instance, businesses should consider these questions:

* Compared to other marketing channels, does the company have good reach across its target audience on social media?

* How does the target audience engage with the company’s content compared to how the audience engages with the content of the company’s competitors?

Aligning the data you need alongside your strategic objectives is a big part of the decision making process, according to the article. For those on a marketing team, the article contains a few helpful guide points to consider in your data analytics efforts.

When it comes to enterprise information management, an understanding of entity extraction can be very important for a successful strategy so the article may be a good read. Look for content intelligence tools that use metadata effectively, like Smartlogic. They offer the Semaphore Classification Server which automatically applies consistent and accurate metadata tags to documents using a taxonomy or other controlled vocabulary unique to a business or industry.

Alice Wilson, May 23, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Nate Silver and his Advice for Successful Analytics Practices

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Nate Silver made headlines with his predictive analytics in the 2012 presidential election. Sharon Machlis shares some of Silver’s advice for successful analytics in the ComputerWorld article, “More Data Isn’t Always Better, says Nate Silver.” Silver says that abundant data can lead to cherry-picking data points that confirm what someone wants to show. The problem is explained:

Abundant data is a notable problem in politics, where many have an interest in the outcome. But it’s also an issue in fields ranging from medicine — where many researchers and journals would rather see studies showing an interesting result than a confirmation of no news — to earthquake prediction.

When it comes to gaining insight from data, Machlis also shares four tips from Silver. For example, Silver says to ‘think probabilisticly’ rather than in terms of absolute. If you are struggling with getting off the ground with data analytics, the article and tips seem to be helpful.

One expert company that understands data analytics is Smartlogic. This company’s mission is to assist with big data initiatives by joining data with content and analyzing that information for the purpose of providing intelligent, valuable information so that reliable methods come into play when making business decisions.

Alice Wilson, May 23, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Big Data is Being Used to Eradicate Diseases

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We’ve talked before about how big data and analytics are transforming healthcare. Mike Wheatley also weighs in on the topic in the SiliconANGLE article, “3 Ways Big Data’s Helping to Eradicate Disease.” Wheatley starts the article by sharing Google CEO Larry Page’s efforts to gather data from people suffering a condition similar to his – a rare kind of vocal chord paralysis. There is limited amount of data on this condition, but his hope is that by crowdsourcing what is available, researchers can treat and possibly prevent it. The author explains this data strategy in healthcare:

In fact, it’s one of the most visible ways in which Big Data is helping us to gain a better understanding of the more bewildering health problems impacting people’s lives today. From relatively benign conditions like the common cold, to more serious problems like dealing with Cholera epidemics and Parkinson’s disease, crowdsourced Big Data is fast becoming one of the most powerful tools to help us eradicate diseases around the world.

Wheatley also discusses how big data, including structured historical data, can be used to predict disease epidemics. The article seems to be a good read for ways data, both structured and unstructured, is transforming healthcare and life sciences.

To add meaning to enterprise information and big data, look to experts at Smartlogic as a third party solution. The Semaphore Content Intelligence Platform is being used in a variety of industries, such as healthcare, governments, research, and media, to improve business outcomes and overcome challenges.

Alice Wilson, May 23, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Graph Processing on the Rise to Visualize Analytics

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Graph-processing applications are all the rage. At least according to Derrick Harris in his GigaOM article, “We’re Witnessing the Rise of the Graph in Big Data.” Harris talks about GraphLab Inc., a popular open source project focused on graph analysis and machine learning.

Graph analysis is among the hottest techniques around for making sense of large datasets, primarily by determining how tightly different data points are related or how similar they are. The term “graph” came into the broader lexicon along with social networks, which built social graphs to assess the relationships among their millions of users, but the technique has much broader uses.

The author says, though, that the bigger question is how big a market there will ultimately be for graph-analysis or any other specific technique. The article is a good example of tools available to combine with proper analytics and big data.

One system that is being used to make major strides in enterprise content management and re-purposing data for real world applications is Smartlogic. The Semaphore Content Intelligence Platform makes entity extraction possible and is currently being used in healthcare, life sciences, and research-intensive organizations to extract valuable insights and solve real world problems.

Alice Wilson, May 22, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Microtargeting and Big Data Analytics in the 2016 Election

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It was made clear how important big data analytics proved in the 2012 United States presidential election. Now, discussion on how it will play out in the 2016 election is already underway. Gurbaksh Chahal comments on the content management strategy in the Wired article, “Election 2016: Marriage of Big Data, Social Data Will Determine the Next President.” According to the Center for Responsive Politics, $6 billion was spent on ads across all media in the 2012 election making it the most expensive in history. That’s big money. The author shares his prediction for 2016:

As our nation ramps up for 2016, the role of big data + social data in influencing election decisions cannot be ignored. Social data drove the 2008 presidential elections and big data drove the 2012 election. In 2016 it will be the marriage of the two that will determine the next President of the United States.

When it comes to 2012′s focus on big data, Chahal says it was all about numbers:

Math quants and data crushers were able to disseminate the mounds of campaign data at their fingertips into actionable targeting information to persuade prospective voters across the nation, and within strategic swing states.

Combining this focus on number crunching with the social media data that is always flowing obviously seems like it can contain valuable and game-changing. The article is an interesting forecast of where politics is heading. These new ways of understanding the public also means marketers and ad-execs will change the art of advertising in the political arena.

Honing in on the right information is challenging for many organizations. To make the process easier, Smartlogic has developed the Semaphore Content Intelligence Platform with entity and subject identification capabilities. Semaphore can read text and extract entities like companies, people, and locations as well as classify content by adding “tags” from several facets or metadata elements.

Alice Wilson, May 22, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Using Big Data and Location Analytics to Find Underperforming Retail Locations

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Retailers are using big data to identify those outlet locations that are unprofitable. Jeff Bertolucci details the strategy in the article, “Big Data Finds ‘Zombie Stores.’” The need for location analytics is explained:

Poor site selection is an ongoing problem for retailers. Rapid expansion was an ambitious, if sometimes misguided, strategy for many retail chains prior to the global recession of 2009. The end result was often “zombie” stores that were either unprofitable or underperforming.

Simon Thompson, director of commercial solutions for Esri, says that there are two types of ‘zombie stores’ – those that are essentially dead because they don’t meet consumer expectations, like many malls in America, and those that are just underperforming because they are in the wrong place. Focusing in on these stores can help retailers understand a location better thus decide to close it or simply change focus.

Getting your business team the right tools to turn company data into smart content that can be used for decision-making is imperative and Smartlogic is a good tool to look at. The Semaphore Content Intelligence Platform saves “untold man-hours and headaches.” With powerful components, like an ontology manager and classification and text mining server, Semaphore provides features to automatically classify business documents regardless of location or format and streamline workflows.

Alice Wilson, May 22, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

The Need for Data Scientists and the Growing Demand

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Those in the industry have commented before on the lack of adequately trained data scientists for the ever increasing skill demand. But James Kobielus says a growing body of shared knowledge and the up and coming generation of self-taught experts will fill in the gaps. His full comments can be read in the InfoWorld.com article, “There’s No Shortage of Data Science Smarts.” The author explains the important need for data scientists:

Data scientists are among the most important developers in the era of big data. They include statistical analysts, data miners, predictive modelers, computational linguists, and other professionals whose job is to find deep insights in large, complex data sets. You can’t unlock the full value of big data in your business if you don’t bring together your best and brightest data scientists and give them the tools they need to do their job with maximum productivity.

He says that worry of data scientist shortage is misplaced for reasons like open source communities and the growing number of data science centers breeds standardization and collaboration. All of this, he says, will help fill in any skills-gaps.

The author also stresses the importance of giving data teams the right tools. One of these helpful tools is Smartlogic. Smartlogic has helped a number of organizations maximize their information assets and develop smart content from their data. From increasing Web site traffic for media organizations to ensuring accurate and legal compliance of customer content in finance industries, the Semaphore Content Intelligence Platform is a flexible option worth a look.

Alice Wilson, May 21, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Manufacturers Turn to Big Data to Improve Factories and Safety

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Marketing is no doubt an area of business looking to big data to learn more about customers and deliver better products and services. But big data also means measuring millions of little things in factories, like how many times each screw is turned. James R. Hagerty expands on this topic in the Wall Street Journal article, “How Many Turns in a Screw? Big Data Knows.” Hagerty shares how one company is using big data to improve manufacturing:

That is what Raytheon Co. is doing at a new missile plant in Huntsville, Ala. If a screw is supposed to be turned 13 times after it is inserted but is instead turned only 12 times, an error message flashes and production of the missile or component halts, says Randy Stevenson, a missile-systems executive at Raytheon. Improvising with a defective screw or the wrong size screw isn’t an option, he says. ‘It’s either right or it’s not right.’

The author says that manufacturers are looking harder at data partly because of pressure from customers to eliminate defects and partly from shareholders aiming to squeeze out more costs. In terms of safety, regulators are also demanding more data collection to trace any safety problems. The author goes on to discuss Harley-Davidson’s use of data collection in its newly renovated motorcycle plant in York, Pennsylvania that is keeping even the tiniest details of production.

If you are in manufacturing and haven’t yet jumped into big data collections and analytics, the article may be a good place to start. You can also start by evaluating tools to help you manage business information. To save development time and resources, boost business intelligence now with a proven solution. Smartlogic offers inter-connected modules with the Semaphore Content Intelligence Platform that turn data into smart content for business decision making.

Alice Wilson, May 21, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

How to Use Big Data to Improve Customer Interactions

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Many companies are looking to big data as an answer to improving customer service. Paul Dunay shares some advice for doing so in his Forbes article, “Six Tips for Turning Big Data into Great Customer Experiences.”

For those online marketers looking to tame big data, Dunay first suggests to think in terms of continuous evolution and iteration – not an instantaneous solution. He also suggests streamlining your internal team and adequately selling the idea. He has this to say about aligning big data goals with individual business goals:

Create separate initiatives or projects for each of your business goals, such as acquiring new customers, boosting conversion rates, improving customer loyalty or increasing lifetime customer value. This approach makes it much easier to determine what type of data to reel in, and exactly how to use it. Focus a team or a project on one objective at a time.

Dunay’s tips may be a good place to start if you are getting a big data initiative off the ground. The author also points out that your own data is best by far. This means that a proper content management solution for your enterprise data is key to unlocking value, like the Semaphore Platform from Smartlogic. With rich metadata tagging capabilities, turning silos of data into connected insight is done automatically. And with the added benefit of semantic technology, a big data team can interact easily with the interface.

Alice Wilson, May 21, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

Improving Agriculture with Big Data Analysis

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While many industries are tapping into the power of big data, agriculture is one with still much room to explore. Prachi Patel explains how ag-experts are looking to data to lift people out of poverty in the article, “Feeding the World with Big Data.” Patel points out that farmers today produce three times as much food as they did 50 years ago using 12 percent more land. However, on a global scale, the playing field is not even:

In Africa, farmers produce a fraction of what they could, according to the Forum for Agricultural Research in Africa, and most barely get by, struggling against infertile soil, drought, and diseases.

James Hendler, a computer science professor at Rensselaer Polytechnic Institute, in Troy, N.Y. who also guides the U.S. government’s Data.gov website, has this to say about the variety of agriculture data:

There are deeply detailed data sets on things like plant genomics and local weather conditions. Then there are broad data sets on such topics as the best crops for certain soils, changes in rainfall levels, signs of pests and diseases, and anticipated prices at local markets.

If data sets relating to agriculture become more available freely, there is lots of possibility and opportunity to improve practices. The article is an interesting highlight of where data is taking us. No matter the industry, business is poised to exploit data for efficiency. One tool to look at is Smartlogic. Whether data is from a customer base or from other inputs, the Semaphore Content Intelligence Platform uses semantic technology and metadata tagging to give businesses a complete overview leading to marketing plans that hit the mark and take the guess work out for improved revenue numbers.s

Alice Wilson, May 20, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search