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Posts Tagged ‘big data’

Big Data Skills In Demand for Marketing Professionals

MarketerWithDataBig data is becoming incredibly important for marketers. Marketing Pilgrim recently released the results of a study from the Economist Intelligence Unit, which found that companies want to see big data skills in their marketing professionals.

It’s not about turning marketers into mathematicians, however. The focus is primarily on knowing how to use data once it’s been acquired. It’s also about generating insights and predictions about consumer behaviors and using these insights in a productive way.

According to Information Week, however, few marketers can deliver the goods.

“This change in the required skill set…has created a challenge for marketers as 45% of executives now view marketers’ limited capacity in data analysis as a major obstacle to implementing more effective strategies–second only to inadequate budgets for digital marketing and database management.”

Source – EIU Executive Summary

So what can you do to get your marketing staff ahead of the curve?

The key to solving this issue is, of course, is to arm your marketing staff with effective training that will help them understand how best to use the results of any big data program.

You can teach your marketing staff how to ask the right questions, such as the ones outlined in a recent Forbes article discussing marketers and data.

“This starts with simple questions like: how did our last campaign perform? What keywords drive conversions? What websites did my prospects visit before they came to my sites? Which social conversations are spurring the action that lead to deeper engagement with your brand?

…Matt Auker from McKinsey had similar thoughts when he suggests marketers start their Big Data projects by thinking of the end goal and then working through all the details. This so-called “destination-thinking” will help the strategic marketer avoid the traps of many Big Data marketing projects.”

Ready to get your marketing staff ahead of the big data curve? Send them to our free webinar. Then, consider sending them to any of our big data training courses so they can learn how to put data to work for your business.

More Big Data for Retailers: Weather-Related Shopping Patterns

UmbrellaPrevious posts have mentioned ways that weather can affect shopping patterns. Information Week recently ran a feature which expanded upon this relationship, examining the ways that retailers can use this information to their advantage.

Interaction Marketing used big data to research the patterns so that retailers could use weather forecasts to plan more precisely. For example, retailers could use this information to make smarter scheduling and sales decisions in the face of big weather events like hurricanes and snowstorms.

“Here’s what the data analysis found: a day prior to statistically similar weather events, sales in 28 product categories jumped from 20% to 26% over the same day a year earlier.

Anything with more than 20% or greater increase in sales, over sale-day the previous year, gives us the opportunity to identify those categories and have enough time to communicate with retailers and manufacturers.

This allows business enough time to create promotional campaigns to “educate shoppers…even before the shoppers know they’re going to need those particular items…”

On the flip side, the Interactions study showed a drop in sales over the event’s peak (few of us venture out during a blizzard or hurricane) and for days after. Interestingly, these behaviors took place not only in regions that experienced the weather event, but also in areas where the event was forecast but didn’t occur.”

Choosing the right questions means finding ways to take action. From weather to consumer desires, big data has the power to help your company make great decisions.

It all starts with great training. Take advantage of The Modeling Agency’s free webinar to get a good understanding of how to use big data. Then move on to TMA’s free data analytics training courses to get the advanced training you need to put data to work in your business.

UK Supermarket Chain Uses Big Data to Reduce Energy Costs

TescoThe UK supermarket giant Tesco already uses big data in all of the ways that are standard to the industry. They use loyalty card data and data on the ways that customers interact with the store to drive more sales and create good promotions. Now, however, they’re using big data to tackle a new problem–energy consumption and costs in their stores.

The initiative targets in-store refrigerators and other equipment. Computer Weekly explained the project in a recent article.

“The move will help the retailer cut its refrigeration energy costs by up to 20% across 3000 stores in the UK and Ireland.

…The project, which used sophisticated computer systems to analyze gigabytes of refrigeration data, revealed that, without realizing it, many Tesco stores in Ireland were running their refrigerators at a lower temperature than necessary.

“Ideally, we keep our refrigerators at between -21 degrees Celsius and -23 degrees Celsius, but in reality we found we were keeping them colder. That came as a surprise to us,” said John Walsh, Tesco’s energy and carbon manager for Ireland.

…The data warehouse takes readings every three seconds from in-store sensors, processes the data in real time, and displays the results on a Google map which shows the performance of refrigerators in more than 120 Irish stores. It is also able to monitor and control the performance of Tesco’s heating and lighting systems.”

Whether it’s making changes, cutting costs, detecting fraud or predicting the effects of proposed changes in a store, big data, properly utilized, is a big help to business.

It all starts with getting the proper training on how to make the best possible use of that data. The Modeling Agency offers a free webinar to help business owners get a handle on the possibilities, and TMA’s other predictive analytics training courses can help you refine and strengthen your strategy so that your business enjoys the best possible results for its efforts.

Research Report Reveals How Top Companies Use Big Data

BoardroomThe Silicone Angle blog recently covered some of the insights to be found in an SAS and International Institute for Analytics report called “Big Data in Big Companies.” The report is available as a free download on the SAS website.

Each of the companies that the report covered spoke of using data to make smarter business decisions. Big data, when it’s functioning properly, creates real value for the companies who choose to make use of it.

One case study came from UPS. It’s a good study, one that comes with impressive numbers.

“UPS has more experience with Big Data than most, given that it first began tracking the movements of its vehicles and the packages it delivers back in the early 1980s. The firm reckons it tracks in the region of 16.3 million packages a day, whilst dealing with 39.5 million tracking requests from its customers each day. To date, the company has now accumulated over 16 petabytes of Big Data.

UPS’s ORION (On-Road Integrated Optimization and Navigation) initiative is said to be one of the largest operations research projects in the world. The majority of its data comes from telematics sensors installed in its vehicles, together with mapping data and other real-time reports of drop offs and pick-ups from drivers.

According to UPS, the ORION initiative has helped it to shave around 85 million miles off its daily routes during 2011, something that saved it more than 8.4 million gallons of fuel. The company estimates that this has led to $30 million in savings.

GE provided another great example. They use data to prevent mechanical failure.

“Bill Ruh, Vice President and Corporate Officer for GE’s Global Software Center…highlights GE’s industrial business as a prime target for big data, referencing the health of blades on the jet engines the company manufactures. “Our sensors collect signals on the health of blades on a gas turbine engine to show things like ‘stress cracks.’ The blade monitor can generate 500 gigabytes per day–and that’s only one sensor on the turbine. There are 12000 gas turbines in our fleet.” The value in integrating all the sensor data onto a big data platform can reveal patterns on when blades break, allowing GE to time its manufacturing and repair process before a break occurs.

The big companies all use data in ways that are as unique as their businesses are. However, they each have something in common, as well. Each company has set sensible targets for their business which allows them to create real, actionable results.

This kind of effectiveness starts with the proper training about data analytics. If you’re ready to put data to work for your business, start with TMA’s free webinar. Then, take a look at any of The Modeling Agency’s predictive analytics training courses to get more insight about what big data can do to help your business.

‘Big Data’ Is Dead

Style: "Porcelain pastel"Possibly the most overused and the least understood term since ‘cloud computing’, ‘Big Data’ is dead. It is dead because of it’s complete uselessness in the sense that the phrase itself has lost its meaning. In a constantly maturing industry like Data Mining and Analytics, there can be no clear blanket term to replace ‘Big Data’; What was once a blanket term for a collection of information now lacks specificity and no longer applies universally. Data Mining has evolved in a variety of ways, each of which will be further examined in this post.

Firstly, as analytics become more advanced, some important terms are emerging to reference new, narrowly focused, and highly specialized tools and technologies. As identified by VentureBeat.com, the top items about which you’ll want to be in the know are as follows:

1. Smart Data: As companies needs to more efficiently mine data through solely electronic needs takes precedent in the coming years, one can expect to hear more and more about ‘Smart Data’, data which can be processed without a human mind combing through it by utilizing predictive analytics to anticipate consumer actions. In today’s marketplace, examples such as automated personalizations and recommendations through companies like Amazon, Netflix, and LinkedIn can already be clearly observed.

2. Data Science: A useful term whose popularity has skyrocketed recently, with close to but perhaps not so much overuse as is associated with ‘Big Data’, ‘Data Science’ is meant to refer to a new field which utilizes statistics, machine learning, natural language processing, and computer science to extract meaning from large amounts of data, often with the goal of creating new data products.

3. NewSQL: The scalability of NoSQL combined with the strong ACID guarantees of legacy relational databases offers users new options when dealing with relational data. NoSQL will continue to be valuable for companies who do not require an ACID guarantee, but NewSQL is a solid buzz word of which to be aware and an item whose presence will likely continue to grow.

4. Predictive Analytics: A complicated process which relies on advanced machine learning and statistics to recognize and exploit patterns, predictive analytics is perhaps the root of many of the above mentioned items. Relying on manipulation of historical data to anticipate future actions allows Data Scientists to advise companies and consumers in their best interest. Activities in this arena are applicable in any possible industry and are the driving force behind consumer recommendation services and even fraud detection.

Although the circumstances that gave rise to ‘Big Data’ are still relevant, processes in this arena have progressed, and will continue to progress, beyond the need to store copious amounts of data. New and better systems for processing data will continue to emerge, as will more highly specific terms to describe them.

If you’re interested in learning more about Data Mining’s changing landscape, consider joining The Modeling Agency for a free webinar.  TMA’s training seminars are another, more in-depth way to canvas this growing field and ensure that your company is receiving the maximum benefit from your amassed data.