Business Intelligence Blog from arcplan
21Aug/130

On-Demand Webinar: Business Intelligence as the Gateway to Big Data

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View-WebinarCheck out this on-demand webinar from arcplan – a 40-minute primer on using big data and BI together for enterprise impact.

Business Intelligence as the Gateway to Big Data
Recorded Date: August 28, 2013
Speakers: Dwight deVera, arcplan Senior VP; Tom Veith, Senior Solutions Manager

About this webinar:

You’ve heard the hype around big data, and maybe you’ve put some thought into how it could impact your business. After all, the promise of big data is accessing hidden insights, discovering new approaches, and making better decisions. But how do you begin developing a technology approach that’s practical and doesn’t require a massive investment of money, time and resources?

big-data-biThe answer is to leverage business intelligence platforms that can handle huge data volumes, provide real-time access and enable data exploration. This webinar serves as a primer on how to practically use big data and BI together. Investments in big data usually allow a group of data scientists to deliver their results to a small community of business end users. To get beyond small communities and have an enterprise impact, you’ll need business intelligence – the mechanism to scale your big data initiative across the enterprise.

In this webinar, we:

  • Lay out the big data approaches you can take based on your available resources and infrastructure, and the benefits and challenges of each approach
  • Explain the benefits of utilizing existing BI platforms for big data analysis and visualization
  • Demonstrate big data and BI in action on Teradata and Google BigQuery

This isn’t a webinar for IT professionals only. We break the concepts down in a way that makes sense for everyone.

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21Jun/130

Finding the Right Analytics Engine For Your Business

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luxurycar_BIAs we usher in the warm summer months, I can’t help but notice people taking their high performance convertibles out of the garage for a spin. Upon leaving the infamous King of Prussia mall last weekend, I saw a Mercedes SL550 Roadster and an Audi R8 in the parking lot. That’s when I learned an important lesson: people actually drive cars that are over $100k. No but seriously, while these sports cars are great for feeding your occasional need for speed or making a bold statement about personal taste, they are not meant for everyday use. For most of us, a comfortable, mid-range vehicle that won’t empty your bank account works just fine. The same is true when selecting an analytic tool for your businesses. Business analytics solutions are set to reach 50% of potential users by 2014 according to Gartner, but maybe your organization is a bit behind. Choosing an analytic tool can be a bumpy road, so let’s discuss some things you should think about when choosing the right solution for your company’s needs:

Balanced and smooth
When purchasing a vehicle, most buyers will select one that’s reliable, safe, and will hold its value over time. When purchasing a business intelligence solution to meet everyday analytic needs, you should think about similar qualities: you want a BI tool that reliably helps you address specific business problems, is user-friendly for users of all skill levels (especially if you’re shooting for that 50% adoption rate), and holds its value over time – also known as a return on investment.  “Balanced and smooth” BI solutions – those that offer a good deal of options but are easy to install and work with – are great for organizations just getting their feet wet with BI technology…

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14Feb/130

Predictive Analytics: Examples, Advice and Shortcuts

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Everyone is throwing around the term “analytics” – about as much as they’re throwing around the term “big data.” While I might put big data on my list of the Most Overused Phrases, analytics gets a pass. As companies realize the amount of insight and value they can glean from their ever growing volumes of data, there has been a surge in analytics initiatives. The goal of these projects is to use data to analyze trends, the effects of decisions, and the impact of scenarios to make improvements that will positively impact the company’s bottom line, improve processes, and help the business plan for the future.

In order for analytics to remain relevant and always provide value, organizations must continually up their game. One way to do this is with predictive analytics, which is becoming more mainstream every day. If you stick around to the end of the article, I’ll tell you a simple way to bypass its complexity and still get the predictions you need.

Gettin’ Predictive With It
Ventana-predictivePredictive analytics involves making predictions about the future or setting potential courses of action by analyzing past data. A 2012 benchmark study by Ventana Research revealed that predictive analytics is currently used to address a variety of business needs, including forecasting, marketing, customer service, product offers and even fraud detection. While predictive analytics used to be in play in only a small number of companies, two-thirds of companies participating in Ventana’s survey are using it, and among those, two-thirds are satisfied or very satisfied. These results indicate the maturity that predictive analytics has undergone over the last few years, as technology has advanced to make it less expensive and more approachable, and therefore easier for more areas of the business to make use of. At this point, it’s safe to say that most Fortune 500 companies are churning out predictive insights on a regular basis, but that doesn’t mean smaller companies without “big data” can’t do the same thing. They can supplement their internal data with external data from social media, government agencies, and other sources of public data to get the insights they need.

In Practice
Let’s take a look at finance institutions, which have predictive analytics down to a science….

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6Dec/120

Why I’m Not Impressed With Your Big Data

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Musings on the challenges of big data in a year of serious hype

There’s a reason you haven’t heard more than a handful of big data success stories in 2012. Handling big data correctly is hard, requires huge infrastructure and resource investments, and may not be worth it…yet. According to one survey in November 2012, 60% of businesses said it’s too early to tell if their big data project was successful and produced a proper ROI. It seems that so much of the hype around big data is focused on the technologies you need to buy and the talent you need to acquire (data scientist is the latest fad title), and not on what’s most important: what you can do with the data, what value you can extract, what business decisions you can speed up or improve with all that data.

With companies jumping on the big data bandwagon to the tune of $28 billion this year, it’s time to discuss why it might be best to ignore the hype for now and focus on reaping insight from the data you have already. Here’s why I’m not impressed with your big data:

You don’t actually have big data.
The marketing hype can lead you to believe you have a “big data problem” when you really don’t. Using the terminology incorrectly has the potential to harm your business, causing you to invest in unnecessary infrastructure when you may be able to leverage what you already have in place. Even Microsoft and Yahoo! have made this mistake…

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26Oct/120

Teradata PARTNERS User Group Conference 2012 Recap

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I just got back from the Teradata PARTNERS Conference in Washington D.C. – once again a a great event for learning from experts in the industry, listening to real-world examples on challenges with managing and leveraging huge data volumes, and networking with our fellow Teradata partners and customers alike.

It was my second consecutive year at the event, and what struck me most this year was that the topics have clearly shifted from managing big data to leveraging big data. Obviously, data volumes are exploding due to social media and clickstream data, sensor data and other sources and will only continue to grow. This year’s conference, however, was all about Analytics – how to use those data to drive business benefits. And there were great examples given at the conference.

In one of his presentations, Stephen Brobst, CTO of Teradata, described the benefits of collecting weather data around retail stores to determine whether conditions have a significant impact on food consumption in the store (e.g. the deli section). He said combining external weather forecasts with internal operational data and analytical information allows stores to adjust staffing and supplies for a huge impact on the bottom line.

Shaun Connolly, Program Director of Global Industry Solution at Teradata, described an example of how FedEx was able to save $60 million in staffing per year…

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