Business Intelligence Blog from arcplan
30Mar/120

The Practicalities of Moving BI Into the Cloud: Part II

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In Part I, I talked about a couple of reasons why cloud BI hasn’t gone mainstream yet – the inherent complexity of BI systems and the amount of data produced daily. Then I presented a secure way for data to remain in place but your BI to move into the cloud. (web services-based SOA broadcast services, essentially querying data that exists behind your corporate firewall from the cloud). Today let’s weigh the risks vs. rewards of moving your BI to the cloud.

Choosing a Cloud BI Vendor
Do you stick with your familiar BI software as it adapts to a SaaS model or go with a newcomer offering true SaaS? Be sure to carefully consider your business requirements and go with a vendor that meets them. You may risk going with a smaller vendor, but you are more likely to get the BI deployment you want.

TCO
Certainly evaluate the long-term cost of ownership – cloud BI may be more affordable at the outset and allow you to avoid the capital expenditure approval process, but will it cost more in the end? The reward of a quick implementation and “easy out” may be worth the risk of higher long-term cost and may lead to additional benefits, like allowing you to scale your BI to more users throughout the organization faster.

Time Savings
Sticking with an in-house BI deployment results in your IT team spending time to set up, tweak, maintain, and debug servers – time that could be better spent elsewhere…

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28Mar/120

The Practicalities of Moving BI Into the Cloud: Part I

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Many (if not most) companies are evaluating the benefits and risks of cloud-based solutions this year. In fact, marketing research firm IDC predicts that businesses will spend $22.6 billion on cloud services by 2015. However, there is one area that has fallen behind the cloud – business intelligence. But it’s ready to emerge. Even organizations with traditional (hosted on-premise) BI systems in place can make the move. Let’s consider the practicalities of doing so.

Organizations that have deployed business intelligence have first-hand knowledge of the complexities of such a system – the vast network of linked parts and pieces, from data warehouses to ETL applications, OLAP servers to analytical dashboards. It’s a jungle out there and it’s clear that it can’t continue this way for much longer. A more repeatable and sustainable model for business intelligence must emerge – one that reduces the complexity while maintaining security and enhancing ease of use.

The Data Question
For services like CRM and document collaboration, the roadmap for moving to the cloud has already been established by companies like Salesforce.com and Google. But for BI, it’s not as clear. The sensitivity and volume of data as well as the inherent complexity of BI systems have left executing a cloud-based BI strategy more of a dream than a reality.

Many believe that the next logical step in BI’s evolution is moving it to the cloud. However, when looking at the characteristics of a modern day BI deployment, it’s easy see how getting there is complicated.

Let’s take a look at just one aspect of a cloud BI deployment: the amount of data that would need to be moved, stored, and processed. There’s a reason we’re all talking about big data these days – according to April Adams, research director at Gartner, data capacity in enterprises is growing at 40% to 60% year over year…

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23Mar/120

Big Data FAQs – A Primer

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The big data trend promises that harnessing the wealth and volume of information in your enterprise leads to better customer insight, operational efficiency, and competitive advantage. The marketing hype around big data and the pace of studies, analyst reports, and articles on the subject can be mind-numbing for companies that want to take advantage of big data analytics but do not know how to separate fact from fiction and determine real use cases for their business. So here’s a big data primer for those just getting in the game.

1) What exactly is big data?
“Big data” is an all-inclusive term used to describe vast amounts of information. In contrast to traditional structured data which is typically stored in a relational database, big data varies in terms of volume, velocity, and variety. Big data is characteristically generated in large volumes – on the order of terabytes or exabytes of data (starts with 1 and has 18 zeros after it, or 1 million terabytes) per individual data set. Big data is also generated with high velocity – it is collected at frequent intervals – which makes it difficult to analyze (though analyzing it rapidly makes it more valuable). Additionally, big data is usually not nicely packaged in a spreadsheet or even a multidimensional database and often includes unstructured, qualitative information as well.

2) Is it a new trend?
Not exactly. Though there is a lot of buzz around the topic, big data has been around a long time. Think back to when you first heard of scientific researchers using supercomputers to analyze massive amounts of data. The difference now is that big data is accessible to regular BI users and is applicable to the enterprise. The reason it is gaining traction is because there are more public use cases about companies getting real value from big data (like Walmart analyzing real-time social media data for trends, then using that information to guide online ad purchases). Though big data adoption is limited right now, IDC determined that the big data technology and services market was worth $3.2B USD in 2010 and is going to skyrocket to $16.9B by 2015.

3) Where does big data come from?
Big data is often boiled down to a few varieties including social data, machine data, and transactional data…

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21Mar/120

arc|platform 2012 Partner Conference Recap

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Last Thursday & Friday, March 15th-16th, we held our largest partner conference in history at the Atlantic Hotel in Essen, Germany. More than 140 international participants – including arcplan partners, systems integrators, and resellers from Germany, Austria, Spain, Switzerland, the United Kingdom, the United States, Brazil, India, China, and Morocco – joined us for 2 days of presentations, networking, awards, and even a little friendly competition (attendees enjoyed a slotcar racing competition that highlighted our theme of “speed up your business”). Sincere thanks to our sponsors Teradata (Platinum), Oracle (Gold & Evening) and Amorsys (Gold) as well as our presenters!

The conference provided the opportunity for arcplanners (as we fondly call ourselves) to share updates on our company vision, product development, and sales strategies with our partners. They discussed the new arcplan 7 BI platform, its roadmap, and how arcplan is continuing to stay ahead of trends in self-service, mobile, cloud, and collaborative BI. Our CEO, Roland Hölscher (pictured right), delivered an inspiring keynote on these topics and highlighted how arcplan enables customers and partners to simplify and accelerate decision-making by 1) easily connecting users with all relevant information sources, 2) providing integrated solutions for analyzing the past and planning for the future, and 3) making critical business insight available in real-time, anywhere on any device. In addition, he announced arcplan’s support for SAP HANA with our latest version, solidifying us as the #1 BI front-end for SAP environments.

As for the other presentations at arc|platform, there were too many excellent ones to mention them all, but here’s a few highlights…

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16Mar/120

4 Things I Learned About BI Strategy from Playing Scrabble

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I enjoy a good game of Scrabble, whether with a friend or with a fellow enthusiast online. Recently in a really close game, I was able to clinch my victory by strategically placing an “x” to spell “xi,” earning me a final 27 points. Though I’m no expert at Scrabble, I’ve picked up a few strategies that apply to the business intelligence world:

1) Planning matters.
Scrabble is all about planning and strategy. You may have a great word lined up on your rack but you can’t just play it anywhere. You need to plan ahead, consider your opponent’s next move and the remaining open spaces on the board. Similarly, your business needs to plan ahead and BI software facilitates that planning. Just like you lay out your Scrabble tiles over and over to plan for maximum word score, budgeting & planning software allows finance teams to perform monthly re-forecasting and rolling forecasts that help your business adjust to changing market conditions. The automation built into BI software makes it possible to be more forward-thinking since there’s more time for analysis and less manual data entry and consolidation.

2) Analyze the changing environment.
So you’ve just made your move and now you have to refresh your rack with new letters. The board has changed and so have your options. In Scrabble, your playing environment constantly changes just like in the real world. How quickly can your business react to market changes? BI software like arcplan enables what-if, best case and worst case scenario planning, which are critical to an enterprise’s long-term stability and growth. What about trend spotting? Maybe you notice your opponent tending to place 4-letter words, allowing you to somewhat anticipate his or her next move. Spotting and reacting to trends is crucial for businesses that want to compete. Do you have an analytic tool in place that allows you to visually spot patterns, analyze data on the fly for underlying causes, and make decisions that will move your company in the right direction? When businesses first get to know arcplan, the application we show them is a dashboard app that features an ad-hoc component. This app allows users to explore the patterns they see on their dashboard in greater detail. Business intelligence provides insight beyond just reporting; it’s the analysis that helps you make sense of the data and get insight that enables better decisions.

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