Collaborate 13 IOUG/OAUG/Quest Oracle Conference Recap
by John Kozlowski
Last week I had the pleasure of attending Collaborate 13, the Technology & Applications Forum for the Oracle Community, for the first time. Over 5,000 Oracle experts, users, and partners assembled in Denver, Colorado for a week of education and networking.
I was there as arcplan’s Director of North American Alliances to build and expand our partner community. As the most widely-used third-party BI frontend to Oracle Essbase, I was looking to meet with Essbase experts as well as Hyperion and OBIEE consulting and systems integration firms. Collaborate was an excellent way to get in front of these companies, who can benefit by adding arcplan to their solutions portfolio. I found a great deal of interest and acceptance of our positioning: arcplan as a lower cost, less complex, and quicker-to-implement solution than OBIEE; our extensive connectivity within and outside of Oracle databases; and our ease of use for developers and end users.
My colleagues mentioned that last year at our booth, the common theme of conversations was the challenges IOUG and OAUG members were experiencing around budgeting and planning. This year, however, the conversations tended toward challenges around reporting and dashboards – the importance of connecting all their data sources and making meaningful use out of the data they already have without having to build additional repositories or metadata layers. arcplan is a lightweight, flexible alternative to the Oracle and SAP BI tools many companies have in place that aren’t meeting their needs.
While I met with partners and our team manned the booth, our CEO Roland Hölscher attended Collaborate’s educational sessions…
iWatch MyKPIs: Real-Time KPI Delivery to Your Watch?
by Roland Hoelscher
As speculation about Apple’s iWatch grows – will it be a snap bracelet? will it replace the iPhone? – it got me thinking about a watch (of all things) supporting the vision of real-time analytics. What sounds stupid at first (the notion of an old-fashioned personal device, around for 5 centuries with little to no innovation over such a long period, inspiring a 21st century topic such as real-time analytics) has some merits if you think about it twice.
First off, wearable computing devices are real business. According to tech analyst Juniper Research, the next-gen wearable devices market, including smart glasses, will be worth more than $1.5 billion by 2014, up from just $800 million this year.
While the majority of those devices are sold in the context of fitness and healthcare scenarios, there is applicability in modern enterprises. In fact any business process that can benefit from real-time analytics can leverage computing devices that are “at hand” and travel with us easily.
So what business processes can benefit from real-time analytics?
Predictive Analytics: Examples, Advice and Shortcuts
by Dwight deVeraEveryone 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
Predictive 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….
When Analytics and Collaboration Intersect
by Tiemo Winterkamp
Fueled by the big data hype and the need to extract greater business value from data, investment in business analytics software is on the rise. Many companies have begun to tap into the potential of big data analytics and this number is predicted to increase according to recent reports by the International Data Corporation (IDC). IDC forecasts that the market will continue to grow at a 9.8% compound annual growth rate through 2016 to reach $50.7 billion. Perhaps to a less aggressive extent, interest in Collaborative BI is also on the rise, with top performing companies incorporating collaborative techniques to share knowledge throughout the enterprise according to Aberdeen’s extensive 2011 research report on Collaborative BI. The demands for agile insight and self-service are changing the landscape of BI, driving the need for Collaborative BI, which uses social functionality to improve business decision-making. Separately, the benefits of deploying analytical tools and taking advantage of collaborative techniques are appealing for any organization seeking streamlined operational success – but the payback of merging these initiatives could be even more rewarding.
Analytics is gaining traction in the BI arena due to the need to explore massive amounts of varied information (what we now call big data), extract valuable insight, and quickly deliver these insights to the users who need it. Initiatives geared toward improving analytics utilize technology that gathers and organizes data from disparate data sources and provides a platform for in-depth analysis, yielding benefits such as improved business operations and agility, increased sales, and lower IT costs. So it’s no wonder that organizations are making significant investments in the analytics market.
Collaborative BI, on the other hand, seems to be the new kid on the block…
Designing Olympic “A” Standard BI Dashboards
by Monique Morgan
With trials for the 2012 Olympic Games in London almost complete, as a diehard trackie, I can’t help but reflect on the amazing standards that athletes must meet or exceed in order to qualify for their respective events. For instance, the “A” standard for the men’s 100 meter event is 10.18 seconds – that’s faster than the time it would take for many of us to boot up our computers. The standard for women’s high jump is 1.95 meters or about 6 feet, 4.7 inches – so an “A” standard athlete could easily clear the height of a very tall person. Olympic hopefuls work diligently to meet (or exceed) these high standards. Likewise, in a quest for excellence, we in the business intelligence world should strive to improve the design of our BI dashboards – the ones that guide our daily decision-making. We should be reviewing their effectiveness at least yearly. To that end, we’ve compiled a simple checklist to guide your dashboards towards the “A” standard.
Whittle them down to only the most relevant and timely information. With all the excitement around big data and the need to analyze vast amounts of information in order to spot trends, it’s easy to be swept away in a deluge of data and be distracted from what really matters. As excited as you (or the users you serve) may be to display all kinds of new information, remember that some data is a distraction rather than relevant to the decision-making process. So be cautious of the information overload that can hinder the effectiveness of your dashboards. Each organization must determine what really matters to decision-makers (this will vary between them) and center dashboards around the metrics most relevant to each department.
Implement appropriate design. When it comes to dashboards, looks do matter. But dashboards aren’t just eye candy. They’ve become a standard point of reference for business managers and executives who need to monitor company operations – often at a glance – in order to make timely decisions. In a 2011 interview with Dashboard Insight, Stephen Few, author of bestselling books on dashboard design and data visualization best practices (and also inventor of the bullet graph), explains…
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