If you want to learn how to use your new BI system or the companies BI system - then you most likely want to get the data to your system.
You can download it in several formats (i.e. CSV, TXT, or XLS) and then import into your system. The XLS file format would be the most likely to contain a virus - so if that is an issue you would probably choose to get the data as CSV and convert to something easy to import into your BI tool.
Many of the sites also note that the data is virus free and checked so I have not seen that as an issue.
So Tricia does playing around with sample data typically involved downloading it (ie, bringing it in house) or are we talking about playing around with it on the provider's site (in the cloud, in today's parlance)?
Good question Beth. Many companies have a development or test area where it is playpen area. My larger concern has always been making sure the data is good to use for learning.
I really liked the BIRT data because the data has issues (missing values, complicated joins) that force you to learn how to use the tool to overcome those situations. Real data often has issues so you have to know how to work with the data.
Hi Tricia, I love the idea of using sample data, especially when it's free. But do BI and analytics professionals need to be aware of any risks, especially if you bring the sample data inhouse? Do we have to be concerned about bugs or other security issues, for example?
LEADERS FROM THE BUSINESS AND IT COMMUNITIES DUEL OVER CRITICAL TECHNOLOGY ISSUES
The Current Discussion
Visual Analytics: Who Carries the Onus? The Issue: Data visualization is an up-and-coming technology for businesses that want to deliver analytical results in a visual way, enabling analysts the ability to spot patterns more easily and business users to absorb the insight at a glance and better understand what questions to ask of the data. But does it make more sense to train everybody to handle the visualization mandate or bring on visualization expertise? Our experts are divided on the question. The Speakers: Hyoun Park, Principal Analyst, Nucleus Research; Jonathan Schwabish, US Economist & Data Visualizer
To save this item to your list of favorite AllAnalytics content so you can find it later in your Profile page, click the "Save It" button next to the item.
If you found this interesting or useful, please use the links to the services below to share it with other readers. You will need a free account with each service to share an item via that service.
Dynamic data visualizations let analysts and business users interact with the data, changing variables or drilling down into data points, and see results in a flash. Advance your use of data visualization with tools that support features like auto-charting, explanatory pop-ups, and mobile sharing.
No doubt your enterprise is amassing loads of data for fact-based decision-making. Hand in hand with all that data comes big computational requirements. Can traditional IT infrastructure handle the increasing number and complexity of your analytical work? Probably not, which is why you need a backend rethink. Big data calls for a high-performance analytics infrastructure, as Fern Halper, a partner at the IT consulting and research firm, Hurwitz & Associates, discusses here.
Redbox's bright-red DVD kiosks are all but ubiquitous these days, located in more than 28,000 spots across the country. Jayson Tipp, Redbox VP of Analytics and CRM, provides an insider's look at how the company has accomplished its phenomenal nine-year growth.
InterContinental Hotels Group (IHG), a seven-brand global hotelier, has woven analytics into the fabric of its operations. David Schmitt, director of performance strategy and planning, shares IHG's analytics story and his lessons learned.
Elizabeth Barth-Thacker, a BI and informatics technology manager at Humana, tells us how her team is creating data transparency and building engagement with the business – with the help of an internal collaboration portal called Humanalytics.
Speaking at SAS Global Forum Executive Conference, Rajeev Kaul, SVP of pricing at OfficeMax, uses a Chinese proverb to explain one of the reasons he's deploying SAS Visual Analytics.
In an All Analytics interview, Mike Cavaretta, technical leader, predictive analytics at Ford Research & Advanced Engineering, shares how big-data is fueling vehicle decisions.
Analytics professionals and SAS executives share how organizations can get on with their work so much faster when working in a high-performance and visual analytics environment.
Analytics professionals who attended SAS's recent Executive Briefing in New York share how they think visual analytics might help their organizations get better value from data.
At Boeing, effective decision making comes down to this simple formula: QxA=E, as executive Jerry Allyne explained at the recent INFORMS analytics conference.
Whether working in major league sports, financial services, or healthcare, analytics, and data, professionals are checking out how visual analytics and high-performance technologies can help them optimize their environments, shrink their cycle times, and improve decision making, as attendees at the recent SAS Executive Briefing in New York share with us.
SAS CEO Jim Goodnight speaks with us at a recent SAS Executive Briefing about getting a feel for what's in your big-data and other new realities powered by advanced analytics.
Jim Davis, SVP and CMO at SAS, talks with us at a recent SAS Executive Briefing about how high-performance analytics and visual analytics take away the concerns over big-data and let companies get down to business with their data.
Tweet This
7 
3 
