In my last post on this subject, I talked about the benefits of cloud computing, especially when it comes to deploying BI in the cloud. The advantages are numerous, but there are also drawbacks that need to be considered before responsibly moving forward. Here are some of the arguments we hear about from our customers and how business intelligence providers have already thought of ways to curb them:
Data security. Security is a concern for IT and business professionals alike. Since your business performance data is stored externally in a cloud model, data management and protection is in the hands of the provider – not your IT department. For regulated environments such as the pharmaceutical, healthcare and financial services industries however, data security is paramount and their information may never be stored off-site. However, it’s still possible to deploy your BI in the cloud even if your data needs to be stored on the premises. It simply involves storing your data on-site behind firewalls and running your queries and reports over the web in a browser. Your data never leaves the premises so you maintain your own data security, but you still benefit from less hardware costs and time saved from not having to install the BI software on every machine or mobile device. It’s a win-win. You can learn more about this particular style of deploying cloud BI in our webinar, A Roadmap for BI Cloud Computing, which is available as a recording here.
Data backup. Though it’s a cost-saving measure to dump your backup servers, having your backup and storage off-site can keep you up at night. If your company is dependent on the cloud provider’s backup and redundancy services to preserve data if any issues arise, you better hope you chose your vendor wisely :-). No seriously, the method we just touched on where data is actually stored on the premises is a compromise that can alleviate this issue.
“Cloud computing” is a term that’s thrown around a lot today, but it simply means accessing your data and applications without on-site infrastructure, i.e. in the cloud. Data processing, storage and backup, maintenance, administration and even troubleshooting are all taken care of by the service provider.
Some of us (like me) were skeptical when everything started being labeled as “cloud.” The thought of not having a trusted IT department maintain control of data and hardware was a little unsettling at first. But after considering the pros and cons of cloud computing (and also realizing that I use cloud services like Gmail and Salesforce.com every day without hesitation), the advantages became clear, even for business intelligence.
Implementing BI in the cloud is a dilemma for a lot of organizations we work with. They’re (rightly) concerned about data security, hardware failure, and anything that could take their reports offline, slow employees’ decision-making process, or expose valuable information to the wrong people. Those are all concerns that have been and continue to be addressed by cloud providers. Certainly data security and back-ups have become paramount to vendors offering cloud services. But as we hear less and less about massive cloud failures in the news and executives and IT managers get more comfortable with the cloud, we’ve seen a shift toward the cloud becoming acceptable for business intelligence deployments. Here’s why:
The cloud offers access to data, applications and other resources without the need for program installation. This equals major convenience when doing work on a portable device like a laptop, tablet PC or smartphone. Not only are your devices free from the clutter of numerous installs (which facilitates effective use of resources), but your company’s IT team isn’t bogged down with installing, reinstalling, and troubleshooting numerous devices for each employee. And since many of us work remotely occasionally, if not exclusively, a lightweight approach to accessing data is truly beneficial.
Marketing research firm IDC predicts that businesses will spend $7.3 billion net new IT dollars on cloud services by 2013. For services like CRM (Salesforce.com) and document collaboration (Google Docs), the roadmap for moving to the cloud has already been established. But for business intelligence, it’s not as clear. The sensitivity and volume of data and the potential complexity of BI systems have made executing a cloud-based BI strategy more of a dream than a reality.
If you’ve been thinking about how to move your BI to the cloud, I hope you’ll join arcplan on Thursday for our webinar, A Roadmap for BI Cloud Computing. It’s a roadmap for implementing BI in the cloud that mitigates concerns about data security and confidentiality. The strategy we’ll present allows BI consumers to manage large volumes of data securely at a low cost and with shortened implementation times.
Whether you’re a smaller company looking for a cost-effective, easy entry-point into BI or you’re a large organization looking to capitalize on what’s sure to be a trend with staying power, this webinar is worth your time. Here are the details:
Date: Thursday, January 27th
Time: 2 – 3 pm Eastern (NYC time)
Speaker: arcplan Senior VP, Dwight deVera
UPDATE 1/28/11: Click here to access the recording of this event.
Business Intelligence applications are often based on a denormalized version of transactional data. This is done mainly to:
- keep analytical processing from slowing down the transaction systems
- create “reporting friendly” databases that lend themselves to analysis
Traditionally, both Transactional and Analytical databases reside on hardware inside the company’s firewall and when necessary, a BI report and/or chart can drill down from one system to another transparently.
With Cloud Computing, this model gets more complicated. The current trend of moving to the Software as a Service (SaaS) model is centered on transaction processing. For example, Salesforce.com is a transactional system that allows users to access a Customer Relationship Management system in a cloud. In the old days, because of the total cost of ownership, smaller organizations could ill afford to acquire these systems, and instead, resorted to maintaining their data in home grown and/or Excel-based databases. The SaaS model allows an organization of any size to access and benefit from very sophisticated systems through subscribing to them on a named user basis. Therefore, whether an organization has 10 or 1,000 sales reps, it can maintain a robust set of metrics at a very reasonable cost.