5 reasons to move to big data (and 1 reason why it won't be easy)

By Reda Chouffani, CIO |  Big Data, Analytics

Another example is medical transcription. As electronic health record (EHR) use grows, healthcare organizations are increasingly using natural language processing systems to transcribe, extract and process data within a clinical context.

2. You'll Benefit From Speed, Capacity and Scalability of Cloud Storage

Organizations that want to utilize substantially large data sets should consider third-party cloud service providers, which can provide both the storage and the computing power necessary crunch data for a specific period.

Cloud storage presents two clear advantages. One, it lets companies analyze massive data sets without making a significant capital investment in hardware to host the data internally. Two, as internal IT departments recognize that big data hosting platforms require new skills and training, they find that a hosted model tends to abstract that complexity, enabling more immediate deployment of big data technology. This also lets developers build a sandbox environment that's preconfigured and ready to go without having to set up the necessary configurations from scratch.

3. Your End Users Can Visualize Data

While the business intelligence software market is relatively mature, a big data initiative is going to require next-level data visualization tools, which present BI data in easy-to-read charts, graphs and slideshows. Due to the vast quantities of data being examined, these applications must be able to offer processing engines that let end users query and manipulate information quickly-even in real time in some cases. Applications will also need adaptors that can connect to external sources for additional data sets.

Analysis: 4 Barriers Stand Between You and Big Data Insight

Usability is another consideration. CFOs, CMOs and other non-IT executives are looking to leverage data, so they need access to charts, infographics and dashboards. Fortunately, leading BI vendors are shifting from an IT-driven to self-service analytics model that puts business users in the driver's seat. This accelerates adoption as well as return on investment and expands analytics' reach beyond report writers and more technical end users.

4. Your Company Can Find New Business Opportunities


Originally published on CIO |  Click here to read the original story.
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