There is no shortage of information on how to use parts of the most common big data solutions, like Hadoop. But what about the other pieces of the puzzle necessary to get real business value from this technology? For starters, there is a need to make decisions around:
- Mobile strategy and its support
- Web delivery
- User interactivity/experience
- Data support and operations
- Storage (for both big data and traditional SQL)
- Revenue Generation models
- Filtering knowledge and noise
- Integration into existing applications and processes
For these areas, there is less information available and just as important a need.
In reality, there isn’t a single application development platform that covers a full solution. There are instead many choices, each having tradeoffs in usability and scalability.
Also, there are solutions that have already come and gone in the short time big data has been in vogue. The question arises, “How does one now what will be around and still supported in two years’ time?” Predicting the future popularity and support for the many available tools is a significant challenge.
Open Source is an excellent way to ramp quickly and cheaply, but the solutions aren’t necessarily as mature as market requirements. As things stand today, it would be easy to get a few months into development of a solution before a particular tool’s shortcomings become apparent. A great example would be that basic features like multi-language support are missing from some of the common solutions. Some lack authentication capabilities.
Lastly, user interfaces are no longer a common part of the equation. Less investment has been made in UI technologies in the haste to bring back-end capabilities to market. Avoiding these problems involves having enough knowledge of the space to make sound choices.
Big Data means broad solutions to complex problems. There are enormous opportunities ahead for those who consider the ecosystem beyond the big names, like Hadoop.