These days, big data is attracting a lot of attention—and a wide variety of funding—from all sorts of industries, as well as consumer applications. But just recognizing trends in technology, although helpful, doesn’t always point to the key factors that spawned them, and savvy companies who want to transition from start-up status to business leaders need actionable ideas designed to breed growth.
Building a big data company can become an achievable goal with the help of techniques that have already been proven to generate results. Here are five strategies based on observations made from previous successes that can point the way forward:
1. Going from a Platform to an Ecosystem. Watching how quickly an ecosystem is forming around an existing platform is a good indicator of whether or not that platform will take root. Consider the boom experienced by Salesforce during the SaaS era. By establishing a sprawling, adaptive ecosystem, they became a giant, and big data companies can follow the same trend.
Past trends also show that ecosystems of companies could combine the burgeoning Hadoop open source community and an adaptive portfolio of partner solutions in effective ways. Using these resources, enterprise customers can easily incorporate big data initiatives with the utilities and applications that are already customized to receive them. Also, companies could build an impressive ecosystem of partners that transcend industry lines to answer the big data needs of today and tomorrow.
2. Do the Dirty Work. Someone once said, “The ultimate job security means doing the job no one else wants to do.” Although this means doing the stuff no one else wants to tackle, like solving cumbersome data integration issues, companies which take on such jobs can develop their niche and become giants by simply performing the tasks that take time, energy, and insight.
For instance, companies have been able to accomplish much by inventive actions for difficult data integration tasks. Transforming raw data into an actionable form could enable companies to offer practical solutions for technical and non-technical analysts, thus ensuring their position in big data leadership.
3. Offer Insight. Real business intelligence requires interpretations and insights, not just numbers. The same principles that apply to brick and mortar success apply here. Insights provided through fast and easy to understand techniques can orchestrate success for a big data companyby setting it apart from the others.
4. Embedded Expertise. In the past, companies have become leaders in the software industry by embedding their valuable expertise into their analytics application in a way that it could not be extricated.
In addition, big data analytics companies can offer valuable domain expertise though a combination of human and automated resources for specific uses, such as cyber-security, or for other vertical industries, like law enforcement and healthcare.
5. Offer Intuitive Interface. This point may seem trivial, but it isn’t. If people don’t want to use their interface to interact with the data, they won’t; or it will seem like a chore. But by making the interface something that offers a great user experience, companies can move closer to the goal of becoming leaders in the big data arena. So don’t skimp on the details that will make your application easy or fun to use.
With the expanding capabilities that are becoming daily realities, watch out for new methods that will deliver data in ways never imagined before. In fact, companies will even need to rethink data ownership, which will create a whole new area for innovative expansion in the days to come.