Think Big Analytics has raised $3 million from angel investors for what it calls its “big data as a service,” which combines data science and data engineering for customers invested in building out infrastructures to get more from their data and build predictive models to make decisions. Daniel Scheinman led the investment with participation from WI Harper Group.
Think Big is a new form of service provider that specializes in helping companies take advantage of a new wave of software and cloud-based offerings that have been built out with big data in mind.
This is a departure from the more traditional companies that prospered during the 1990s when more software started getting built on top of client/server stacks and companies actually saw value in multi-year, multi-million dollar ERP projects. Since then, Internet scale companies like Google have shared some of their methods for analyzing data on elastic networks of servers.
Businesses do need help but the services deals are not country club solutions projects. The teams are smaller, the engagements shorter. Companies don’t see the value in large-scale systems-integrations projects. Still, the new technology is not shrink-wrapped and packaged. Companies need help putting it together and then layering the data. Once that’s done, the solutions can often be self-serve.
The problem with big data pretty much comes down to the fact that few actually know how to collect it, much less analyze and act upon it. Big Think aspires to serve this data-hungry market but not in the form of a multi-million-dollar systems-integration project the guy in the suit sold to his pal at a wine and dine Super Bowl weekend party back in 1995.
These are different times, folks. Different times.
Think Big Analytics provides services to assemble Big Data applications. The company provides data science and engineering services to assemble custom applications oriented towards business outcomes. Its “test and learn” methodology was created for Big Data projects to prioritize initiatives and learn from frequent releases.