3 S for Building Big Data Analytics Tool of the Future

3 S for Building Big Data Analytics Tool of the Future
3 S for Building Big Data Analytics Tool of the Future

There is a huge debate on what constitutes the Big Data Analytics tool of the future and many jump in the race to try their flavor of solutions or problem solving techniques that address many critical use cases at play in Big Data laden businesses. While new businesses are working at it, what constitutes a good fundamental theory on product design strategy that could help create something for the future – Solutions with an ability to stay competitive and relevant in the current times.

On the search for some thoughts, I stumbled upon the video of Christopher Lynch from Atlas Venture (@AnalyticsWeek Boston’s First Unconference Finance/Insurance track keynote). He made some interesting points on what constitutes an interesting focus area for new opportunities. You could see the video attached below(Click the video below to watch the specific bit, I would also recommend watching the entire bit as it has lots of great points on current big data ecosystem). He touched on 3S’s Simplicity, Scalability and Security as 3 fundamental areas for big data analytics companies. He certainly has an interesting perspective and surely provides a good coverage on the current disruptive opportunity areas. I’ve some coinciding thoughts briefly mentioned in the ebook Data Driven Innovation – A Primer(download free here). I briefly touched about 3S’s that we should use in our products to help cause much needed disruption in big data space. My laundry list was Small, Simple and Scale. So, it’s great to have 2 of 3 areas that Chris also slated.

3S’s that I think will shape the future of Big Data Analytics and Why:

1. Small: Yes, Big Data is Big but the solution should be small. Reducing the scope of the product to the one magical thing that could solve a potential use case. Wearing a system’s architect hat, one could easily vote for it as small solutions tends to scale well and are more often than not simple to understand. Small is where the most tough part goes in the planning. When you’ve heard that 80% is planning and 20% is execution, it is safe to say that 80% is / should be spend on making the solution smaller. A quick bite size for easy adaptability.

2. Simple: This is a no brainer in the world of software engineering. Simplicity always triumphs ginormous complicated product. Sure, complexity sells but as a service and not as a product. Who has not heard about the quote “if you can’t explain it simply you don’t understand it well enough?”. This is applicable to a good system design and hence a good big data product design. Simple solutions are often understood quickly and therefore meet easy adoption, hence better sales. In fact, it could be safe to say that simplicity is the most important aspect of the 3 listed here.

3. Scale: This is surely a freebie if you get the first two right, but there have been times when a simple and small solution failed to scale. Scalability is another good area of focus for disruption. A good unit size simple tool could be replicated over and over. This will induce the element of scalability in the tools. A good system should be able to grow with the company it is helping to grow. A tool that does not travel for a long ride with a company will often see a diminishing adoption right at the beginning. A great hopeful thought is that this point is easiest to achieve if above 2 points are taken into consideration. Scalability is important for adoption among big businesses who deal with big blobs of data.

I would certainly agree to Chris’s point of importance of security in current tools for easy adoption in enterprise world and I should probably add it as my 4th S as well. So, yes, all powers to you and congratulations on your disruptive platform if you’ve build your science around those 4S’s. World needs your product and Big Data Analytics world is craving for disruption from the tools that only serve to the 1% and rest 99% only wait and watch for the tools to get to their capability levels, else they have to up their game and buy into ocean of tools which are complicated, super sticky and failure is expensive.

Till that day arrives, all we’ve to do is write in front of us: Simple, Small & Scalable and keep them in mind as you build a solution.

Here’s the video (If you don’t have time? Skip to 4m 10sec down):

Originally Posted at: 3 S for Building Big Data Analytics Tool of the Future

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