Inspiration
Big corporations invest ever increasing amounts of resources into business analytics departments. This widens the gap with the middle/small retailers who struggle to compete. In addition to not having a dedicated team for data driven decisions, ERP solutions are also not an option, as they take a sizable portion of the revenues. The target group for our app are the local bakeries, fruit and vegetable stores e.t.c , alongside your average self employed Alibaba or Ebay retailer. A further solution-cap exists in developing countries, where the need for services provided by SAP has yet to become a necessity.
What it does
Tiny Analyst provides an easy to digest breakdown of all the important data needed to run your company. Today , next week, next month or many years into the future, we will show you how well your products are performing, how to optimise your warehousing, plan your promotions, discounts and much more.
How we built it
We build the app on a 3 component architecture. An iOS App periodically requests data from a python server. Different analytical methods are then applied with the goal of generating business insights. Those are then grouped and weighted based on importance (time, effect on profits e.t.c). The selected data packages are provided to a Visualizing component which creates short, dynamically generated, animated content with the goal to make the key information apparent. The prepared material is returned to the server and makes its way to the user. Three different content lists are displayed (Daily, Weekly, Monthly).
Challenges we ran into
Extracting meaningful information from data is a task that requires a lot of time and effort. Generating insights or recommendations from that information is even a greater challenge.
Accomplishments that we're proud of
We believe our app will provide users, without an analytical background, valuable information that would help them run their business. Big Data is an integral part of the twenty-first century and we provide that opportunity to businesses that need it the most with minimum effort/investment on their part.
What we learned
Variety of methods to parse and work with Data-sets alongside different techniques to extract information and recommendations.
What's next for Brute Force Technologies
We will continue to look for ways to make monetarily gated advantages more accessible and simple to implement for everyone.
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