Web Development: Webapp for sales data analysis (Dearborn) - (Dearborn) in Detroit, Michigan For Sale
The app analyzes sales data through customized aggregation, dedicated analytics, and charts. The required functionalities are better described by looking at the data structure. Data At the lowest level of aggregation the data is organized by item and each item is associated with a time series (sales data). At a higher level of aggregation, each item is associated to a customer, and each customer is associated to a region. From a top-down point of view the data is organized in a tree-type structure by region/customer/item. At each level in the hierarchy a 'parent' is an associated with a time series obtained by aggregating (summing) the time series of each of its child, in a recursive way. Analytics For example, the app needs to calculate the volatility of sales data, at each aggregation level. At the lowest level, that is simply the standard deviation of the time series associated to an item. At higher levels of aggregation, the time series need to be aggregated first (summed) and then the standard deviation (or other statistic) is calculated on the aggregated time series. More statistics will be developed, but the logic will be the same. Layout and Interactive Functionalities The data will be presented in a tree-type format. The rows at the various levels can be compressed and expanded. The columns will be customizable in terms of number of columns, statistics, etc. and be selectable from a list. The columns will also be sortable. The sorting algorithm will sort the top level of aggregation first and then the next levels down, recursively. For example, if the tree is region/customer/item, the sorting algorithm will first sort the statistic by region, then within that region it will sort the customers within that region, etc. The user will be able to drag and drop items from one customer to another and customers can be dragged and dropped between different regions. In general, a row can be dragged and dropped into another category at the same level of aggregation (a child can change parent). Extra items, not present in the original breakdown can be selected from a universe of available items. Each item is associated with an additional list of other attributes ( tags ), eg type, rating, etc. The tree-structure needs to allow for any custom aggregation, eg by region/rating/item, or customer/region/rating/item, etc. Look and feel The app should very intuitive and easy to use with state of the art components and charts. Charts and additional tables The user will be able to select rows and a set of charts will provide visualization. Development The app should be accessible from desktop, mobile, or tablet. The analytics should be developed so that I can deploy new functions to the app (written in Python). The data will be provided in a spreadsheet but should then be stored via DB possibly MySQL. The app should be developed with open source code and so that it can grow organically once more functionalities and pages are added. A more detailed set of specs will be provided, but the structure of the problem is described above. Many other additional features that can be added in the future. If the project is of interest, please send a link to relevant work. Thank you very much! R. Outsource.com helps thousands of small businesses looking to find and hire talented freelancers. We re the fastest growing online freelance website today! We have clients ready to hire you if you provide any freelance services and need extra work. Create a Winning Profile Describe the problems you solve, add client reviews, and create an attractive portfolio. Receive Requests for Your Work We simplify your job search by matching you with clients who are seeking your skill set. Send a Quote Your custom quote includes a price estimate and a personal message. Purchase credits to send quotes, to learn more about credits please click APPLY!
Source: http://www.juju.com/jad/xxxxxxxxrlk0uk?partnerid=af0exxxx314cbc501beebacaxxxx739d&exported=True&channel=staticfile&hosted_timestamp=xxxxa345f27ac5dcxxxxd7b93f091ce1bfe900aaxxxx8c2cd91cbc4f8a4b3de8