SEVENTH is a data management platform, where users can manage their own data along with third party data, under same data schema. This helps users to work with modern data analytics tools to drive more insights from multiple sets of data.
To work with multiple data-set, all data-set must be cleaned. Data-sets must be deserialized and serialized in and out of unified data schema. The first challenge was (and still is) to create adapters and converters that are flexible enough to work with variety of data-sets, to convert a data-set to universal data schema. Today, we are using community effort, and be able to create such adapters and share at marketplace.
Now that you have all of data-set in one data schema, accessing your data from anywhere anytime is next crucial point. We have all of our data managed under cloud servers, protecting your data, and giving most convenient and fastest access whenever you need at volume you desire via API.
The true value of SEVENTH is; you can work with variety of third party data and services. The platform already provides all features to manage and visualize your data. But, single data-set hardly brings any values. The true value of data is being able to drive insights from your data-sets, along with collated data-sets. We have data provider or data collecting services that can be worked as a collated data with your data, helping to predict and model insights.
This is what we believe. Everything happens for reasons, and reasons are made with logics or rules.
Finding rules and equations (logic) are regular practices for finding probability and prediction from set of data. However, the real life data is not simple and independent hence there is no point in having prediction of data that depends on other data-set. From group of data-sets, we conclude degree of correlation for the period of span. If we find strong correlation in long period of span, it is likely to sustain strong correlation in the future too? Our answer is, maybe, or maybe not. But we can help to compute the most accurate prediction from multiple data-set using third party deep learning services, by giving as many collated data within giving span. This way, you will know what will or will not happen if you choose to proceed with your decisions at giving time.
We saw data analytic, forecasting, BI, AI, all of these sectors will be big and growing market. We originally started out making BI tools, dashboard following these market. However, today, we provide a data platform service on top of cloud data storage service. We have chosen this model because we think this service needed first to create more insightful output from any BI tools.
We are here at backend to clean and organize multiple set of data for BI - Analytic tools, for those service to be able to work more efficiently and effectively. All bussineses own and work with variety of data-set that may not seem to be related. However, working with different type of dataset on same unified data schema generates new outcome that you have not yet seen, with value you have not yet experienced.
It is important that system can scale up properly and easily as your company grow or become more data driven company. And not to forget, being able to scale down is also as important to reduce fixed cost when needed. Our platform is designed as per used bases pricing model, allowing you to have freedom to scale up and down as your business need. When the time comes that you need to do heavy computing, our virtual server will collect resources within our cloud computing system to deliver computed data for you to see and use. And if you are not using it, that resource will be used by others and you do not need to pay for it. Our platform gives businesses easy access to the top level machine learning intelligent system at low overhead cost. Data driven business doesn’t mean you have to have your own data team, infrastructure and big annual fixed cost anymore.