Cooking Data

To handle data, it is first necessary to understand data structure. Forget relational structure, look for graph databases and think in documents related to each other. That's the, way handle data. Just the amound of all the entities and to find a specific item is a little bit tricky. Our data factory allow us, to store, find and relate data.

Restructured with love

To relate data and join things together, what should joined together, is is fundamental necessary, to have a common wording of key:value structure. We have it, and now, a Car can talk to a Human, an Asset can talk to any kind of Object or Scheme. It look's like CHAOS, but not for us.

Human's Live is Chaotic

Humans go from A to B, decide C instead of D and see only things near to him. CHAOS explains, what is around us and what is the consequence, if we choose a way we shouldnt. CHAOS thinks further and offers relations, we cannot see right now. We walk from A to B and now, we see things, we never saw before.

Who We Are

Vision and Values

We are people from all over the world having the same vision. Get control about tons of data and show, what we can learn, if we have the right tool's to get into a new data matrix. First Step is getting the data-matrix up and running, second, put billions of data there and join things together. Than build a GUI and than ... try to make it autonomic. OK, we are on step 2, but starting now on 3, but everyone of us knows, step 4 is the checkpot.

CHAOS is nothing else than an entity, having his attributes and values + meta informations like country, language, organisation and division. On top of this, the data model put this cube of current and historical dataset of each entity into another cube of time and location ranges and of cource, if a cube streams during time and locations, it crosses other cubs, calling relations. Thats it. Not really, because the attributes are the tricky part.

Humans give everything a name, but this name is not uniq. Humans like to modify values and now, values are also no more longer uniq. The attribute engines joins attributes and values from each cube together. Right now, this is a manuel task. Additional each Key:Value pair has his own time and location stream. All this streams of cubes and pairs allow us to get a real overview and show relations, we not saw before.