DataCellnet Q&A

Why DataCellnet?

Why not? If physical infrastructure limitations previously hindered new types of technologies, there is now more than enough capacity to support new ways of processing information. This means breaking away from known mechanisms that have been applied until now.

Is it another database?

Not just that. It is technology that allows working with different database engines in the market with performance much superior to what those engines can provide on their own. And when these cannot deliver the expected performance, we have our own engine.

What is a mesh of indices and route models?

Information handling is done from a mathematical point of view, for example, a+b=c. However, the way humans process information involves a context. Why am I doing this calculation? For whom and what am I doing it? What will I do next with the result? In DataCellnet, there are no mathematical calculations. Not even logical ones. There are paths through which information flows. Some paths are longer and others are shorter. With the DataCellnet engine, these paths or routes can be 'processed'.

What is the difference with graph-based database engines?

A graph represents the relationships that exist between data. Once defined, you work with these relationships. In DataCellnet, there are no relationships, nor do you know in advance what line the data will follow. The only thing you know is where you come from, where you are, and what possibilities you offer the data to jump forward. Therefore, there is a significant difference between processing graphs that follow a serialized and predefined line and DataCellnet, which at each point of the route has a new tree of routes to choose from.

So, is it a model of 'tree of trees'?

It has a similar taxonomy but without limitations. What happens is that in such a structure at each point where a branch bifurcates, we are accustomed to seeing a binary path. However, the DataCellnet engine allows at each point of bifurcation to apply a tertiary logic where there are more than two possibilities to choose from. In fact, there can be 'n' possible alternatives.

What benefits are achieved with DataCellnet?

The ability to synthesize the logic of why, for what purpose, when, for whom, and not just the outcome.

That is, to synthesize the complexity of the relationships that arise in models of very high volume with high relational complexity depending on the context. It is for this reason that the logical structure on which DataCellnet is based natively incorporates the ability to compute time.

And therefore, the ability to compute hundreds of possible routes and issue a digitally valid conclusion.

What in a traditional information system requires hundreds of lines of programming and computation, in DataCellnet is replaced by route processing.

How is it possible to achieve much faster responses than other engines in contexts like the previous ones?

It's important to remember that DataCellnet does not process data; it processes indices to the data. These indices are precisely what are used to create the processing routes. DataCellnet is a vast three-dimensional mesh of indices that on one hand point to the concept they represent, and on the other, they connect to other indices. DataCellnet uses dictionaries to encode concepts and incorporates them into its core. Then, the data are constructed with indices to these concepts, drastically reducing the processing and data querying times. It is precisely because of this computing system that it can solve extremely complex queries in real-time.

What is the level of difficulty in using DataCellnet?

It is extremely simple. It is true that there is a change in the way of thinking and one must get used to moving through a computing space that allows establishing multiple relationships without limitation. But the type of results achieved is totally addictive. Once you see what the engine allows, there is no turning back. You realize the change it represents compared to traditional information processing technologies. A business consultant designing the model does not need to worry about the technology's limitations when building business concept relationships.

What level of productivity is achieved from the point of view of digitalizing business models?

This is where DataCellnet begins to show its power. Typically, whenever we face a new challenge, technological structures are designed, database models are repeated, and ad hoc informational systems are generated. What if there was a layer to define the informational model independently of the data model structure that allows for dynamic changes? A fundamental value of DataCellnet is that the routes are alive; they are reused in new projects and grow in length and breadth. The routes are the assets of the architects using DataCellnet. They are not even part of DataCellnet itself. DataCellnet processes them, but the routes are created on demand. Some during the design phase, others during execution, and others are generated by auto-learning processes. The route libraries are the most valuable asset and are capable of changing the way of responding to the same data simply by changing the model.

What level of consistency does the technology provide to the data it handles?

DataCellnet stores in a truedataware database the indices without relational information. These indices are aseptic. They do not even know what they are. This information is audited and is equivalent to a physical data point in a database. Later, on that mesh of indices, the result is interpreted differently depending on the active model. This is one of the tremendous advantages for understanding situations requiring broad-spectrum decision-making and strategic analysis.

How can it work with existing datalakes?

An initial indexing process is performed to create DataCellnet indices over the existing information. The interesting thing about working with existing data is that you do not try to index all the information, but choose the most important fields and index them. From this data, you create new types of relationships with DataCellnet.

So, if we had to define DataCellnet, we would say that...

DataCellnet is the first cell-oriented informational structure. How many times have we seen data systems where the address or phone field appears multiple times in different tables when the address cell is defined? In DataCellnet, it exists only once. All indices to all possible occurrences of addresses reside in a single cell. This greatly simplifies the designs of operational business models. We have found that with only 20 or 30 cells, we are capable of creating business information systems that would be very complicated with traditional systems.

It seems like a system that is very oriented towards analysis, can it be used in operational environments?

DataCellnet starts from the idea that by digitizing operational processes with the indices we use, we can have accurate, up-to-date, and real information with which to perform analysis and query systems. DataCellnet also allows that within an information route, one point can be operational and the next one for consolidation. The richness of the system is that it serves both scenarios, which does not mean that the operator navigates the same routes as the analyst, even though everything resides in the same DataCellnet. The core that processes all of DataCellnet is encapsulated in just 11MB. This allows DataCellnet to be used on mobile devices, in the firmware of IoT ecosystem devices, and of course, in cloud models.