Data Centric
Raw data is fundamental to any data analysis
The primary, original data collected from a source, which has not been transformed, aggregated or changed in any way
The raw data is primary –
the interface secondary
Kronometrix can help to
capture and consolidate
the right data
Data Recorders
Using data recorders, a simple to use, data collection package with a low memory and system footprint, supporting raw data, you can capture the right performance metrics from enterprise ICT, Industrial IoT to weather and environment devices.
Consolidate Data
It is easy to bind different data coming from one or many data sources in a single raw data file. For example different sensors can produce different metrics and parameters which can be consolidated as a single data message, and raw data file.
Central Repository
All raw data files are simple to consolidate and saved to a single central repository. This repository can play a very important role to any data analysis process, providing access to fetch, extract and aggregate data as needed for analysis and visualization.
Unstructured Data
Store and access data with no temporal structure, such as a document, a video and image or different log files. This kind of data can grow in size very quickly, requiring a scalable storage system and a RESTful API based applications.
Historical Data
Using a very efficient copy-on-write and compression mechanism, Kronometrix can keep track of long records of historical raw data on regular disks and storage systems. Such way you can keep years of raw data at the lowest cost.
Easy Access
There are different ways to access the raw data: interactive, by downloading a single monthly archive file, or individual raw data files for each day, and automated using a REST based API for other applications and systems.
No Vendor Lock-in
Having access to raw data means you have full control and unlimited possibilities to conduct your own data analysis process: Using Kronometrix exploratory raw data module, or using other software applications or systems.
Data Strategy
Any organization needs to have a data strategy to protect their own business and at the same time continuously improve. Having access to raw data will help you develop and improve the strategy and set clear key performance indicators in place.
Using a distributed
system architecture
Different Services
…
Private and Public API
…
Different Data
…
Rich Communication
…