Analytics ● Cloud ● DataViz
your data engineering provider
Analytics ● Cloud ● DataViz
your data engineering provider
your data products and its market fit
Unstructured data analytics
Unstructured data analytics
Unstructured data analytics
If users can’t find it, it doesn’t exist.
- Collect semantic data
- Build upon knowledge graphs
- Enable users to augment your data
Spatial analytics
Unstructured data analytics
Unstructured data analytics
"A map is not the thing mapped". It's more.
- Surface your data with 3D and GIS
- Explore with image processing
- Layer and filter real world data
Real-time analytics
Unstructured data analytics
Real-time analytics
Data have a shelf life. Freshness matters.
- Speed up with stream processing
- Scale out with edge computing
- Gain insights on your flywheel
teams and products, built for scale
Teams
Outsourcing and team building – The K Parameter Company has delivered larger projects by scaling out to multiple teams. Those delivery teams were key to our success and that of our customers. Gain an insight on capacity planning, engineering management and delivery for specific projects: let's build your next team!
Processes
Agile processes across teams – As a technology provider, we deliver in increment of one to two weeks. If needed, we would adopt a continuous delivery workflow (CI/CD). We may follow the Scaled Agile Framework (SAFe) when we need to synchronize teams across several business units. In all cases, we use the user stories and Agile backlog as a unified view on how we progress toward completion.
Customer success
Solution engineering and technical writing – With scale comes some challenges. Our work does not stop once a product is in production, it often starts at that time. For instance we would work on solution engineering, customizing a product to fit specific user segments. A/B testing leads to further customizing. User documents, inline helps and training material all help with user adoption, the ultimate criteria of success.
Quality assurance
Metrics and testing – Quality assurance takes into account all aspects of data processing, from APIs data schema to data governance. Most projects run with two parallel work streams: one dedicated to data quality and the other to features. Technical metrics are used as input to scorecards as well as business KPIs.
what we work on
The engineering practice you will benefit from
Service offerings
The K Parameter Company offers data engineering services at each step of a data pipeline, across data acquisition, data processing and data visualization. It is specialized in data analytics.
- Unstructured data analytics consists in indexing raw data then transforming it into a NoSQL data structure called knowledge graphs.
- Spatial data analytics is centered on using image processing to transform images into either 3D assets or geo-tagged data.
- Real-time analytics is built around high-throughput of a stream of technical data. The pipeline starts with data pre-processing at the edge and data aggregation in the Cloud.
These services are helpful in starting a discussion about your specific needs. Contact us for custom work.
Technical stack
The following toolbox balances the risk of technical fragmentation and the benefits of best-of-breed tools.
- Amazon Web Services as a cloud provider along with Spark and Hive for NoSQL processes.
- Python for data processing and React for data visualization with the occasional C++ for speed.
- XML web services and micro-services for data integration and service architecture.
In past customer engagements, we produced native iOS/Android applications. More specialized work in 3D would use for instance WebGL while GIS work would use PostGIS along with JavaScript libraries. Last but not the least, devops work may use Docker and Jenkins.
about
History
A parameter is a way to set an expected outcome. When it comes to data analytics, the "k parameter" is used in classification techniques.
The K Parameter Company is a marketing reboot of Reality Frontier, operating with the same teams and processes since 2011. In its former iteration, it was focusing on 3D data. The company is now working on data engineering at large, from data pipelines to analytics solutions.
Work principles
The K Parameter Company is built upon the principles of grit and curiosity.
Grit allows us as a team to offer a safe and fast journey to our customers.
While building a product, curiosity will help us discover the user's true intent and correct course. Curiosity is at the core of what is called intentional design.
Principles are fulfilling a purpose through values to look up to. When hiring or deciding to commit to a job, the company as a business is placing people and planet before profit. Once committed, we will have no rest until delivering.
The idea of flow
Data is often described as a flow, with "pipeline", "data lake" and so on.
From the data we work on, the tools we use, even the processes we set up, everything is intended to evolved. It is with the same spirit that we work with our customer's changing needs. The products and teams we build are designed from the ground up to fit and evolve with the flow of our customer's business.