Work on Project Management

We offer full integrated project management solutions to clients who wish to mandate Artecha for the execution of end to end data projects.
Artecha teams hold expertise on all the major database platforms, applications, frameworks, cloud services and best practices.

Our data-centric approach involves an in-depth look at organization’s data architecture so when we create a plan, it is based on client’s unique data management framework.

We can build, optimize and construct data pipelines to ensure that the data is properly received, transformed and stored. We have deep experience in creating and integrating APIs through ETL as well as developing dataset processes for data modeling, mining and production.


Work on Project Lifecycle

Both Cloud Computing, Business Intelligence and Machine Learning projects are highly iterative and are duly structured into different stages:

  1. Planning and Project setup
  2. Architecture & Design
  3. Setting up project codebase
  4. Data collection and labelling
  5. Building data ingestion pipeline
  6. Validating quality of data
  7. Model exploration (model stages mainly applying to AI and ML)
  8. Establishing baselines for model performance
  9. Model refinement
  10. Testing and evaluation
  11. Model deployment
  12. Ongoing Model maintenance
  13. Postproduction support


Work on Team Roles

A typical team for data management projects is composed of:

  • Data Engineers who build the data ingestion pipelines.
  • Machine Learning Engineers who train and iterate models to perform the task.
  • Software (Back End) Engineers who support by integrating machine learning model with the rest of the product.
  • Project Managers who keep track of the progress and make sure that it is delivered at the defined deadline.

Whenever a task is completed, our Data Engineers report to their PM and update them about the completed task and how much work is left.


Work on Project Methodologies

We lead the full project lifecycle in line with the client objectives adopting the most suitable standards:

  • Agile methodologies to prepare the roadmap, manage the teams and allocate the roles to the product roadmap
  • SPRINT plans to set up tasks, backlogs and deliverables
  • SCRUM frameworks for getting updates on daily basis from the Data Engineers, Data Analysts and Data Scientists who are working on that product.

We engage our clients directly with our Data teams so they can communicate and deliver their requirements clearly.