Eng
Eng
In addition to data-driven digital transformation, in enforcement part, ACT offers establishment of customer centric analytics and BI tools.
Our project management methodology is based on the golden standard of the industry (CRISP-DP – Cross-Industry Standard Process for Data Mining) which is actively applied when managing Data Science and Machine Learning processes and comprises of 6 phases:
BU (Business Understanding) |
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M (Modeling) |
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Understanding data processing goals and business tasks. |
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Analysis of data structure, quality assessment and description of exchange mechanism.
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DU (Data Understanding) |
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E (Evaluation) |
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Data organization, processing, formatting and unification. |
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Choosing the technique, building the model and generation of test design.
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DP (Data Preparation) |
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D (Deployment) |
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Evaluation of results, Alpha testing, planning integration in unified system. |
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Beta model testing, integration in unified ecosystem, development of monitoring and system maintenance plan and full deployment in the product.
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Together with standard process, project team is guided by agile approaches based of which works are divided into short-term sprints. Concentration on each spring makes gives a feeling of success to the team which boosts motivation and expectation towards the following stage. But in some cases, it happens that we go back if needed, we go back to the previous process and go through it again, more thoroughly. All of this is done in order to achieve the best results.
