This purpose led us to create a methodology that helps companies reduce costs, improve efficiency, identify innovation opportunities and improve the productivity of our clients’ operations.
- Detects key aspects of the operation of the business from the analysis of large volumes of data.
- Take advantage of the value of analytical models to automate decisions.
- Direct and design the methodology for the implementation of AI solutions.
- Reduce the loss of business opportunities due to ignorance of the value of data.
At Sofka Technologies we’ve helped several of our customers to establish Big data solutions based on organizational needs, among the strategies we use are:
We’ve created the ideal architecture definition taking into account the customer’s choice of technology and its implementation in platforms such as Azure, AWS and GCP.
- Artificial intelligence research.
- Feasibility of AI projects.
- Opportunity analysis.
- Benchmark (Market Comparison).
01
Solution ideation according to business needs.
02
Choosing the right machine learning framework.
03
Choose the machine learning algorithm.
04
Tune the algorithm and data to get the most accurate predictions.
05
Identify training data for machine learning models.
06
Model training and generation of predictions in production (inferences).
07
Integrate machine learning models into business applications.
08
Return operational models that have large-scale performance in production.
01.
Solution ideation according to business needs.
02.
Choosing the right machine learning framework.
03.
Choose the machine learning algorithm.
04.
Tune the algorithm and data to get the most accurate predictions.
05.
Identify training data for machine learning models.
06.
Model training and generation of predictions in production (inferences).
07.
Integrate machine learning models into business applications.
08.
Return operational models that have large-scale performance in production.
- Data sources Identification, understanding their structure and context.
- Selection of storage systems, access policies and information consumption.
- Implementation of the solutions infrastructure, defining the access rules and maintenance policies.
- Sources consolidation and unified display of information.
- Establish information governance policies.
- Prioritization of data sources based on relevance to the business.
- Discover the data model as well as the information risks involving key areas of the company.
- Define a maintenance plan, estimation of resources and associated costs.
- Design a clear view of the information in a structured way to be used in business analysis.
- Detection of determining characteristics and relevant information.
- Find meaning in information and transform it into useful data.
- Hypothesis testing and validation of current business data.
- Information extraction aligned with the business strategy.
- Design a clear view of the information in a structured way to be used in business analysis.
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Duberney López – Líder de Inteligencia Artificial e Inteligencia de Negocios
