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Data science is a holistic discipline that implements scientific methods, processes, and systems to gain insight from the acquired data. Companies now realize that this data is a critical corporate asset, so it undergoes systematic computational analysis with analytics. As a result, data science and analytics coupled with Artificial Intelligence (AI) and Machine Learning (ML) are becoming fundamental for companies to keep pace with the competition and succeed in the marketplace.

As data and analytics become the centerpiece of enterprise strategy and investment, the challenge is to use data science, machine learning, big data, AI, and IoT to make the environment completely digital. Consequently, the gathered business intelligence is computed with corresponding business data to determine actionable insights.  

Arbour Group’s Business Intelligence Services with Data Science and Analytics 

At Arbour Group, our approach and process to Data Science and Analytics are using systems, algorithms, practices to extract information and insights from structured and unstructured data. We use analytics and machine learning to help users make predictions, enhance optimization, and improve operations and decision making.  With your defined business objectives, we assist in driving business results and make informed decisions. Arbour Group can develop models and perform an analysis of data trends that forecast future predictions under numerous possibilities.  We can also anticipate where to utilize maximum data to provide actionable results.  This may include but is not limited to the following: 

  • Predictive Model and Dashboard Development
  • Data Classification & Pattern Detection
  • Recommendation engines
  • Visibility and Big Data analytics
  • Technologies utilized include Python, SAS, R, Tableau, and Qlik
  • Biostatistics and Bayesian modeling

Arbour Group has the capabilities to work with your predictive model development, biostatistics, Bayesian statistical modeling. We have the knowledge to work with cross-functional teams that include expert data scientists, programmers, engineers, and business analysts that can extend across business units.  As a result, these methods deliver digital innovation by introducing the potential to change long-running traditional business models. 

For data science to be useful, its comprehensive development must not only sustain conventional analytics, but it must also operate in harmony with modern applications. In some instances, automated AI technology is implemented with Data Science to increase analytical effectiveness.  Arbour Group’s approach means that data science practice must evolve beyond routine and monotonous duties. The use of automation can optimize a team’s time and operational effectiveness.  

To find out more information regarding Arbour Group’s approach to Data Science, Analytics, and Business Intelligence, contact us today!