Data Science

Business Analytics & Machine Learning

Discover how technologies for data management and analysis, along with machine learningalgorithms, can enhance your ability to understand your business and market dynamics, delivering speed and accuracy to your decision-making process.

Official Partnerships
Bridge is an official partner of the main platforms in the market.

data science

Organizations face a wide variety of business challenges, which can be solved through an effective data strategy. A detailed understanding of the operational and financial indicators, while monitoring the effectiveness of the business process and tracking the entire customer experience and satisfaction cycle are examples of how Data Analytics initiatives can benefit your business.

We work to help organizations assemble their data strategies, governance mechanisms and architectural projects to deliver greater capacity to understand the present, predict future scenarios and strengthen decision-making skills with strategic insights.

We are experts in important market technologies for Data Science. Contact us to understand how we can help your organization.

business intelligence

Business Intelligence and Data Monitoring Panels

Use technologies to consolidate and analyze your organization’s data, projecting it onto dashboards.

data analytics

Data Analytics and Forecasting Future Scenarios

Rely on technologies to facilitate strategic data management and enable predictive analysis for your organization that will support decision making.

machine learning

Machine Learning

Use machine learning algorithms to create structures capable of interacting with data and generating strategic insights for your decision-making process.

Data Science Applications for Smart Organizations

To support your understanding of how these technologies can strengthen your business, we present examples of applications in some segments:

Smart Retail

Business Intelligence technologies enable centralized monitoring of sales, revenue, assortment and seasonality indicators, for example. Data Analytics platforms perform more structured data analyses, correlating and analyzing them to provide strategic insights. Predictive scenarios for purchase and replacement orders, crossing time, inventory turnover, among others help retail leaders to make more assertive decisions. Machine Learning algorithms accurately define the time to buy and replenish inventory, indicate the volume to be purchased, optimizing the cost of loss and excess, and define the best suppliers based on historical rankings.

Smart Client Relationship

Business Intelligence technologies let you monitor the satisfaction and engagement indicators of your client base, centralizing reports for marketing leaders and customer experience areas. Data Analytics platforms perform more structured analyses of consumer behavior, allowing you to compare multiple information sources and generate trends. Predictive scenarios for shifts in habits and preferences, for abandoning purchases or dissatisfactions are developed through technologies capable of operating large volumes of data – Big Data. Machine Learning algorithms accurately show when you tend to lose the loyalty of a certain type of client and support corrective decisions throughout the client’s journey.

Smart Healthcare Management

Business Intelligence technologies enable the monitoring of hospital occupation indicators, scheduling rooms and medication control. Data Analytics platforms support the identification of scenarios for optimizing the use of hospital resources and generate insights for logistics and medication purchases. Predictive scenarios for the evolution of epidemic conditions and demand for hospital services are developed using technologies capable of operating large volumes of data – Big Data. Machine Learning algorithms define actions to be taken to support spikes in demand for medical care and medication purchases.

Smart Supply Chain

Business Intelligence technologies enable central control of information on suppliers, times required for transportation and arrival of goods and other data related to product distribution. Data Analytics platforms support the identification of better distribution routes and the optimization of storage and transportation spaces. Predictive scenarios for inventory optimization and changes in the supplier network help managers to build more assertive strategies. Machine Learning algorithms define actions to be taken to increase on-time delivery and have suppliers operating within the agreed service levels.

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