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Data Science and Analytics

Helping businesses in their quest optimal
growth patern

Grow your business at the pace of technology giants

Data science is not rocket science. Thanks to technology’s advances, you can put today’s most innovative technical solutions to work in your organization and solve complex problems using custom machine learning applications. Whether you want to upgrade your enterprise’s range of capabilities or maximize customer experience, you can unleash data science’s power.

With our in-depth experience in complex problem solving and business transformation, we at AltexSoft provide data consulting services to help companies derive value from raw datasets. Add competitive functionality for greater customer satisfaction, automate internal processes, or peer into the future – all on the bedrock of custom-built machine learning algorithms engineered on the foundation of your own data. Our machine learning experts will immerse themselves in your business processes and industry specifics to discover the main problems and offer solutions to them. Then, applying their skills in data analytics, machine learning models, and algorithms, they will help you decipher what data is telling you. In the end, you will be using a custom ML algorithm to continuously gather analytical insights and make data-driven decisions.

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Why is Predictive Analytics important?

Discover other use cases

Optimizing marketing campaigns

Predictive analytics are used to determine customer responses or purchases, as well as promote cross-sell opportunities. Predictive models help businesses attract, retain and grow their most profitable customers

Improving operations

Many companies use predictive models to forecast inventory and manage resources. Airlines use predictive analytics to set ticket prices. Hotels try to predict the number of guests for any given night to maximize occupancy and increase revenue. Predictive analytics enables organizations to function more efficiently.

Sales Forecasting

Sales forecasting is the process of estimating future revenue by predicting the amount of product or services a sales unit (which can be an individual salesperson, a sales team, or a company) will sell in the next week, month, quarter, or year