Automated processes can mean greater operational efficiency, but also reduced time to market, better customer experience and a more personalized response, in addition to lower structural costs.

At BI4ALL’s AI & Data Science team, we frequently tackle challenges that require a multidisciplinary mindset to overcome. One recent example was a solution that pulled us into the much-dreaded realm of concurrency computing with computer vision mixed in for good measure.

When is the best time to launch the new product? What is the most effective marketing strategy for the next semester? Is this a good investment and when will the company get a return? These are some of the many questions that most concern marketers.

Undoubtedly, technology has evolved to offer new and innovative ways to interpret, systematize and present data, and new Artificial Intelligence tools, including Machine Learning and Deep Learning, bring enormous added value to the business, increased productivity, improved customer relationship, time and money savings.

With the uncertainty of recent times, companies felt the need to realign strategies, reduce costs and increase operational efficiency, in order to keep the business healthy and competitive.

Previously called Azure Data Warehouse, Azure Synapse Analytics is a complete platform for analyzing Data Warehouse environments and Big Data systems Synapse Analytics brings together on a single platform several technologies such as SQL, Spark, Integration Pipelines and ETL / ELT. All components have a strong integration with many other features of the Azure environment.

It is time to align strategies, optimize performances and take the next step towards success, and data-driven cultures, or take the risk of not succeeding in the new paradigm, which is beginning to reveal and foresee itself more, and more challenging and demanding.

Market Basket Analysis is an Associate Rule Mining technique widely used by many companies with interest of finding relationships between products that are in their stores.

If Artificial Intelligence was already present in many areas of society, particularly in companies, being the most visible aspect the support to customer service through chatbots and voice assistants, today organisations have extended the adoption of AI solutions to several areas, allowing them to centralise and access critical information for decision-making.

Data Analytics and Artificial Intelligence solutions allow, for instance, essential business indicators to be identified, monitored and analysed in detail, as well as market trends and customer needs.