The Business Intelligence projects we propose aim to support strategic business decisions. We refine and simplify the processes of data discovery and data visualization to identify phenomena, patterns, and anomalies, enabling the company to implement strategies with data-driven approaches.
The quality of data can improve business performance.
The value of data
In 2023, the Analytics market reached a value of 2.85 billion euros, registering an 18% increase compared to the previous year and a 68% increase compared to 2019 (1.7 billion), with an average year-on-year growth rate of 13%. This investment is justified by the benefits that companies can obtain from these technologies.
Business decisions are more informed, resulting in increased revenues. Data quality can, in fact, improve business performance in several ways, allowing companies to:
Identify new market areas, acquire new customers, optimize sales prices, and increase customer retention;
Speed up decisions and stay ahead of the competition;
Highlight results, trends, and anomalies to support optimal planning;
Improve business processes and operational procedures;
Immediately understand information, thanks to the graphical representation and interactive approach of data visualization systems.
Beta 80 offers BI solutions based on two key technologies:
Microsoft Power BI: With the self-service BI option, individual business lines and users can quickly define, produce, and modify reports and dashboards. With the IT Managed mode, report generation is entrusted to the IT team.
Qlik (Qlik View/Qlik Sense): An IT Managed BI solution, where the IT department is responsible for producing all reports.
Machine Learning: intelligent support for business decisions
To fully exploit the potential of data, it is necessary to transform it into valuable information that can support business actions and initiatives. Machine Learning allows for the automatic and intelligent analysis of data, generating knowledge and providing forecasts and operational recommendations.
Beta 80’s Data Value solutions use Machine Learning algorithms to:
Identify phenomena, anomalies, and hidden patterns in the data through interactive and intuitive data discovery and data visualization systems;
Predict future scenarios and possible outcomes using predictive and prescriptive models based on advanced algorithms;
Act effectively and promptly by leveraging the information and recommendations generated to optimize processes, strategies, and performance.
Data Value: Beta 80's approach
Beta 80’s Data Value solutions support companies in various areas of business operations: customers and market (industry segmentation, behavior analysis, customer retention, identification of sales areas); production (Industry 4.0, monitoring of plants and machinery, maintenance optimization); competition (data comparison, market share simulations); internal organization (performance monitoring, customer management optimization).
Beta 80 assists companies through a progressive collaboration process:
Mapping the previous and current situation;
Defining objectives and metrics;
Choosing and implementing the most suitable tools;
Evaluating results;
Providing continuous support.
Using Python, Beta 80 offers a specific data analysis and decision support service.
Methods and tools for implementation
To manage, integrate, and activate the data on which Business Intelligence, Machine Learning, and Artificial Intelligence are based, it is necessary to set up an adequate infrastructure. Data Platforms are solutions that allow for the creation of a unified and comprehensive view of data from various sources, ensuring scalability, flexibility, security, and governance. Beta 80 offers Data Platform solutions with Informatica, Microsoft Azure, Snowflake technologies, and Data Governance solutions with Informatica and Azure. These industry-leading technologies and solutions enable:
Efficient and reliable governance of large volumes of data thanks to the capabilities of the cloud and the functionalities of the Informatica platform;
Simple and fast integration, using Informatica for data replication, ingestion, and transformation to and from the cloud, and Snowflake for data storage and processing;
Intelligent data activation, using Informatica and Snowflake for information analysis and insight generation; Azure or AWS for Machine Learning and Artificial Intelligence.
