See your customer journey through all your company's contact points, analyse their behaviour and preferences. Get suggestions on how to deliver greater value to your customers and personalize their interaction with your company.
Analyse your entire sales history, predict future behavior. Understand the impact of promotional actions and identify cross selling opportunities. Assess the power of your online channel and social networks in driving new business.
Evaluate the performance of your business processes with indicators designed specifically for this purpose. Translate strategic and tactical objectives into operational targets, measuring their activities' KPIs and KRIs.
Automate financial and management reporting, even if you use different systems in your company. Make bottom-up budgets and evaluate your execution. Track financial ratios of liquidity, profitability, leverage and efficiency.
Follow all stages of your production industrial processes in real time. Identify key bottlenecks and points of failure to implement operation improvements.
Identify and anticipate problems in your logistics chain, analyse evolution of stocks of goods, raw materials and finished products. Get suggestions for relocating resources or stock .
Centrally analyse the state and performance of your company's Human Resources. Evaluate macro trends to introduce improvements or anticipate training or recruitment needs.
Monitor access and utilization of your systems, integration status and the health of your infrastructure. Receive alerts and anticipate usage spikes to be able to provision resources in advance .
Automated data channeling and enrichment processes based on ETL (Extract, Transform & Load) and ELT (Extract, Load & Transform) methods.
These processes apply business rules, invoke Data Quality processes, and reorganize information into a format suitable for exploration in a central repository.
Enterprise Data Warehouses are repositories that constitute a single source of truth about your company's activity. They are the result of joining multiple data sources and applying business rules for consistent and facilitated analysis.
Data Lakes are highly scalable repositories storing petabytes of data at low cost. It is possible to store information in virtually any format (e.g. image, video, text files) for further analysis.
Massive information processing and storage technologies that take advantage of distributed computing to grow unrestricted with your business.
Factors such as relatively low storage cost, high configuration and data types flexibility open up new opportunities to take advantage of all the data you have.
Machine Learning (ML) is a subset of Artificial Intelligence (AI) that enables the learning and improvement of systems based on experience. They are a part of augmented analytics and make use of statistical methods to predict and prescribe actions based on data patterns.
Some use cases include:
Systems that enable ad-hoc exploration with click-and-drag-style interactions as well as the possibility of extending data models with additional information, simple data cleaning & wrangling tools included in the software.
High autonomy and adaptability in building and adapting interactive dashboards, enriching business models with departmental data and distributing the analysis with colleagues and partners.
Interactive dashboards and reports where you can quickly view your business data and make decision making easier.
These dashboards, customized to your needs, allow you to automate the process of collecting and sharing information to support the strategic and tactical management of your operations.
B2F has extensive experience in dealing with various markets and implementing BI systems, and can therefore support you with:
B2F's training plans are based on real case studies, and reflect B2F's experience in Business Intelligence projects.
Leading BI and Analytics tool that makes all your organization's data simple and intuitive to view and analyse
Self-service BI and exploratory data analysis tool with great governance features
Self-service data visualization platform with excellent data preparation and transformation features
The Microsoft Azure cloud platform has a wide offer and allows you to take full advantage of the various tools in the Microsoft ecosystem such as Azure Synapse Analytics
Google cloud provides you with numerous serverless resources designed especially to deal effectively with large volumes of data and information such as Google BigQuery
Considered one of the most competitive and complete stacks, with an excellent database engine and tools for data processing and analysis
One of the most recognized database engines worldwide with excellent robustness and fine-tuning capabilities for your use case
Highly scalable open-source relational database engine available on several operating systems and with over 30 years of history
One of the most well-known and complete analytical engines used in the processing and analysis of big data, and with extensive application in the context of artificial intelligence
One of the most used frameworks in distributed computing, being composed of several components, such as the HDFS file system, MapReduce and the resource manager YARN.
Highly scalable platform for processing and orchestrating integration processes, used to build a Lakehouse (a cross between Data Warehouse and Data Lake)
Data Factory and SQL Server Integration Services (SSIS) are, respectively, Microsoft's cloud and on-premises data integration orchestrators.
The technology used must be the one that best fits your situation.
For this reason, we assess which technologies you already have and whether they fit your requirements.
We give preference to your existing technology, suggesting without vendor bias a new architecture if the current one does not meet thedefined objectives.
We use cookies from third party services for marketing activities and to offer you a better experience. Read about how we use cookies and how you can control them by clicking "Privacy Preferences".