Thinking outside the box and taking advantage of unprecedented opportunities is the best way to ensure your company's success in the strategic arena of tomorrow.Contact us
Regardless of whether you want to get to know your customers and markets better and subsequently increase sales or whether you want to maximize the efficiency of your work processes and save costs, we will give you the appropriate advice after in-depth analyses of your internal and external context. Our experienced data scientists in our Data Practice department identify and analyze your company's data streams, identify digitization gaps, develop appropriate recommendations for action and develop Artifical Intelligence algorithms to optimize processes, storage, operations and structures with accuracy in mind at all times/stages. We are efficient, innovative and user-oriented.We engage with colleagues in oApplication Practice department to unlock the key elements of these processes.
Centralizing all the data your company generates and processing it in a scientifically sound manner enables methodical and strategic use of the data. With the help of the implemented structures, the potential of the data is fully exploited and contributes significantly to the achievement of your business goals.
The basis of all optimization processes is the comprehensive knowledge of the enterprises database and the possible uses that can be made of it. Using in-depth analyses of inventory data, our data scientists identify optimization potential and make processes in your company visible.
Automating processes to increase the efficiency of the company is a challenge, especially for medium-sized companies. Thanks to data collection, data analysis and the implementation of strategic data use, this challenge becomes manageable. Today. And in the future.
Whether it's the merging of data sources, analysis and transparent controlling or conclusive visualisation in real time - with a customised software and digitalisation solution, you can unlock the full potential of your company and take advantage of the opportunities that digitalisation and automation offer your business.
A data warehouse acts as a central platform that brings together different data sources from different parts of the organisation. It enables data to be structured and stored consistently, regardless of its origin or format. Integrating data from different sources creates a comprehensive data set that can be used for analytics and AI applications.A key benefit of a data warehouse is that it helps organisations manage the entire data lifecycle. From data collection, to data transformation, to making data available for analytics and AI models, a data warehouse provides a solid foundation. It enables users to run complex queries to gain valuable insights from the data and make informed decisions, especially when using AI. AI models require a large amount of training data to make accurate predictions. By bringing together data from different parts of the business, organisations can generate a rich data set that enables robust AI model development. The data warehouse provides a stable foundation for storing and accessing this data, enabling the efficient use of AI algorithms.
In addition to a data warehouse, a datalake can also be a valuable addition. A datalake allows you to store raw data in its original format without having to structure it first. This is particularly useful when organisations want to collect large amounts of unstructured data, such as log files or social media feeds. A data lake can act as a complement to the data warehouse, providing the flexibility to store different types of data and transfer it to the data warehouse as required.
innovative approaches we use, including leading technologies such as Data Bricks. These include data warehouse solutions that provide a reliable and scalable foundation for data management. The integration of a delta lake ensures high-performance data processing that seamlessly integrates and manages both structured and semi-structured data.
Azure Databricks enables Limendo to incorporate advanced analytics and machine learning into data processing. This platform provides a powerful environment for data science, enabling the development and implementation of complex models to predict and optimise business processes. The connection to Azure Event Hub ensures that real-time data is captured and processed efficiently, enabling immediate response to changing market conditions.
Another important aspect of Limendo's technology suite is the OLAP (Online Analytical Processing) layer, which supports multi-dimensional analysis of data. This allows users to gain deep insight into the data and perform complex queries in real time. The ETL (Extract, Transform, Load) processes are streamlined by Azure Data Factory (ADF) to extract, transform and load data from disparate sources into the data warehouse. This ensures high data quality and consistency.
In addition to the core components, Limendo benefits from a wide range of cloud services that are seamlessly integrated into the architecture. This ensures flexibility and scalability, as resources can be adjusted as needed. The choice of different cloud services allows Limendo to select those that best fit the specific requirements of each project.
Overall, the data warehouse is an essential component for companies that want to use their data assets to develop AI applications and make better business decisions. When it comes to aggregating and structuring data in a central data warehouse and making it available for the use of artificial intelligence, Limendo GmbH, based in Bolzano, South Tyrol, is the right partner at your side. With its ability to implement complex data-driven projects, Limendo helps companies unlock the full potential of their data and make data-driven decisions that drive business success.
The complete Business Intelligence package: Data Warehouse, Power BI, Forecast and Analytics for perfect mapping of all business processes and a solid data basis and visualization.
Using the latest technologies, a data pool is created, fed from a wide variety of data sources. Data from all inventory systems has been congruently merged and is now visualized using MS Power BI. The system is also connected to 4 different machine learning models: Sales Forecast in existing branches, Sales Forecast in new locations, Quantity Forecast and Staff Planning. Ongoing implementation over a period of 2 years using various technologies: Databricks, Datalake, Pipelines, Python, SQL, various ML models.
The innovative controlling software by Finanzwerkstatt. For meaningful reporting in the simplest possible way: by clicking one button.
The Microsoft-certified, client-capable Excel add-in for a quick overview of current company figures is equipped with interfaces to the leading ERP systems on the South Tyrolean market and enables automated display of key figures without the need for extensive training. Anytime and anywhere.
wingX was developed in an agile manner over a period of about 1 year and constantly refined. The software was implemented in the MEAN technology stack and subsequently expanded to include AI-based sales forecasting - based on Python.