BI - Business Intelligence

This project use case aimed to enable industrial reporting and geology reporting using data from plant historians, IoT sensors, MXDeposit, and other sources. The industrial reporting dashboard shows key metrics and KPIs related to the plant operations, such as production volumes, energy consumption, machine efficiency, and downtime. The geology reporting dashboard shows information about the geological samples and activities collected from different projects.

The goal of this project/use-case was to provide a centralized and automated dashboard for shipping data across different regions and plants. The dashboard combines data from various sources, such as SAP ECC, JWS, and VAS, and allows users to filter, drill down, and analyze the shipping performance and costs. The dashboard also includes audit data to track the changes in shipping documents and invoices. The dashboard is built using Power BI and Databricks, and leverages the Medallion architecture and the element61 Data Warehouse Acceleration Kit.

The purpose of this project was to migrate the existing SQL Server and SSIS components of the BIG BI data platform to an Azure Lakehouse platform, which is a hybrid architecture that combines the best features of a data lake and a data warehouse. The project aimed to improve the performance, scalability, flexibility, and innovation capabilities of the BI data platform, as well as enable new use cases for reporting and analytics in various domains such as sales and marketing, finance, ESG, EHS, and innovation.

The project involved assessing the current BI environment of both companies, using data sources such as SQL Server, Excel files, Power BI models and reports, and proposing recommendations for a future BI environment that would meet their business needs and goals. The project covered the back-ends & front-ends as well as identifying the benefits and challenges of implementing harmonizations of both platforms, such as improving scalability, automation, documentation, security and adoption, as well as addressing legacy, complexity and risk issues. The project concluded with a roadmap and timeline for the next steps.

The FAST Data Analytics project was a collaboration between element61 and Euronav to leverage a modern data platform architecture to handle the large and complex data generated by the sensors on board the vessels. The data platform feeds insights & data to FAST itself and uses Azure services such as Event Hubs, Data Explorer, Databricks and a Data Lake. The data platform also supports various use cases for different stakeholders at Euronav supporting data products on fuel optimizations & noon reporting. The data platform enables FAST to deliver real-time and accurate insights to the users and facilitate data-driven decision making.

The project aimed to design and implement a marketing data platform for Klépierre. A platform that enables Klépierre to collect, integrate, and analyze data from various sources, such as SAP, Salesforce, and a lot of marketing & footfall external providers, and to generate insights and reports for marketing and business decisions. The platform was built in this project on Microsoft Azure Cloud using Synapse Analytics, Data Factory, and Power BI, and follows the best practices and standards of data governance and security.

Azelis was been undergoing a digital transformation, migrating various systems to the cloud, including introducing Microsoft Dynamics 365. As the existing on-premise DWH of Azelis was facing performance, scalability, and flexibility challenges, and could not cope with the upcoming Dynamics migration, Azelis wanted to have a clear, well-thought, and future-proof architecture and data platform ready to enable self-service BI and advanced analytics capabilities for the business users.

As part of a broader modernization journey, Acerta is migrating their on-premise data warehouse to a Modern Data Platform in Azure & Databricks. This migration was done not as a project but rather tackling use-case by use-case as new requests & business projects came it. As element61 we guided this end-to-end stepwise migration and development of new use-cases ; all in a coaching & codevelopment set-up with the internal data team at Acerta.

In 2022, Acerta accelerated their digitalized back-end with the use of Service Now as back-end to serve customer better. Acerta uses both CSM, ITSM, HRSD and other modules in Service Now. This project related to make the Service Now data speak both in reporting: status of tickets, team efficiency & service KPIs as well as in data integration. All analytics on Service Now was done using a Modern Data Platform with Azure, Databricks & Power BI

As digitalization accelerates throughout Acerta in its interactions with leads & customers, personalization takes a growing importance. In this project element61 helped define the approach forward on personalization through all digital touchpoints available. The project was twofold incl. clarifying the personalization use-cases but also building an actual specific personalization Data Product API for website personalization currently in use.