Industry: Pharmaceutical
Project: Clinical Data Platform Implementation
Technology: Oracle, GCP, Power BI
Scope: Audit and design of the data platform.
Expert Profile: Data Project Director / Data Product Owner
Industry: Agrifood
Technology: SAP, SalesForce, Oracle, Anaplan, Microsoft Cloud Tools (ADLS, ADF, SQL DB, Power BI)
Scope: Modernization of the data platform for the Finance department (Orders and Billing).
Expert Profile: Project Director
Results:
Consolidation of different data sources into single platform, improved data governance and delivery times of objectives by store and optimization of profitability
Industry: Bank (AML)
Technology: Actimize
Scope: Create a new type of manual alert base on supply chain management
Expert Profile: Business Analyst
Results:
SCM type of alert has been created on the RCM and users are able to create manually this type of alert
Industry: Bank (AML)
Technology: RCM, Oracle, Excel
Scope: Monitoring the volume of alerts per month and to realize data sanity checks
Expert Profile: Business Analyst
Results:
A dashboard to monitor the volume of alerts per month (in relation to the previous year) and assured data quality
Big Data Discipline is a systematic and comprehensive approach to managing, analyzing, and extracting valuable insights from massive and diverse datasets. It goes beyond traditional data processing methods, encompassing the three Vs: Volume, Velocity, and Variety, to harness the full potential of data in real-time.
Data visualization is a powerful tool that enables rapid comprehension, prioritization, and retention of complex data. It plays a vital role in the world of data by organizing and presenting a company’s strategic information effectively. The compilation and presentation of Key Performance Indicators (KPIs) carry essential messages, serves to unlock valuable insights, streamline decision-making, and drive success by effectively presenting and communicating data.
Providing reliable, objective, and usable data poses a significant challenge for companies. Master Data Management (MDM) involves efficiently structuring data through unique and standardized repositories to ensure data quality. Solutions such as MDM, Data Quality Management (DQM), Business Glossary (BG), and Enterprise Metadata Management (EMM) support and manage corporate data governance policies.
The Business Intelligence Information System is an essential component of every company’s information system. It collects, qualifies, standardizes, enriches, and aggregates ever-increasing volumes of raw data to deliver value-added insights. Today, Business Intelligence is adapting to meet new data challenges, driving changes in its approaches and solutions.
Data governance is the strategic framework and practices that govern the management, usage, and security of data assets within an organization. Just like any valuable asset, efficient data governance is necessary to extracting the maximum value from data. This involves implementing repositories like Master Data Management (MDM), managing data quality with Data Quality Management (DQM), and ensuring data traceability through Meta Data Management.
Implementing robust Anti-Money Laundering (AML) strategies has become a paramount concern for financial institutions. AML is an integral part of financial institutions’ core business, necessitating effective strategies to navigate complex financial data flows. Expert systems for monitoring, detection, and alert processing play a vital role in tackling attempted attacks and frauds by criminals seeking illicit gains within financial systems.