• Industry


  • Project Type

    Power BI, Big Data, Azure, Business Intelligence

The challenge

  • The retail client, a distinguished footwear retailer in the United States, faced challenges with the existing sales reporting structure.
  • Monthly static reports were generated manually for various workstreams, hindering quick decision-making.
  • The generation of gross sales reports was challenging due to unstructured data, and the traditional IT infrastructure struggled to maintain a central repository for the constant influx of information from different regions.
  • The use of tools like SQL, SAP, and spreadsheets for data sorting hindered organizational growth

The solution

  • Power BI consultants utilized Microsoft Power BI to deliver visually appealing and interactive dashboards, enabling the client's operations staff to become more self-sufficient.
  • To optimize processing time and save costs, Azure SQL Server Database service was scaled up as needed during data processing.
  • The solution included a wide range of data analytics capabilities, such as ETL, data cleansing, filtering, and deduplication.
  • The platform handled unstructured and structured data while providing futuristic insights and visualization.
  • A cloud-based predictive analytics platform was built using Node JS, React, Mean JS, Firebase, and Elastic Search to detect and forecast patterns in real-time across big data sources, including social media analytics.
  • Additionally, a platform was developed for customers to access, explore, and visualize their Hadoop data using full-stack technologies like Node, Angular, React, React Native, and ELK.
  1. Consolidation of massive data sets and streamlined data preparation.
  2. Accelerated production of sales reports and ad hoc analysis with Power BI.
  3. Improved communication with sales staff in multiple regions through shared interactive visualizations.
  4. Development of time-intelligent reports based on actual and target data.
  5. Rapid generation of business intelligence gross sales statistics based on customer actions, product demand, and brand recognition.
  1. Implement an on-premises solution for sales reporting.
  2. Generate rich iterative and precisely formatted reports.
  3. Visually explore huge data and quickly discover patterns.

Project outcomes

  1. Improved self-sufficiency of operations staff with visually appealing dashboards.
  2. Optimal processing time and cost savings through Azure SQL Server Database scaling.
  3. Enhanced data analytics capabilities, including ETL and data cleansing.
  4. Cloud-based predictive analytics platform for real-time pattern detection.
  5. Full-stack platform for customer data access, exploration, and visualization.

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