Retail & E-commerce
North America
End to End Project Lifecycle Management
The company highlighted multiple challenges in its data management pipeline when we first sat together for a discussion. Here are the key issues we identified:
Disjointed Data Systems
The company struggled with fragmented data from various systems, including Shopify for online sales, Salesforce and Microsoft Dynamics for CRM, and SAP/Oracle SCM for inventory. This made it hard to get a unified view of their operations.
Slow Reporting Processes
Reports took several days to compile due to data being scattered across systems. This delay impacted their ability to make timely and informed decisions.
Inventory Management Issues
Frequent stock-outs and overstock situations created operational inefficiencies and led to customer dissatisfaction, affecting overall business performance.
Customer Insights Gap
Data from loyalty and rewards programs was not fully utilized, limiting their understanding of customer preferences and engagement.
Lack of Actionable Visualization
Without a centralized dashboard, tracking key metrics like sales, inventory levels, and customer behavior was a challenge, hampering real-time decision-making.
Our experts implemented a centralized data warehousing solution integrated with Power BI to address the client’s challenges. Key steps included:
Unified Data Infrastructure
Consolidated data from e-commerce platforms, CRM systems, inventory systems, and loyalty programs into a centralized warehouse.
Data Integration and ETL
Streamlined data ingestion using Azure Data Factory, ensuring real-time synchronization and consistency.
Advanced Reporting
Deployed automated dashboards in Power BI for quick insights into sales, inventory, and customer behavior.
Predictive Analytics
Implemented demand forecasting to optimize inventory levels and reduce inefficiencies.
Secure Governance
Enforced data security using Azure Role-Based Access Control (RBAC) and encryption protocols.
Azure Data Factory (ADF)
Purpose: Orchestrated and automated ETL (Extract, Transform, Load) processes by connecting to various data sources, transforming the data, and loading it into a centralized data warehouse.
Key Data Sources:
Data Storage and Processing Layer
Purpose: Stored and processed unified data for analysis.
Key Components:
Features:
Data Transformation Layer
Purpose: Prepared data for analysis by ensuring it was clean, consistent, and actionable.
Tools:
SSIS/Synapse Pipelines: Used to remove duplicates, normalize formats, and aggregate data.
Key Steps:
Data Analytics and Visualization Layer
Purpose: Enabled decision-makers to derive actionable insights through dashboards.
Tool: Power BI was used for visualizations and reporting.
Dashboards created for the client:
Data Governance and Security Layer
Purpose: Governed and secured the data while ensuring compliance.
Key Features:
The centralized data warehousing solution transformed the client’s data landscape, enabling real-time analytics and seamless decision-making. With improved reporting, inventory management, and customer insights, the client is now well-equipped to drive operational efficiency and strategic growth.
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DataToBiz is a good choice for someone who wants a partner who understands the product journey, requirements, and delivery expectations. They have the experience and agility to understand what’s possible and deliver to the client’s expectations. They‘re really passionate people, and they know what they’re doing!
We’re impressed with DataToBiz’s professionalism, dedicated support, and consistent follow-ups. Their team maintains clear communication through online meetings, ensuring a smooth and reliable collaboration.
A solution like this is a good fit if your teams spend more time collecting and reconciling data than acting on it, if reports from different departments do not match, or if decisions depend on delayed or manual reporting. It also fits when your data is growing in volume or sources, and your current setup struggles to keep up.
DataToBiz starts with a discovery call to review your goals, data sources, and reporting gaps. You get a clear view of the expected outcomes, effort, and timeline before any commitment.
Yes. Every solution DataToBiz delivers is configured around your industry, business processes, and existing data environment. The team assesses your current systems, data quality, and reporting needs first, then designs a solution that works with what you already have instead of replacing it. This applies across industries such as manufacturing, retail, healthcare, finance, and logistics, and across setups ranging from legacy databases to cloud data platforms.
DataToBiz works across the major analytics, cloud, and data engineering stacks. For BI and visualization, this includes Power BI, Tableau, and Looker. For cloud platforms, it includes Microsoft Azure, AWS, and Google Cloud. For data warehousing and processing, it includes Snowflake, Databricks, and SQL-based databases. Data sources include ERP and CRM systems, spreadsheets, APIs, IoT and sensor data, and third-party applications.
If your stack includes a tool not listed here, the team can assess compatibility during discovery.
Most projects with DataToBiz take from a few weeks to a few months. The timeline depends on how ready your data infrastructure is for the initiative and how many systems need to connect. Smaller solutions go live quickly, while larger programs roll out in phases so you see value early. After an initial discovery call, you receive a timeline with clear milestones.
Security and governance is part of the plan from the first conversation. DataToBiz works within your security policies and follows the regulations that apply to your industry. The project usually Access stays limited to the people who need it, and confidentiality terms cover the engagement from kickoff to handover.
The work does not stop at go-live. Your team gets a proper handover and guidance on using the solution, and DataToBiz stays available for questions and improvements. The business impact of the project is measured against the goals set at the start, so you can see exactly what changed for your company.
