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Case study

Digital Transformation of a Quartz Products Manufacturing Company5.0 rating5 Stars Rated On Clutch

0 %
Reduction in average lead time

Industry

Manufacturing & Industrial Engineering

Services Used

Business Intelligence (BI), Data Analytics, Data Centralization, Digital Transformation, Power BI, Predictive Analytics

Region

North America

Engagement Model

Managed Analytics

Function/Department

Manufacturing & Production, Procurement and Purchasing

About Client

  • A leading quartz products manufacturer for the semiconductor industry has two facilities located in the USA and Europe that serve customers around the world. The enterprise specializes in fabricating customized products as per the requirements of the clients.

Problem STATEMENT

  • Our client manufactured quartz products per their customers’ specifications and requirements. These products were pre-ordered by the businesses. This made it challenging to manage the tracking of the inventory and production.
  • The raw data was collected from multiple sources and there were no defined KPIs and definitions, resulting in discrepancies in different departments (data anarchy). Furthermore, the organization was highly dependent on tools for sourcing data and the enterprise data was not being leveraged to its full potential.

Solution

Since there was no proper system in place to manage and analyze data, we understood the challenges faced by the stakeholders and decided to assist them in transitioning to a higher level of data governance maturity.
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  • We discussed with the C-level stakeholders on discovery calls to understand the operations, objectives, and priorities of each department. We noted down the data collection processes that were being followed.
  • From the information gathered, we identified and resolved data discrepancies. Our experts defined the KPIs including categories and dimensions. Through continuous inputs and feedback from the stakeholders, we finalized the KPIs. Mockups of the dashboard were shared as well for any suggestions and changes.
  • We built real-time dashboards using Power BI for visualization of the data. Different dashboards were built for different functions of the business. The shareholders, customers, and employees could analyze and gain insights in real-time.
  • We developed artificial intelligence systems for product and material tracking, defect and disposition tracking, product quality tracking, statistical process control(SPC), failure detection and control (FDC), engineering data analysis (EDA), predictive maintenance, predictive yield/output, plant optimization, and more. This was incorporated into the manufacturing units, screens, and floors.

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Business Impact

  • The complete digital transformation enabled the organization to detect anomalies or defects in real-time. Ensuring that the products were of the desired quality.
  • The organization was able to save approx. $73k within a year of implementation of the AI and BI systems.
  • Switching from manual to automated reporting, the client saved more than 55 Hrs per month on analyzing collected information and making decisions
  • Operations in the various departments were streamlined with the centralized data engineering infrastructure that we implemented.

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Frequently Asked Questions(FAQs)

How do I know if a solution like this is right for my business?

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.

Can DataToBiz customize the solution for my industry and current data setup?

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.

Which tools, platforms, and data sources does DataToBiz work with?

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.

How long does a project like this take with DataToBiz?

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.

How does DataToBiz keep my data secure and compliant during the entire engagement?

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.

What support and results can I expect after the solution goes live?

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.

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