Evaluate InetSoft's Easy Big Data Analytics Path
There is a dizzying array of big data solutions in the marketplace, and it's a daunting challenge to evaluate them all, determine which fit together, and hire the expertise to assemble the puzzle pieces to deliver a useful solution. InetSoft aims to solve this problem with a unified, easier-to-implement application.
InetSoft offers a cloud-ready, fully scalable enterprise-grade platform that can access an existing big data source or use its own built-in, dedicated Spark/Hadoop cluster to turn an organization's data warehouses, relational databases, and almost every other on-premises or cloud-hosted data source into an integrated big data environment.
With its powerful data mashup engine, data can be transformed and combined on the fly. With its visualization designer, interactive analyses, management dashboards, and production reports can be created.
InetSoft's unified big data solution simplifies turning big data opportunities into actionable, self-service visual analytics.
Why InetSoft's Solution?
There are three primary reasons to choose InetSoft for an organization's big data solution:
1. Visual Analytics Is Included
There are plenty of big data platform technologies for storing and managing data lakes, but they don't include a data visualization layer. So an organization must separately evaluate, select, and manage separate solutions, potentially from more than one vendor. InetSoft's solution includes a very mature data visualization and reporting application that offers a visually-compelling interface for consuming big data by business users and data scientists.
2. No Big Data Expertise Is Required
In the build-it-yourself scenario, an organization must seek and hire expensive specialists experienced with various big data technologies. With InetSoft's big-data-in-a-box solution, no such expertise is required. IT staff with traditional data management skills can install a built-in, dedicated Spark/Hadoop cluster. InetSoft's advanced visual analytic engine will automatically configure and manage a big data cluster according to user defined visual analytics. InetSoft even offers the option to host its application in the cloud as a turn-key big data solution.
3. An Easy Growth Path to Big Data Is Included
Organizations that do not already have a clear big data challenge get the security of being able to grow into one over time. The concern of acquiring a dashboarding and analytics solution that cannot grow as an organization's data does is eliminated. Investment in the InetSoft solution can pay off now and in the future with a single easy-to-use platform.
Glass Microfabricator Adopts InetSoft for Streamlined Big Data Analytics
In the highly specialized field of glass microfabrication, precision and process insight are critical. Companies in this niche create micro-scale structures in glass for applications ranging from microfluidic lab-on-a-chip devices to advanced photonic sensors. Each project generates a wealth of data—machine performance logs, laser etch parameters, chemical etching metrics, and quality inspection results. Managing, visualizing, and acting on this data is essential not only for operational efficiency but also for maintaining quality standards that meet client expectations in biotechnology, optics, and electronics industries.
Recognizing the need for a more advanced analytics solution, one leading Glass Microfabricator recently selected InetSoft’s platform to simplify and enhance its path to big data insights. The company’s prior approach relied on fragmented reporting tools, manual spreadsheet analysis, and small-scale visualization solutions. While these tools served their purpose in early operations, they were increasingly inadequate for managing the volume, variety, and velocity of data produced across production lines and R&D experiments.
The Complexity of Glass Microfabrication Data
Microfabrication processes involve precise control over variables such as laser power, etching time, chemical concentration, substrate temperature, and environmental conditions. Each step is logged in high resolution, often generating millions of data points per week. In addition, quality inspection systems—including high-resolution imaging and interferometric surface measurements—add further layers of complexity. Combining these heterogeneous datasets for meaningful analysis is challenging but crucial for defect reduction, yield improvement, and predictive maintenance.
The Glass Microfabricator faced several pain points with its existing analytics tools:
- Fragmented Data Sources: Production, R&D, and quality systems were siloed. Engineers had to manually consolidate data into spreadsheets for analysis.
- Limited Visualization Capabilities: Previous tools could generate basic charts and reports but lacked the interactivity needed to explore multi-dimensional datasets.
- High Maintenance Overhead: Updating dashboards or creating new metrics required significant IT intervention, slowing response times for operational and client queries.
- Scalability Constraints: Existing solutions struggled with growing data volumes, resulting in slow report generation and delayed insights.
These limitations prompted the company to evaluate a more scalable, developer-friendly, and integrative analytics solution that could handle the complexity of modern microfabrication operations.
Why InetSoft Stood Out
The selection process emphasized three critical criteria: seamless integration with multiple data sources, high-performance visual analytics for large datasets, and the ability to embed dashboards into internal and client-facing applications. InetSoft emerged as the clear choice for several reasons.
- Data Mashup Engine: InetSoft’s platform can combine structured and semi-structured datasets from multiple sources in real time. Production logs, R&D experimental data, and quality inspection results could be unified in a single analytics view without complex ETL pipelines.
- Easy Big Data Path: The company valued InetSoft’s “Easy Big Data Analytics Path,” which simplifies access to large datasets without requiring extensive custom coding. Data queries are optimized to leverage underlying database performance, enabling rapid visualization of millions of records.
- Interactive Dashboards: Engineers and managers can now drill down into process parameters, isolate trends, and explore anomalies across multiple dimensions. For example, they can correlate laser etch parameters with microstructure defects, or examine how environmental fluctuations affect batch yields.
- Embedding and API Flexibility: InetSoft’s APIs allow dashboards to be embedded directly into internal applications and client portals, providing real-time insight without requiring separate tools.
- Performance and Scalability: InetSoft’s caching and query optimization features ensure smooth interaction even when working with high-volume sensor and inspection datasets, supporting both on-premises and cloud-based deployments.
Migration Process
The migration from legacy reporting and visualization tools was executed in stages. The first phase involved connecting InetSoft to existing SQL and NoSQL databases, production logs, and R&D experiment tracking systems. Developers leveraged InetSoft’s mashup engine to create unified views of key metrics such as etching consistency, laser power variations, substrate defect counts, and environmental monitoring data.
In the second phase, the team replicated critical dashboards from previous tools but enhanced them with interactivity and predictive features. Engineers could now filter data by batch, material type, or machine ID, and apply statistical models directly within the dashboard to forecast yield variations. This eliminated the need for offline analysis in spreadsheets or specialized statistical software.
The final phase focused on embedding dashboards in operational workflows and client-facing portals. Internally, production supervisors and R&D engineers could monitor real-time process metrics and receive automated alerts for parameter deviations. Externally, clients accessing their orders or custom fabrication requests could view performance and quality trends in real time, increasing transparency and trust.
Operational Impact
The adoption of InetSoft resulted in measurable operational improvements:
- Faster Insight Generation: Engineers reduced the time required to consolidate and analyze data from hours to minutes, accelerating process optimization cycles.
- Improved Quality Control: Real-time dashboards allowed early detection of anomalies, reducing defective batch rates and improving overall yield.
- Resource Efficiency: IT teams spent less time maintaining and updating reports, freeing resources for development of new analytics features.
- Enhanced Predictive Analytics: The unified data environment enabled the application of predictive models to anticipate equipment maintenance needs and optimize fabrication parameters.
- Client Transparency: Embedded dashboards in client portals provided real-time visibility into order-specific production metrics, strengthening client relationships and differentiating the company from competitors.
Developer Advantages
For developers and engineers, InetSoft delivered several key benefits:
- Reusable Templates: Dashboard components and widgets could be reused across different datasets and projects, reducing development time for new visualizations.
- Custom Scripting and API Access: Developers could extend functionality with JavaScript and REST APIs, integrating advanced analytics features or custom visualizations.
- Version Control Integration: Dashboard definitions and data models could be managed through standard CI/CD pipelines, supporting agile development practices.
- Security and Governance: Role-based access ensured sensitive process data remained secure while allowing controlled access to clients and internal teams.
Strategic Benefits
Beyond operational and developer efficiency, InetSoft enabled strategic advantages. The Glass Microfabricator could now leverage comprehensive analytics to support product innovation, client reporting, and process benchmarking. Insights derived from combined R&D and production data informed material selection, tool calibration, and workflow optimization, helping the company maintain a competitive edge in a high-precision industry.
The enhanced visualization capability also supported marketing and sales efforts. Clients could better understand the company’s technical excellence and quality consistency through interactive dashboards, reinforcing brand trust and facilitating long-term partnerships.
