AI-POWERED QUALITY & DATA ANALYTICS TOOL

#Fintech & Trading & Retail

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#CUSTOM SOFTWARE DEVELOPMENT, #BESPOKE SOFTWARE, #CLOUD SOLUTIONS, #AUTOMATION, #ML & AI

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SUMMARY:

We have developed a high-quality monitoring tool and data quality software that automates the processing of large volumes of sensitive data. This solution incorporates real-time monitoring capabilities to ensure the data being processed meets the required standards. With the assistance of AI-powered features, this software enhances data quality and ensures reliable data collection. It also automates manual entries, improving the overall processing quality and enabling data-driven insights.

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CLIENT

NDA

Mexico | 50-100 employees

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Our client, a prominent fintech leader, serves as a trusted partner for entrepreneurs seeking innovative finance, investment, and data management solutions. The company manages a diverse range of data sources, including customer transactions, market data, and internal operations, positioning itself as an expert in handling complex data environments.

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REQUEST BACKGROUND

Automated Data Profiling Software & Data Quality Tool Development, in order of staying competitive, the company adopted an automated data profiling solution to address significant challenges in data quality, collection, and processing time.

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Inconsistent and inaccurate data from various sources resulted in data quality issues, undermining the credibility of analytical insights. Consequently, the company relied on traditional manual profiling methods. However, this approach was time-consuming, error-prone, and hindered the efficiency of the overall data ingestion pipeline.

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Recognizing the limitations of manual data profiling, the client sought to leverage automated data profiling and requested the development of a tool from the ground up. The tool was envisioned to serve as a comprehensive data quality software solution. It was designed to automate data collection, categorization, and allocation, ensuring data quality and enabling the extraction of valuable and consistent insights.

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CHALLENGE

A Scalable Data Profiling Tool Eliminating Manual Processing through AI Automation

To address regular bottlenecks and delays in data processing during periods of high incoming data volumes, our client needed a scalable and flexible solution. The goal was to handle fluctuating amounts of data effectively.

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As both a data quality and profiling tool, the product required cohesive AI algorithms for sorting data and extracting insights. Since manual effort was the primary cause of delays, our team focused on providing comprehensive automation across the entire data handling cycle.

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Further, data availability delays and inconsistent quality significantly impacted the client’s analytics clarity and overall operational costs.

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GOALS

1. Enhance data quality: Leverage AI-automated data profiling to significantly improve the accuracy, consistency, and reliability of incoming data.
2. Streamline data ingestion: Optimize the data ingestion process to efficiently process and assimilate data from diverse sources.
3. Implement real-time quality monitoring: Identify and address data quality issues promptly with real-time monitoring features. Ensure that the data quality software prevents the spread of inaccurate data.
4. Scale AI data profiling solution: Provide seamless scalability of the integrated AI data profiling solution to handle increasing data volumes while maintaining performance and efficiency.
5. Reduce data management costs: Minimize manual efforts in data profiling and mitigate the impact of poor data quality, leading to reduced data management costs.

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SOLUTION

Artificial Intelligence Data Profiling Solution and Data Quality Monitoring Tool

Apache Spark, Apache NiFi, AWS, Tableau, Power BI, DBSCAN, SVM

11 months

7 specialists

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To address the aforementioned challenges, the Levisoft team created an AI-powered automated data profiling tool. Initially, our developers assessed current data collection patterns to determine the required artificial intelligence algorithms for the data profiling solution.

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We utilized sophisticated machine learning data classification and clustering techniques to automatically analyze and comprehend incoming data. As a result, the data profiling tool could autonomously recognize data types, patterns, and anomalies.

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This approach provides a comprehensive overview of incoming data. Automation reduced reliance on manual profiling and accelerated the data profiling process as a result.

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With a focus on real-time data quality monitoring, the development team implemented standardized and iterative processes and frameworks. This methodology allowed for the identification and monitoring of data quality issues through dashboards. It can also automatically configure alerts to notify of any data alterations as they occur.

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To ensure future scalability, the system was designed to accommodate growth and fluctuations in data inflow. The data profiling and data quality tool was structured for horizontal scalability, enabling the client to seamlessly manage increasing data volumes without compromising performance.

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OUTCOME

DATA QUALITY AUTOMATION = OPERATIONAL EFFICIENCY 

• Data processing time has been reduced by 30%, taking an average of 8 hours compared to the previous 12 hours per 1 terabyte dataset.
• Real-time monitoring has been implemented, enabling the identification and resolution of data quality issues within 1 hour.
• A 40% reduction in data errors and inconsistencies has been achieved, resulting in a final data quality rate of 95%.
• Scalability has been improved by over 200%, allowing the client to process and ingest up to 30 terabytes of data per day.
• The confidence level in data-driven decision-making has increased by 25%, resulting in an average confidence level of 95%.
• AI data profiling software has contributed to improved scalability and data processing times.

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