Assessing Big Data Operations Performance

The client, a leading provider of point-of-sale and ATM services, needed RKTech, Rikkeisoft’s US-based subsidiary, to provide a solution that could help them gauge the efficiency and effectiveness of their big data operations.

About the client

Azure Synapse Analytics

Power BI

Azure Data Lake

Azure Data Factory

This article describes a real-life project. However, we cannot disclose our client’s name for privacy purposes.

The Client is a prominent US-based company with a long history in providing POS, ATM, and ITM solutions. With a significant annual revenue exceeding $7 billion in 2022, their offerings include a broad spectrum of products and services, including self-service kiosks, POS terminals, ATMs, check processing systems, and barcode scanners. As their business expands into the digital sphere, the volume and complexity of their data storage and processing requirements have grown exponentially. The project addressed the Client’s challenges in extracting actionable insights from their rapidly growing data set.

Project Overview

Industry

Information Technology

Technology

Azure Data Lake, Azure Synapse Analytics, Azure Data Factory, Power BI

Country

United States

Duration

Ongoing

Challenges

Despite the vast amount of data collected, the Client faced three significant hurdles in extracting meaningful insights for performance optimization:

– Limited Data Transparency: The Client lacked a centralized, well-documented data management system. The origin, meaning, and structure of the data were often unclear, hindering the identification and utilization of relevant data points for KPI extraction.
– Data Quality Issues: Inconsistencies, inaccuracies, and missing values were prevalent within the data sets, compromising the reliability of extracted KPIs. Manual data cleansing and validation were not only time-consuming but also prone to human error.
– Ineffective Data Analysis: The sheer volume and unstructured nature of the big data overwhelmed traditional data analysis methods. This resulted in a significant gap between the data collected and the actionable insights needed to optimize operations.

Solution

RKTech designed and developed the “Big Data Ops Performance KPIs Extractor” to address these challenges. This solution leverages Microsoft Azure cloud services to deliver a comprehensive data management and analysis framework. The core functionalities include:

– Ingestion & Transformation: Developed ETLs to integrate data from various sources into a centralized Azure Data Lake for efficient storage and management.
– Insight Extraction: Advanced analytics using Azure Synapse Analytics to extract key performance indicators (KPIs) across crucial operational areas.
– Pipeline Performance Measurement: Monitoring of specific data pipelines for:
– Recency: Ensuring data reflects the most up-to-date information.
– Completeness: Verifying the presence of all necessary data points for accurate analysis.
– Performance: Identifying bottlenecks and optimizing data processing speed within pipelines.

Result

The Client expressed a great level of satisfaction with the solution, since it significantly improved their ability to extract actionable insights from their vast data collected, leading to optimized operations and better data-driven decision making. The Client has also expressed strong interest in further collaboration to explore additional solutions that leverage their big data for continued growth and success.

Download case study