Improving Data Insights with Query Optimization on BigQuery

Business Opportunity

Optimizing Queries for Improving BQ Performance

The client is a fast-growing social e-commerce platform catering to value-conscious customers in India. Founded in 2018, it serves millions across multiple states with an innovative group-buying model. Offering over 100,000 products across categories like groceries and home essentials, the client partners with local suppliers to support small businesses. 

The client’s previous data warehousing setup, which utilized Redshift along with various tools for data ingestion and processing, faced several challenges. This included maintenance complexities, data reliability concerns, inefficiencies in data processing and ingestion, high costs, performance and latency issues, and restricted scalability.

We helped the client address these issues by optimizing their queries and elevating their BigQuery usage. By migrating to BigQuery, the client was able to improve data warehousing, streamline task management, and better align processes with business objectives. The optimization enabled a more efficient, scalable, and cost-effective data architecture with enhanced data governance and real-time analytics capabilities.

The Challenge

Cost Concerns: The existing data warehousing setup incurred high operational costs, driven by inefficient resource utilization and scaling limitations.

Performance and Latency Issues: Frequent delays in query processing and data retrieval hindered real-time decision-making, leading to bottlenecks and reduced overall performance.

Maintenance Difficulties: The complex architecture of the current setup required significant effort for routine maintenance and troubleshooting, which would impact business continuity.

Our Solution

As the client had already migrated their data, our focus was on translating and optimizing the provided queries. We utilized the BigQuery query translator tool to convert the queries, followed by manual optimization to enhance performance where necessary. Automatically reflects updates in underlying tables. The optimized queries were saved as BigQuery Views. 

BigQuery Views are virtual tables that allow you to store a query for reuse. They do not store data; instead, they store the SQL query and provide the results dynamically when queried. This can be useful for simplifying complex queries. They maintain access control by granting permissions on views without exposing base tables. Users would require appropriate permissions to access base tables. 

A reporting dataset was created in BigQuery, serving as the foundation for this process. This enabled seamless integration with the client’s existing analytical reports. The approach ensured efficient query execution and a streamlined connection to the client’s reporting framework. With BigQuery in place, dashboard reports in Redash, Superset, and Tableau provided the client with seamless access to actionable insights, empowering data-driven decision-making and enhancing operational efficiency.

Results

The optimization efforts resulted in:

• 99% Improvement in Query Response and Runtime: Significantly enhanced performance, enabling faster data-driven decision-making.
• Customer Experience Enhancement: Improved data accessibility and efficiency contribute to a smoother customer journey.
• Productivity Improvement: Streamlined query processes reduced manual effort, allowing teams to focus on strategic tasks.
• Improved Brand Engagement, Loyalty, and Trust: Faster, reliable insights strengthened the client’s ability to engage customers and build trust in their services.

Power of Partnership

Partnering with Niveus enabled the client to overcome the challenges of its existing data warehousing setup and achieve measurable improvements. Leveraging our expertise in BigQuery, we provided tailored solutions that seamlessly integrated with the client’s infrastructure. By translating and optimizing queries, we ensured a scalable, cost-effective architecture aligned with the client’s business goals. Our hands-on approach, from query translation to performance enhancement, delivered improvement in query runtime, reduced costs, and enhanced operational efficiency.

Through this collaboration, the client benefited from faster insights, improved customer engagement, and a reliable data foundation to support its growth. With Niveus, the client gained not just technical solutions but a committed partner dedicated to driving long-term success.

Benefits of Niveus BigQuery Optimization Services

By optimizing queries in BigQuery, businesses can elevate the benefits that come with BigQuery. These include:

• Cost Reduction in Storage Usage: Optimizing data management and storage leads to significant cost savings by reducing resource consumption
• Improved Operational Efficiency: Streamlining processes and optimizing queries enhances overall operational efficiency
• Decreased Latency and Enhanced Performance: Optimizing queries can enable faster data retrieval and processing, thereby reducing latency and improving system performance 
• Faster Time to Delivery: Optimizing systems and processes enable quicker delivery of data and insights
• Improvement in CSAT Scores: Enhancing BQ performance and user experience results in higher customer satisfaction and loyalty