Blog
Putting our heads together.
04/23/2025
Cloud Data Engineering for EV Charging Networks: 3 Business Challenges You Can Solve Today
Scaling an EV charging network isn’t easy. From choosing the right sites to minimizing downtime without blowing the budget, it's smart data use that makes it possible.
Explore how Cloud Data Engineering can help solve common EV Charging Network challenges, including data fragmentation, uptime, and operational costs.
04/20/2025
How NaNLABS Developed a Cloud Native Observability Platform and Optimize Data Processing For An EV Charging Company
An EV charging company needed to design a scalable, cloud-native data architecture to process information, gain insights fast, and improve reliability. Learn how NaNLABS supported them to achieve these goals.
An EV charging company needed to access data coming from multiple EV charging stations. Along with NaNLABS, it built an observability tool to drive insights, here's how.
04/03/2025
How we Turned an Internal Tool Into a SaaS Platform With 75% Faster Query Response Times For Equinix
Turning an internal tool into a SaaS platform is about more than adding features. It’s about ensuring performance, reliability, security, and availability for all users. Here’s how NaNLABS and Secretly Nice helped Equinix tackle these challenges.
Learn how NaNLABS migrated Equinix’s sales platform to a multi-tenant architecture, boosting performance while reducing infrastructure costs.
03/27/2025
Reducing Fleet Downtime: How Real-Time Data Analytics Drives Operational Excellence
Every minute an EV fleet is out of service means lost revenue, inefficiencies, and customer dissatisfaction. Discover how real-time analytics can transform your operations to minimize downtime and optimize costs.
Downtime isn’t just an operational challenge—it’s a strategic risk that affects revenue, asset utilization, and scalability. In an uptime-critical industry, reactive maintenance isn’t enough; real-time insights are the key.
03/26/2025
In-House vs. Outsourced Data Engineering: Which is Best for Your Business?
Data collection, processing, and analysis are essential for gaining a competitive edge and driving innovation. But should you build this capability in-house or outsource to data engineering experts? Let’s break down the pros and cons.
Building, managing, and scaling efficient data pipelines requires a skilled team. The question is—should you develop that expertise in-house or leverage an external team to drive smarter, data-driven decisions?
03/06/2025
From Startup to Acquisition: How We Helped WootCloud Cut Costs by 44% Through Data Engineering and Cloud Optimization
Unreliable architecture, slow data processing, and high costs were preventing WootCloud, an IoT security company, from growing. See how we enabled it to scale, leveraging a serverless architecture, AI/ML models, and cloud-native solutions.
We helped a device context platform scale, cut costs by 44%, and get acquired by optimizing the cloud infrastructure and building real-time data pipelines.
02/17/2025
AI in Customer Experience: How Businesses Use it to Increase Engagement And Lower Costs
Wow your customers at every stage of the lifecycle with AI-powered features. Learn the benefits of using AI in customer experience, real-life examples, and pitfalls.
AI models allow you to automate repetitive tasks, drive insights from data, and improve the customer experience. Here’s how.
01/03/2025
How Databricks Transformed Real-Time Data Processing for Advanced Analytics
Databricks completely changed how we stream and process real-time data. This makes it the go-to choice for building advanced analytics. Here’s how to use this service to solve common data management challenges.
Process data from diverse sources in real-time with Databricks for advanced analytics. Here’s what Databricks can do for you (with examples).