Systems | Development | Analytics | API | Testing

At ThoughtSpot, we’re on a mission to empower every business user to become a data champion. Over the past year, I’ve witnessed firsthand how organizations across Australia and New Zealand are embracing this vision, transforming the way they work, make decisions, and serve their customers. Today, I’m excited to share some of the incredible momentum we’re seeing in the region and to celebrate the forward-thinking organizations leading the charge.

Gen AI call center co-pilots can provide enterprises with operational visibility and insights while automating repetitive tasks, to improve the customer experience. In this session, we’ll show how a large health insurance provider implemented an agentic co-pilot designed scale across multiple call centers and environments. To dive deep into the architecture and see a demo of the co-pilot, you can watch the webinar this blog is based on.

You’re probably familiar with Android Geofencing already, but in case this is your first rodeo, it’s a location-based system that can receive access to a mobile device’s location data, and trigger all kinds of functions when users pass in and out of specific areas. The ads our users see, the content they can stream, the offers they receive via push notifications… all can be triggered by geofencing.

Scaling services can be tricky. But understanding the difference between stateless and stateful services makes it easier. Here's what you need to know.

The retail industry is constantly evolving, and so is the way that businesses use BI tools. Retail business intelligence (BI) dashboards are now more important than ever, as they allow businesses to monitor their operations in a more comprehensive way. In this article, we explore the benefits of using dashboard software in the retail industry, and discuss some of the ways in which they are transforming how it operates.

In the fast-evolving world of data engineering and operations, agility is no longer optional—it’s a competitive necessity. Organizations are under pressure to deliver real-time insights, automate repetitive tasks, and streamline business processes faster than ever. But traditional, code-heavy development cycles can’t keep up with this pace, especially when every change request adds to your backlog and dev cycles stretch into weeks.

In today's interconnected SaaS landscape, application programming interfaces (APIs) have emerged not just as technical enablers but as strategic assets. For field service businesses managing complex operations—from dispatch and inventory to customer engagement—the Service Fusion API offers a powerful gateway to automation, integration, and operational intelligence.

In the era of data-driven decision-making, Customer Data Platforms (CDPs) are pivotal. However, legacy CDPs, which are monolithic, inflexible, and siloed, are falling behind. The rise of Composable CDPs marks a strategic pivot, placing power back in the hands of data teams. At the forefront of this shift is Databricks, whose Lakehouse Platform offers a foundation to unify, govern, and activate customer data with unprecedented agility.

Finance leaders today face increasingly complex challenges, from managing vast amounts of data to meeting growing demands for real-time insights and agility. During a recent LinkedIn Live session, insightsoftware showcased how it is addressing these challenges by empowering the Office of the CFO through innovative solutions, deep integration with Microsoft Dynamics, and strategic partnerships. Head over to our LinkedIn page to watch on-demand.

By optimizing Python code, you improve performance, reduce resource consumption, and enhance scalability. While Python is known for its simplicity and readability, these characteristics can sometimes come at the cost of efficiency. In this article, we'll explore four ways to optimize your Python project and improve performance. First, we'll look at how best to use data structures.