Key Challenges with Database Pipelines

As a data engineer who has worked on building and managing various technical aspects of data pipelines over the years, I've navigated the intricate landscape of data integration, transformation, and analysis. In mid-market companies, where data-driven decision-making is pivotal, constructing efficient and reliable database pipelines allows you to store data in cloud data warehouses and carry out better data analysis or machine learning models.

AWS ETL; Everything You Need to Know

As a data engineer who has designed and managed ETL (Extract, Transform, Load) processes, I've witnessed firsthand the transformative impact of cloud-based solutions on data integration. Amazon Web Services (AWS) offers a suite of tools that streamline ETL workflows, enabling mid-market companies to move the big data to data stores such as Snowflake, data lake from different sources depending on use cases.

The Power of Data Streaming in Digital-Native Organizations: A Look Inside AppDirect

In today’s fast-paced technological landscape, staying ahead means more than just keeping up with the latest trends—it requires a fundamental shift in how businesses operate in increasingly digital spaces. AppDirect, a digital-native company at the forefront of innovation, has fully embraced this digital paradigm, aligning itself with modern business approaches that enhance both operational efficiency and customer experience.

Driving Real Business Value from AI: Value-Focused Data Leaders to Watch in 2025

As organizations mature in their execution of data and AI initiatives, a burning question remains: How do we measure the effectiveness of our teams and our impact on the business? This isn’t the perennial “What’s my data worth?” dilemma often asked rhetorically and answered theoretically. Today’s challenge is concrete: to define and track the metrics used to justify continued investment in data and AI innovation.

Ep3: Data, AI, and the Hybrid Hustle: Connecting the Dots in a Fast-Paced World

Technology in the enterprise is evolving at a record pace, making it increasingly difficult to keep up with the latest "tech du jour." AI has only accelerated this evolution, bringing about a data reckoning—especially as more organizations adopt hybrid models to manage their data. Both users and organizations are seeking data platforms that can connect the dots of their data today while adapting to tomorrow's demands. This shift underscores the growing demand for open standards. But what does that kind of platform experience look like today?

Embedded Spotter, the AI Analyst that delivers actionable insights where you work

With ThoughtSpot Embedded’s modern developer tools, you can embed Spotter into any of your business applications. Spotter integrates effortlessly into your preferred platforms, seamlessly embedding within existing business applications, digital productivity tools, and custom agents to meet you where you work, so your users can ask questions of their data anywhere, at any time.