Systems | Development | Analytics | API | Testing

Get Full LinkedIn Ad Performance Data (Beyond LinkedIn's 25-Company Limit)

LinkedIn Ads only show 25 companies in their reporting. But if you’re running demand gen for B2B clients, that’s not enough. In this quick walkthrough, Jason Spooner (Founder, Jars Digital) shows how he uses Databox to get a complete view of LinkedIn ad exposure by company—so you can: See every company engaging with your ads Match ad data to pipeline and revenue Prove marketing’s impact on sales Whether you run paid media for clients or in-house, this tip helps you unlock more insight and drive better decisions.

Data Validation in ETL - 2026 Guide

Data validation is the cornerstone of successful ETL (Extract, Transform, Load) processes, ensuring that information flowing through your data pipeline maintains its integrity and usefulness. When data moves between systems, it can become corrupted, incomplete, or inconsistent—problems that proper validation techniques can prevent.

Confluent Cloud Is Your Life (K)Raft Away From Hosted Apache Kafka

Streaming your data with Apache Kafka, at its core, involves moving data from one point to another in real time, much like a river flows from its source to its destination. However, beneath this seemingly straightforward goal lies significant complexity and hidden costs. The multitude of available deployment options, hosted and managed Kafka services, and design choices make it difficult to navigate the data streaming landscape.

How to Automate Data Quality for AI and Analytics with Snowflake and Anomalo

Join Anomalo’s Jonathan Karon to learn how organizations implement automated data quality natively within Snowflake to: Securely govern structured tables and unstructured documents for AI-readiness Leverage Snowflake Native Apps and Snowpark Container Services so data never leaves your environment Detect 80% of data issues automatically without manual rules Standardize quality across all data types so BI tools and AI agents can safely operate and trace decisions.

Leveraging Dynamic Parameters for Enhanced Data Visualization

Are your liveboards getting cluttered with too many charts? In this video, Amit Barnwal, Solutions Architect at ThoughtSpot, demonstrates how to use Dynamic Parameters to consolidate multiple reports into a single, interactive visual. Learn how to give your end-users the power to swap measures and attributes on the fly, allowing you to tell a bigger story in a much smaller space. What’s inside this video.

Deep Insights into Big Data - Spotter Search

-Are you new to a data model or looking to uncover the "why" behind your metrics? In this video, we dive into Spotter, the conversational AI feature in ThoughtSpot, to see how it acts as an agentic teammate for data exploration and research. Follow along as we use a Customer Success model to demonstrate how Spotter moves beyond simple charts to provide comprehensive reports, relationship mapping, and statistical correlations.