Systems | Development | Analytics | API | Testing

Open Lakehouse Meetup (ft. Apache Iceberg): Building Scalable Data Platforms

Discover the future of the Data Lakehouse with this deep dive into Apache Iceberg V3 and V4 from the Bengaluru community meetup. Learn how PyIceberg and DuckDB are revolutionizing Python-native data processing by eliminating the need for Spark clusters for 99% of common query sizes. Explore high-performance ingestion benchmarks from Oleg and the Google Dataproc Lightning Engine, achieving over 500k rows/sec through Apache Arrow and C++ vectorization. This session is a masterclass for data engineers on metadata compaction, Rest Catalogs, and building vendor-agnostic data platforms.

Top 22 Real Estate KPIs and Metrics for 2026 Reporting

A real estate Key Performance Indicator (KPI) or metric is a quantifiable measure used to assess the performance of a business in the real estate industry. These performance metrics can be used to analyze several different business segments from individual realtor performance to investment property potential. In turn, this information can be used to identify weaknesses in your business or help make better business decisions.

BigQuery Migration Service: SQL and data transfer

Following your migration assessment, it is time to execute the transfer of your data and SQL queries into Google Cloud. This video dives into the specific tools and services that simplify migrating workloads from Snowflake, Teradata, Cloudera, and Databricks into BigQuery, Dataproc, and Google Cloud Storage.

How to Join Parquet & JSON Files in ThoughtSpot Analyst Studio

Stop manually juggling mismatched data formats! This video demonstrates how to join Parquet and JSON files directly within ThoughtSpot Analyst Studio’s Python Notebook to create a single, enriched dataset. What you will see: This is a must-watch for data professionals looking to unify complex, multi-format data sources and deliver searchable, AI-ready insights in one continuous workflow.

Do Identity Intelligence Better with Snowflake and Verato

Healthcare organizations can’t achieve true Patient 360 or power accurate AI and analytics when identity data is fragmented across EHRs, EMRs, CRMs, and countless clinical and operational systems. Check out the full video to see how Verato MDM Cloud delivers industry-leading healthcare identity resolution and master data management (MDM) directly inside Snowflake to unify, enrich, and master patient and provider data with unmatched accuracy.

How Column Sets and Query Sets Simplify Analytics

When you’re building analytics for users, you quickly realize something: not every definition belongs on the Model. A lot of business logic sits in an awkward middle ground, too context-specific to hardcode into the Model but too important to leave scattered across one-off formulas. And in most tools, if the logic doesn’t live on the Model, every team ends up rebuilding the same thing over and over again. That’s where Query Sets and Column Sets in ThoughtSpot come in.

Avoid Vendor Lock-in With Cloud-Agnostic BI

Many AI analytics platforms force enterprises into an impossible choice: adopt cloud-only solutions that compromise data governance and security policies or forgo AI capabilities entirely. But there’s a significant problem with that: most companies aren’t 100% cloud-based, and those that are vary between whether they operate in the public cloud, private cloud, or a hybrid environment.