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Fundrise CTO: New SQL Tools Lead to ‘Wonderfully Seamless Solutions’

The Startup Magazine

Despite its decades-old roots, SQL is undergoing a renaissance, buoyed by SQL tool advancements in a variety of data-related tools. What Is SQL? SQL is a standardized programming language specifically designed for managing and interacting with relational databases, where information is stored in interrelated tables.

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Lessons Learned: Sharding for startups

Startup Lessons Learned

If youre of the type of organization that doesnt use db access objects directly, but simply passes SQL statements through a central API, you can try this: consider the entity identifier as part of the statement itself. Nearly every SQL query I see has a join. The actual directory itself is straightforward. E, How is WoW sharded?

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A Marketer’s Guide to Kaggle for Analytics and Data Science

ConversionXL

Working with this dataset can be valuable in terms of understanding the underlying structure of Google Analytics data and experimenting with a number of advanced statistical and data mining techniques that can’t be applied when the data is in aggregate form (which is the norm with standard Google Analytics.). Let’s have a closer look.

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Scaling lessons learned at Dropbox, part 1

eranki.tumblr.com

Another thing that became increasingly useful was to have thousands of custom stats aggregated over thousands of servers graphed. We eventually ended up converting everything to SQLAlchemy’s lowest-level language for constructing SQL (one step away from raw SQL). Better than switching off features! App-specific metrics.

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Amazon Redshift Too Slow or Crashing? BlazingDB Performs

Austin Startup

Massive Scale with Unprecedented Speed BlazingDB offers a massively distributed, “cloud first”, high performance SQL database that achieves performance gains on the largest workloads and datasets at extraordinarily competitive costs. Transformations, aggregations and joins at massive scale is where BlazingDB wins!

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A Quick Primer on B2B Conversion Optimization

ConversionXL

So the process in B2B looks a bit like this (simplified): Visitor → MQL → SQL → customer. There you want to look at things in clumps and aggregates. What this means depends on the company, but it can take into account different metrics like pathing, time on site, video engagement, company size, role, etc. Account-Based Marketing.

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Google BigQuery: A Tutorial for Marketers

ConversionXL

Alternatives include Amazon Redshift , Snowflake , Microsoft Azure SQL Data Warehouse , Apache Hive , etc. The solution is to give every lead and every purchase a userID (like an encrypted email), to pull CRM and Google Analytics data into your BigQuery data warehouse, and then—with a simple SQL query—join the two tables.

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