ConversionXL
JANUARY 8, 2020
Most importantly, there’s a large variety of datasets related to marketing, ecommerce, and sales. Work with R, Python, and SQL code directly from the browser—no need to install anything. Some interesting marketing datasets to explore. They come with a quality score ranging from 1 to 10 based on how complete the documentation is.
Austin Startup
MARCH 15, 2017
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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ConversionXL
NOVEMBER 3, 2016
Some of the same underlying principles apply, but because of the inherent differences in buying decisions and sales cycles, pulling B2C optimization practices straight from the book might be a bad idea. There are a few things that make optimizing for B2B a different beast: The sales cycle is usually longer.
ConversionXL
FEBRUARY 18, 2020
For example, while the data aggregation process in Google Analytics seems like a “normal” feature, it might be a hurdle if your business needs to process data at the hit level instead of by sessions or campaigns. An enterprise data warehouse for fast SQL queries. How precisely does this model work? Only Google knows. Customization.
ConversionXL
OCTOBER 4, 2018
According to Phillips: A few thousand records with a sufficient amount of positive and negative outcomes can be sufficient for marketing, sales, and product prediction. In stadiums, Longstreet explained, point-of-sale machines and ticket scanners exist for a single purpose—to complete transactions quickly and keep lines moving.
ConversionXL
MAY 13, 2020
After a few hours playing around with SQL , I was already able to deliver insights I never could have with aggregated Google Analytics reports. What’s the difference between raw and aggregated data in Google Analytics? Google Analytics, in the free version, provides only aggregated data. Where do my users come from?
Version One Ventures
AUGUST 16, 2017
Let’s think about the typical (and simplified) data flow in a company: raw data is aggregated, normalized or processed and then stored in a data warehouse. In addition, different parts of the organization usually create their own dashboard for a view of more team-specific metrics (like sales, marketing, product, etc.).
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