IBM Big Data Hub

MARCH 25, 2022

We founded MemSQL (the original name of SingleStore) in 2011. This helps our customers mitigate the risks and costs of managing complex ecosystems of tooling built around the mostly single-host SQL database technologies that existed at the time. Guest blogger: Chief Technology Officer and Co-Founder: Adam Prout.

Data-driven 69

Data-driven Data Warehouse Data Processing Marketing 69

The Unofficial Google Data Science Blog

APRIL 17, 2017

In the first plot, the raw weekly actuals (in red) are adjusted for a level change in September 2011 and an anomalous spike near October 2012. Such a model risks conflating important aspects, notably the growth trend, with other less critical aspects.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Peter James Thomas

AUGUST 12, 2018

Integrity of statistical estimates based on Data. Having spent 18 years working in various parts of the Insurance industry, statistical estimates being part of the standard set of metrics is pretty familiar to me [7]. The thing with statistical estimates is that they are never a single figure but a range. million ± £0.5

Metrics 49

Metrics Statistics Data Quality Measurement 49

The Unofficial Google Data Science Blog

MAY 31, 2016

Statistical power is traditionally given in terms of a probability function, but often a more intuitive way of describing power is by stating the expected precision of our estimates. This is a quantity that is easily interpretable and summarizes nicely the statistical power of the experiment. In the U.S.,

Advertising 43

Advertising Testing Sales Statistics 43

Domino Data Lab

MARCH 3, 2019

While image data has been the stalwart for deep learning use cases since the proverbial “ AlexNet moment ” in 2011-2012, and a renaissance in NLP over the past 2-3 years has accelerated emphasis on text use cases, we note that structured data is at the top of the list in enterprise. Spark, Kafka, TensorFlow, Snowflake, etc.,

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

JANUARY 6, 2019

What are the projected risks for companies that fall behind for internal training in data science? Downey (2011). How do options such as mentoring programs fit into this picture, both for organizations and for the individuals involved? In business terms, why does this matter ? Python Data Science Handbook. Jake Vanderplas (2016).

Data Science 56

Data Science Machine Learning Visualization Reporting 56

CIO Business Intelligence

APRIL 9, 2025

The foundational tenet remains the same: Untrusted data is unusable data and the risks associated with making business-critical decisions are profound whether your organization plans to make them with AI or enterprise analytics. Absent governance and trust, the risks are higher as organizations adopt increasingly sophisticated analytics.

Enterprise 102

Enterprise Analytics Experimentation Statistics 102

Sisense

MAY 4, 2020

These statistics highlight how large the task is to extract, transform, and load data that will be ready for analysis. According to an Accenture study, 79 percent of enterprise executives say that not embracing Big Data will cause companies to lose competitive position and risk extinction. Organizations must adapt or die.

Big Data 78

Big Data Data-driven Snapshot Unstructured Data 78

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. More people than ever are using statistical analysis packages and dashboards, explicitly or more often implicitly, to develop and test hypotheses. This question is statistical or methodological in nature. Know what matters.

Experimentation 62

Experimentation Testing Statistics Metrics 62

Occam's Razor

JUNE 4, 2018

I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Not wanting to risk it, I click on the Find in Store link you see at the bottom of the page. I don’t mean: BUY IT NOW OR ELSE! Sizing the Opportunity. Add to Basket!

Strategy 125

Strategy Cost-Benefit Testing Sales 125

Domino Data Lab

JULY 9, 2019

You can sleep at night as a data scientician and you know you’re not building a random number generator, but the people from product, they don’t want to know just that you can predict who’s going to be at risk. Nobody paid any attention to it whatsoever until 2011. They want to know what are the risky behaviors.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

datapine

AUGUST 29, 2022

He founded the project Apache Storm in 2011, which turned to be “one of the world’s most popular stream processors and has been adopted by many of the world’s largest companies, including Yahoo!, Microsoft, Alibaba, Taobao, WebMD, Spotify, Yelp” according to Marz himself. It was lately revised and updated in January 2016.

Big Data 263

Big Data Data Analytics Analytics Data mining 263