Occam's Razor

SEPTEMBER 13, 2016

If you are curious, here is a April 2011 post: The Difference Between Web Reporting And Web Analysis. With that as context, you can imagine how heart-broken I was when Jane shared the following visual from a study done by Econsultancy and Lynchpin. Visual perception of information. Interpreting mathematical information.

Modeling 127

Modeling Reporting Strategy Consulting 127

Domino Data Lab

JULY 9, 2019

A “data scientist” might build a multistage processing pipeline in Python, design a hypothesis test, perform a regression analysis over data samples with R, design and implement an algorithm in Hadoop, or communicate the results of our analyses to other members of the organization in a clear and concise fashion. And it works.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Occam's Razor

APRIL 25, 2011

" I'd postulated this rule in 2005, it is even more true in 2011. Making website iterations based on executive opinions, but not site testing. via Jordan Silton] "With testing you can prove if Executives are right or not, and maybe, just maybe figure out WHY. The 10/90 rule. People matter.

Marketing 126

Marketing Measurement Metrics Testing 126

Domino Data Lab

AUGUST 22, 2019

Note: A test set of 19,500 such analogies was developed by Tomas Mikolov and his colleagues in their 2013 word2vec paper. This test set is available at download.tensorflow.org/data/questions-words.txt.]. Relative to extrinsic evaluations, intrinsic tests are quick. Note that the final test word in Table 11.2—ma’am—is

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Domino Data Lab

MARCH 3, 2019

I’m here mostly to provide McLuhan quotes and test the patience of our copy editors with hella Californian colloquialisms. Note how model visualization is bubbling up to the top, which has implications for model interpretability, cyber threats, etc. Seriously, Ben gets credit for foresight on how to organize those surveys.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

APRIL 3, 2019

Fun fact: in 2011 Google bought remnants of what had previously been Motorola. Marquez is a project sponsored by WeWork and Stitch Fix to “collect, aggregate, and visualize a data ecosystem’s metadata” which sounds roughly akin to some aspects Egeria. Apache Atlas is a Hadoop-ish native reference implementation for Egeria.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

MARCH 25, 2022

We founded MemSQL (the original name of SingleStore) in 2011. Around 2011, we worked with a hot gaming company with a real-time analytics use case to understand what their users were doing in the moment to optimize the gaming experience by monitoring how users interacted with the game.

Data-driven 77

Data-driven Data Warehouse Data Processing Marketing 77

Occam's Razor

SEPTEMBER 24, 2012

It is possible to get good test and control groups (type of population, existing brand awareness, market penetration, competitive structures) for our experiments. I wanted to come up with a way to visualize the unique challenge Facebook faces when it comes to proving ROI. Let's go! Metrics are a problem. It is cute.

Advertising 165

Advertising ROI Metrics Marketing 165

BizAcuity

MAY 10, 2022

2011: IBM enters the cloud market with IBM SmartCloud. Microsoft also releases Power BI, a data visualization and business intelligence tool. AWS rolls out SageMaker, designed to build, train, test and deploy machine learning (ML) models. [You can read more on IaaS, PaaS and SaaS here ].

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

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!, To start a more in-depth grasp of your own data sets, you can try our online data visualization tool for free with a 14-day trial !

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Smart Data Collective

JUNE 6, 2021

This can be done through the analysis of previous product success as well as the data collected from test markets and/or social groups that may dictate what commercial offerings are best received. Ingesting, storing, processing and visualizing information are key areas of focus that BigQuery aims to assist you with.

Big Data 133

Big Data Data Analytics Analytics Cost-Benefit 133