Dataiku

NOVEMBER 13, 2020

While the backdrop of 2020’s global health crisis and economic uncertainty makes heading into the holiday season quite unlike years past, the U.S. is still slated to drive online sales growth. According to eMarketer , both Black Friday and Cyber Monday shopping days are positioned to surpass $10 billion in e-commerce sales, with their projected totals up 39% and 38% from last year, respectively.

Forecasting 105

Forecasting Uncertainty Sales 105

Analytics Vidhya

NOVEMBER 13, 2020

Overview Looking to transition into data science? Here are 8 paths for a non-data science person to land a role in this space The. The post 8 Thoughts on How to Transition into Data Science from Different Backgrounds appeared first on Analytics Vidhya.

Data Science 361

Data Science Analytics Deep Learning Machine Learning 361

David Menninger's Analyst Perspectives

NOVEMBER 13, 2020

A data lake is a centralized repository designed to house big data in structured, semi-structured and unstructured form. I have been covering the data lake topic for several years and encourage you to check out an earlier perspective called Data Lakes: Safe Way to Swim in Big Data? for background. Our data lake research has uncovered some points to consider in your efforts, and I’d like to offer a deeper dive into our findings.

Data Lake 350

Data Lake Big Data Data Governance Technology 350

erwin

NOVEMBER 13, 2020

The business challenges facing organizations today emphasize the value of enterprise architecture (EA) , so the future of EA is closer than you think. Are you ready for it? See also: What Is Enterprise Architecture? . COVID-19 has forced organizations around the globe to re-examine or reimagine themselves. However, even in “normal times,” business leaders need to understand how to grow, bring new products to market through organic growth or acquisition, identify new trends and opportunities, de

Enterprise 131

Enterprise Digital Transformation Key Performance Indicator Data-driven 131

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Experimentation

Smart Data Collective

NOVEMBER 13, 2020

Artificial intelligence and data analytics are two of the fasting-growing forms of technology for saving money in the world of business. Most companies achieve this goal by cutting down on labor hours, since labor is one of their biggest expenses. There are certainly downsides to that approach, with job security being high on the list. However, in the world of nonprofits, where so many volunteers work, every job that can be done by a computer means one more set of hands that can be working on so

Predictive Analytics 106

Predictive Analytics Analytics Machine Learning Strategy 106

CONTACT Software

NOVEMBER 13, 2020

It’s September 2020 – a lazy late summer evening: Tim Weilkiens and I are holding a virtual meeting to discuss what we would like to present in our joint contribution to Systems Engineering 2020. It will boil down to an example from the current development status of SysMLv2 – something new – a live demo … Continue reading "MBSE is too important not to have a podcast".

IT 52

IT Modeling 52

Cloudera

NOVEMBER 13, 2020

This is part of our series of blog posts on recent enhancements to Impala. The entire collection is available here. Apache Impala is synonymous with high-performance processing of extremely large datasets, but what if our data isn’t huge? What if our queries are very selective? The reality is that data warehousing contains a large variety of queries both small and large; there are many circumstances where Impala queries small amounts of data; when end users are iterating on a use case, filterin

Optimization 143

Optimization Metadata Statistics Cost-Benefit 143