Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. This is the essence of Convergent Evolution.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Jet Global

AUGUST 4, 2023

Providing valuable insights from data that moves the business forward in achieving its strategic objectives is one of the most valuable skills any FP&A or Operational Planning (OP) professional can possess. Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.

Data Analytics 52

Data Analytics Analytics Finance Visualization 52

The Unofficial Google Data Science Blog

JULY 22, 2020

For example, imagine a fantasy football site is considering displaying advanced player statistics. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. One reason to do ramp-up is to mitigate the risk of never before seen arms.

Experimentation 95

Experimentation Statistics Testing Strategy 95

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 56

Data Science Machine Learning Cost-Benefit Deep Learning 56

Rita Sallam

JULY 22, 2016

These intentions are also reflected in Gartner’s previous webinar poll results in March and in our 2015 market share results, which show a 63% growth in Modern BI market growth versus a 1.7% decline in traditional BI ( See: Market Share Analysis: Business Intelligence and Analytics Software, 2015 ).

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

The Unofficial Google Data Science Blog

MARCH 31, 2016

Far from hypothetical, we have encountered these issues in our experiences with "big data" prediction problems. We often use statistical models to summarize the variation in our data, and random effects models are well suited for this — they are a form of ANOVA after all. arXiv preprint arXiv:1506.04416 (2015). [6]

Modeling 40

Modeling Statistics Advertising Testing 40

Occam's Razor

MARCH 30, 2017

Yes, a silo but so much better than 2015. Sidebar: If you don’t know these three phrases, please watch my short talk: A Big Data Imperative: Driving Big Action.]. Insane as it seems like, data collection should get sorted out in the next few years. Students must learn how to turn data into knowledge.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Occam's Razor

JULY 13, 2017

As an analyst, as a Big Data person, as a Data Scientist, pouring the right data on humanity is only marginally effective. Consider this, conversion rate could go up by a statistically significant percentage… While revenue actually goes down. publishes a ton of data. Insanely helpful. 17 mil lives saved.

Visualization 124

Visualization Strategy Interactive Statistics 124

Smart Data Collective

JUNE 26, 2019

Get Rid of Blind Spots in Statistical Models With Machine Learning. Data-related blind spots could also exist in your statistical models. RiskSpan is a company that built a machine learning algorithm that can flag error-prone parts of a statistical model and indicate which associated outputs may be unreliable.

ROI 102

ROI Statistics Machine Learning Measurement 102

CIO Business Intelligence

MAY 7, 2024

When it broke onto the IT scene, Big Data was a big deal. Still, CIOs should not be too quick to consign the technologies and techniques touted during the honeymoon period (circa 2005-2015) of the Big Data Era to the dust bin of history. Data is the cement that paves the AI value road. Data is data.

Big Data 125

Big Data Statistics Machine Learning Data Science 125

Smart Data Collective

MAY 19, 2021

Big data technology has become a major disrupting factor in the energy industry. Many energy conglomerates have started embracing data analytics to expand their markets, respond to new trends, streamline operations and bolster efficiency. The clean energy sector has not been untouched by the big data revolution.

Data Analytics 90

Data Analytics Analytics Big Data Predictive Analytics 90