Business Over Broadway

DECEMBER 20, 2018

Using Predictive Analytics and Artificial Intelligence to Improve Customer Loyalty – As users/customers engage with a company (their products, services, surveys), they generate a lot of data about their behaviors and interactions with the brand. Data Science/Analytics Tools, Technologies and Languages used in 2017.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74

Occam's Razor

JUNE 7, 2017

If someone bothers to interact with the post, the posted comment is a spam or totally useless. Which in turn lead to even fewer customer interactions for content posted by brands. Do you have access to any data to measure how deeply non-impactful your organic Social Media efforts are? They keep posting. Polluting utopia.

Advertising 162

Advertising Marketing B2B ROI 162

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. Today, managers and workers need to interact differently as they face an always-more competitive environment. Over the past decade, business intelligence has been revolutionized. Data exploded and became big.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Domino Data Lab

AUGUST 1, 2021

The need for interaction – complex decision making systems often rely on Human–Autonomy Teaming (HAT), where the outcome is produced by joint efforts of one or more humans and one or more autonomous agents. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. References.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Domino Data Lab

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ Visualizations are vital in data science work, with the caveat that the information that they convey may be 4-5 layers of abstraction away from the actual business process being measured. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Data Insight

APRIL 15, 2019

We reward and punish based on our last interaction with an organisation and are not afraid to take to social channels to articulate our experiences – whether it be good or bad – to also influence our peer’s choices. That’s a massive shift in quite a short time frame from traditional metrics without us even realising it.

Data-driven 40

Data-driven Metrics Measurement Strategy 40

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? It is hard to account for such tweaking in measurement systems. Pertinence and fidelity of metrics developed from Data.

Metrics 49

Metrics Statistics Data Quality Measurement 49

AWS Big Data

AUGUST 7, 2023

The data contains measurements of electric power consumption in different households for the year 2014. The OBJECTIVE parameter specifies a metric to minimize or maximize the objective of a job. For more information, see ElectricityLoadDiagrams20112014 Data Set (Dua, D. and Karra Taniskidou, E.

Forecasting 86

Forecasting Data Warehouse Machine Learning Modeling 86

Alation

AUGUST 26, 2021

HBR Review May/June 2017. Finally, data catalogs leverage behavioral metadata to glean insights into how humans interact with data. A common BI application is the BI dashboard, which displays key metrics so that leaders have a “big picture view” to inform wise goals and decisions. Source: “What’s Your Data Strategy?”

Metadata 64

Metadata Data Governance Dashboards Software 64

Cloudera

MAY 18, 2021

These interactions are captured and the resulting synthetic data sets can be analysed for a number of applications, such as training models to detect emergent fraudulent behavior, or exploring “what-if” scenarios for risk management. Value-at-Risk (VaR) is a widely used metric in risk management. Intraday VaR. Citations. [1]

Risk 96

Risk Marketing Risk Management Data-driven 96

Domino Data Lab

OCTOBER 23, 2019

As a result, there has been a recent explosion in individual statistics that try to measure a player’s impact. Knowing that the ultimate goal is to compare the social-media influence and power of NBA players, a great place to start is with the roster of the NBA players in the 2016–2017 season. 05) in predicting changes in attendance.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

FEBRUARY 4, 2019

People who attended JupyterCon 2017–2018 can attest, an “industry poster session” includes an open bar, catered hors d’oeuvres, lots of mingling … to paraphrase feedback from JupyterCon, “As a tech person, would I get up extra early to meet strangers for coffee at 8:00 am? The ability to measure results (risk-reducing evidence).

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66