CIO Business Intelligence

JULY 5, 2022

Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. The discipline is a key facet of the business analyst role. Business analytics techniques.

Business Analytics 122

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 122

Rocket-Powered Data Science

DECEMBER 16, 2018

So, you start by assuming a value for k and making random assumptions about the cluster means, and then iterate until you find the optimal set of clusters, based upon some evaluation metric. The above example (clustering) is taken from unsupervised machine learning (where there are no labels on the training data). What data do we have?

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Smart Data Collective

OCTOBER 20, 2020

How Can Data Play an Important Role in GTM? There are a number of reasons that data analytics is transforming the direction of GTM marketing in 2021. Some of these were addressed in the Data Driven Summit 2018. Defining the metrics and goals to measure the success of your business strategy.

Marketing 107

Marketing Data Analytics Analytics Big Data 107

Rocket-Powered Data Science

DECEMBER 15, 2018

If we cannot know that ( i.e., because it truly is unsupervised learning), then we would like to know at least that our final model is optimal (in some way) in explaining the data. In those intermediate steps it serves as an evaluation (or validation) metric. This challenge is known as the cold-start problem !

Machine Learning 171

Machine Learning Optimization Metrics Modeling 171

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike. 9) Data Automation.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361