IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts.

Data Science 78

Data Science Data Analytics Prescriptive Analytics Analytics 78

O'Reilly on Data

JUNE 18, 2019

Even with the rise of open source tools for large-scale ingestion, messaging, queuing, and stream processing, siloed data and data sets trapped behind the bars of various business units is the normal state of affairs in any large enterprise. An important paradigm for solving both these problems is the concept of data programming.

Machine Learning 255

Machine Learning Data Quality Statistics Modeling 255

datapine

JANUARY 31, 2022

BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Domino Data Lab

AUGUST 12, 2021

For data, this refinement includes doing some cleaning and manipulations that provide a better understanding of the information that we are dealing with. In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. API Data Pipelines : These pipelines retrieve data from various APIs and load it into a database or application for further use.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Domino Data Lab

AUGUST 1, 2021

The plot below is an example of PDPs that show the impact of changes in features like temperature, humidity, and wind speed on the predicted number of rented bikes. PDPs for the bicycle count prediction model (Molnar, 2009). Creating a PDP for our model is fairly straightforward. References. Explainable planning.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Jet Global

MAY 1, 2023

that gathers data from many sources. Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. References Ask to speak to existing customers in similar verticals. Ask your vendors for references. It’s all about context.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52