DataRobot Blog

MARCH 8, 2023

Today, SAP and DataRobot announced a joint partnership to enable customers connect core SAP software, containing mission-critical business data, with the advanced Machine Learning capabilities of DataRobot to make more intelligent business predictions with advanced analytics.

Enterprise 105

Enterprise Experimentation Machine Learning Modeling 105

Rocket-Powered Data Science

JULY 7, 2019

Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics). Edge Computing (and Edge Analytics): Industry 4.0: Algorithm: A set of rules to follow to solve a problem or to decide on a particular action (e.g., See [link].

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

FineReport

MARCH 24, 2024

Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue. Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

Data Science 101

OCTOBER 31, 2019

Therefore, learning some useful data mining procedures may prove beneficial in this regard. As taught in Data Science Dojo’s data science bootcamp , you will have improved prediction and forecasting with respect to your product. Data Collection. Regression.

Data mining 77

Data mining KDD Data Science Forecasting 77

Smart Data Collective

APRIL 22, 2020

.” In their words, “by providing this tool quickly to the health care data science community, widespread adoption will lead to more effective intervention strategies and … help to curtail the worst effects of this pandemic.” Predicting Patient Treatment Outcomes. ” Jake Laperruque, representing the D.C.-based

Big Data 111

Big Data Machine Learning Risk Interactive 111

IBM Big Data Hub

AUGUST 7, 2023

Therefore, IBM observes that more clients tend to consult AI leaders to help establish governance and enhance AI and data science capabilities, an operating model in the form of co-delivery partnerships. AI models can be designed to detect anomalies in real-time site performance data.

Optimization 55

Optimization Forecasting Data-driven Strategy 55

datapine

AUGUST 29, 2022

Best for : the new intern who has no idea what data science even means. An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

O'Reilly on Data

MARCH 18, 2020

In 2019, 57% of respondents cited a lack of ML modeling and data science expertise as an impediment to ML adoption; this year, slightly more—close to 58%—did so. However, organizations need to address important data governance and data conditioning to expand and scale their AI practices. [1]

Enterprise 316

Enterprise Deep Learning Data Governance Risk 316

FineReport

JULY 18, 2022

Most data analysts are very familiar with Excel because of its simple operation and powerful data collection, storage, and analysis. Key features: Excel has basic features such as data calculation which is suitable for simple data analysis. RapidMiner. From RapidMiner. From KNIME.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

datapine

JANUARY 31, 2022

Although the oil company has been producing massive amounts of data for a long time, with the rise of new cloud-based technologies and data becoming more and more relevant in business contexts, they needed a way to manage their information at an enterprise level and keep up with the new skills in the data industry.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214