David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

Data Science 341

Data Science Data Lake Data mining Deep Learning 341

Birst BI

OCTOBER 30, 2018

An analytics alternative that goes beyond descriptive analytics is called “Predictive Analytics.”. Predictive Analytics: Predicting Future Outcomes. While descriptive analytics are focused on historical performance, predictive analytics are about predicting future outcomes.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

DataRobot

JANUARY 20, 2022

— Snowflake and DataRobot AI Cloud Platform is built around the need to enable secure and efficient data sharing, the integration of disparate data sources, and the enablement of intuitive operational and clinical predictive analytics. Building data communities. . Grasping the digital opportunity.

Data-driven 145

Data-driven Experimentation Predictive Modeling Data Warehouse 145

CIO Business Intelligence

JUNE 14, 2023

CDP Data Analyst The Cloudera Data Platform (CDP) Data Analyst certification verifies the Cloudera skills and knowledge required for data analysts using CDP. The exam requires the candidate to use applications involving natural language processing, speech, computer vision, and predictive analytics.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Sisense

MARCH 27, 2019

To provide real-time data, these platforms use smart data storage solutions such as Redshift data warehouses , visualizations, and ad hoc analytics tools. This allows dashboards to show both real-time and historic data in a holistic way. Why is Real-Time BI Crucial for Organizations? Who Uses Real-Time BI?

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

IBM Big Data Hub

SEPTEMBER 19, 2023

This iterative process is known as the data science lifecycle, which usually follows seven phases: Identifying an opportunity or problem Data mining (extracting relevant data from large datasets) Data cleaning (removing duplicates, correcting errors, etc.) Watsonx comprises of three powerful components: the watsonx.ai

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54