Sisense

APRIL 10, 2020

These libraries are used for data collection, analysis, data mining, visualizations, and ML modeling. Data exploration in R and Python. Data exploration is the initial step in data analysis, yielding visualizations like charts or plots that show human users patterns and trends.

Visualization 98

Visualization Artificial Intelligence Data Mining Logistics 98

Astera

JANUARY 23, 2024

Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

AUGUST 28, 2024

Pros Robust integration with other Microsoft applications and services Support for advanced analytics techniques like automated machine learning (AutoML) and predictive modeling Microsoft offers a free version with basic features and scalable pricing options to suit organizational needs. Amongst one of the most expensive data analysis tools.

IBM Support 40

IBM Support IBM Maintenance IBM cost Data Mining 40

Insight Software

MAY 1, 2023

Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” Show how embedded analytics will enhance sales and marketing through better demos and shorter sales cycles. Standalone is a thing of the past.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52