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. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 87

Data Science Data Analytics Prescriptive Analytics Analytics 87

CIO Business Intelligence

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

Smart Data Collective

DECEMBER 19, 2021

Therefore, if you don’t preprocess the data before applying it in the machine learning or AI algorithms, you are most likely to get wrong, delayed, or no results at all. Hence, data preprocessing is essential and required. Python as a Data Processing Technology. Open Source: Python has an OSI-approved open source license.

Optimization 135

Optimization Machine Learning Data mining Statistics 135

Business Over Broadway

MARCH 13, 2019

IBM Watson Studio , an end-to-end analytics solution to help you gain insights from your data, was designed for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. Case Study: The Survey Data. Why IBM Watson Studio?

Statistics 78

Statistics Measurement Descriptive Analytics Machine Learning 78

Alation

NOVEMBER 28, 2022

Spreadsheets dominate the activities of gathering and preparing data, and performing descriptive analytics. 78 million data workers are advanced spreadsheet users. 27% of their time is spent repeating the same or similar steps every time a data source is updated or refreshed.

Descriptive Analytics 52

Descriptive Analytics Risk Sales Data-driven 52

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. The Importance of Exploratory Analytics in the Data Science Lifecycle. There is no clear end state. ref: [link].

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106