Smart Data Collective

NOVEMBER 18, 2020

You may not even know exactly which path you should pursue, since some seemingly similar fields in the data technology sector have surprising differences. We decided to cover some of the most important differences between Data Mining vs Data Science in order to finally understand which is which. What is Data Science?

Data mining 143

Data mining Data Science Informatics Statistics 143

datapine

MAY 14, 2019

Data science, also known as data-driven science, covers an incredibly broad spectrum. This interdisciplinary field of scientific methods, processes, and systems helps people extract knowledge or insights from data in a host of forms, either structured or unstructured, similar to data mining.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

Smart Data Collective

MARCH 30, 2022

Companies that know how to leverage analytics will have the following advantages: They will be able to use predictive analytics tools to anticipate future demand of products and services. They can use data on online user engagement to optimize their business models.

Analytics 116

Analytics Cost-Benefit Testing Dashboards 116

IBM Big Data Hub

JULY 6, 2023

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

datapine

MARCH 31, 2022

On the flip side, if you enjoy diving deep into the technical side of things, with the right mix of skills for business intelligence you can work a host of incredibly interesting problems that will keep you in flow for hours on end. There’s A Wealth Of Choice. SAS BI: SAS can be considered the “mother” of all BI tools.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

FineReport

APRIL 26, 2023

Descriptive Analytics is used to determine “what happened and why.” ” This type of Analytics includes traditional query and reporting settings with scorecards and dashboards. Here are the key features of RapidMiner: Offers a variety of data management approaches. Enables Predictive Analytics on data.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

IBM Big Data Hub

JULY 24, 2023

It aims to understand what’s happening within a system by studying external data. ITOA uses data mining and big data principles to analyze noisy data sets within the system and creates a framework that uses those meaningful insights to make the entire system run smoother.

IT 60

IT Analytics Cost-Benefit Predictive Analytics 60