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

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. Visualizations are the best tools to make trends and general insights understandable. BI developer.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

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

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 56

IT Analytics Cost-Benefit Predictive Analytics 56

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. appeared first on IBM Blog.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

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. Having visually appealing graphics can also increase user adoption. Enables Predictive Analytics on data.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Bottom line is that analytics has migrated from a trendy feature to a got-to-have. Their dashboards were visually stunning.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52