IBM Big Data Hub

SEPTEMBER 19, 2023

Those who work in the field of data science are known as data scientists. The data science lifecycle Data science is iterative, meaning data scientists form hypotheses and experiment to see if a desired outcome can be achieved using available data.

Data Science 86

Data Science Data Analytics Prescriptive Analytics Analytics 86

FineReport

MARCH 24, 2024

Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making. Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. JPMorgan Chase & Co.:

Statistics 52

Statistics Data mining Visualization Reporting 52

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 61

Machine Learning Data Science Statistics Deep Learning 61

Smarten

JANUARY 31, 2019

Put simply, business Intelligence uses historical data to reveal where the business has been, and managers can use this data to predict competitive response and discover what is changing in customer buying behavior and in sales. How is Advanced Analytics Different from Business Intelligence?

Business Intelligence 40

Business Intelligence Analytics Predictive Modeling Forecasting 40

Jen Stirrup

OCTOBER 30, 2022

What distinguishes Data Mining from other methods of exploring data, and what is its usefulness? Critics might say that if you torture the data enough, it will eventually confess! Computers contain lots of data, but people need help to turn this data into intelligence.

Data mining 52

Data mining Predictive Analytics Cost-Benefit OLAP 52

bridgei2i

JULY 28, 2020

We need people who can test. And monitor those models, software engineers, data analysts, system administrators, and then there’s that whole process of troubleshooting and debugging, which is huge because the system is not going to run perfectly.

Enterprise 98

Enterprise Digital Transformation Insurance B2B 98

Smart Data Collective

DECEMBER 22, 2021

More companies have started using data analytics and AI tools to make the process a lot easier. Data analytics is especially useful for UX optimization. You can use analytics tools to conduct split-testing to see how visitors respond to various messages, which makes it a lot easier to improve the general layout of your design.

Big Data 136

Big Data Data mining Data-driven Predictive Analytics 136

BizAcuity

MARCH 31, 2022

you already have a data strategy in place, then it is easier to identify and analyze where AI would be the most useful for your business.Analytics Insight has an informative blog on the wide range of use-cases of AI in prominent industries. A lot of testing AI methods can be utilized for better and more accurate outcomes from mining the data.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

FineReport

JULY 18, 2022

Key features: Data analysts use Python to realize the functions like data crawling, data cleaning, data modeling, data visualization, data mining, etc. It can realize most of the functions used in general data analysis and academic data analysis. SAS Forecasting. RapidMiner.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

datapine

AUGUST 29, 2022

An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”. If we had to pick one book for an absolute newbie to the field of Data Science to read, it would be this one.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Domino Data Lab

MAY 20, 2021

Their tests are performed using C4.5-generated 1988), E-state data (Hall et al., note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). Data mining for direct marketing: Problems and solutions. Chawla et al., 1998) and others).

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

datapine

NOVEMBER 27, 2019

You simply choose the data source you want to analyze and the column/variable (for instance, revenue) that the algorithm should focus on. Then, calculations will be run and come back to you with growth/trends/forecast, value driver, key segments correlations, anomalies, and what-if analysis.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

MAY 1, 2023

Healthcare is forecasted for significant growth in the near future. 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.” Bid Goodbye to Standalone Users don’t want to have to leave their app or call IT for insights.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52