CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? It is frequently used for economic and sales forecasting.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

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 85

Data Science Data Analytics Prescriptive Analytics Analytics 85

CIO Business Intelligence

NOVEMBER 14, 2022

Bayer Crop Science has applied analytics and decision-support to every element of its business, including the creation of “virtual factories” to perform “what-if” analyses at its corn manufacturing sites. These systems are often paired with data mining to sift through databases to produce data content relationships.

Data mining 142

Data mining Data-driven Statistics OLAP 142

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

FineReport

APRIL 26, 2023

Market Insight : Analyzing big data can help businesses understand market demand and customer behavior. For example, a computer manufacturing company could develop new models or add features to products that are in high demand. E-commerce giants like Alibaba and Amazon extensively use big data to understand the market.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

BizAcuity

MARCH 31, 2022

Not just banking and financial services, but many organizations use big data and AI to forecast revenue, exchange rates, cryptocurrencies and certain macroeconomic variables for hedging purposes and risk management. AI comes handy for managing inventory, manufacturing, production and marketing. AI in Finance. AI Platforms.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

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. How can we make it happen?

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361