CIO Business Intelligence

JANUARY 20, 2023

Business intelligence vs. business analytics Business analytics and BI serve similar purposes and are often used as interchangeable terms, but BI should be considered a subset of business analytics. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

Smart Data Collective

DECEMBER 19, 2021

Here are some of the disadvantages of using Python as data preprocessing technology: Python’s memory consumption is high. It is a dynamically typed language where some machine learning or data science fields prefer Statically Typed programming languages. Python Makes Decision Making Simple.

Optimization 141

Optimization Machine Learning Data mining Statistics 141

Domino Data Lab

JANUARY 21, 2021

This blog explores the challenges associated with doing such work manually, discusses the benefits of using Pandas Profiling software to automate and standardize the process, and touches on the limitations of such tools in their ability to completely subsume the core tasks required of data science professionals and statistical researchers.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

datapine

JANUARY 31, 2022

BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Business Over Broadway

MARCH 13, 2019

IBM is using the power of its Watson Studio platform to extend the power of AI to people who fall outside the realm of data science, machine learning and AI experts. IBM Watson Studio is an end-to-end analytics solution to help you gain insights from your data. The next step is to analyze the data.

Statistics 78

Statistics Measurement Descriptive Analytics Machine Learning 78

BizAcuity

MARCH 31, 2022

Artificial Intelligence Analytics. AI can be applies to all 3 major types of analytics: Descriptive Analytics: The entire journey of the descriptive and diagnostic analytics process includes data extraction, data aggregation and data mining; 3 applications where AI is widely used to reduce costs, and eliminate complex actions.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Alation

NOVEMBER 28, 2022

Or they don’t have the technical skill to extract, cleanse, or transform data they need. Spreadsheets dominate the activities of gathering and preparing data, and performing descriptive analytics. 78 million data workers are advanced spreadsheet users. Spreadsheets are dark matter.

Descriptive Analytics 52

Descriptive Analytics Sales Risk Data-driven 52

FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

MARCH 27, 2024

Nella Pubblica amministrazione c’è un ulteriore parametro che entra nella data governance: la maturità sugli open data.

Data Governance 52

Data Governance Data Lake Data Strategy Data-driven 52

Grooper

AUGUST 19, 2019

The data scientist does this. First, we have the data. We’ve cleaned, transformed, reduced, consolidated and put the data into right form. Once we have right data, we do some descriptive analytics which tells us column’s mean, median, mode, standard deviation, variance, bias, some skewness – how the data is spread.

Machine Learning 40

Machine Learning Metrics Descriptive Analytics Testing 40