CIO Business Intelligence

APRIL 22, 2022

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science could help an organization build tools to predict hardware failures, enabling the organization to perform maintenance and prevent unplanned downtime.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

FineReport

APRIL 9, 2024

In addition to security concerns, achieving seamless healthcare data integration and interoperability presents its own set of challenges. The fragmented nature of healthcare systems often results in disparate data sources that hinder efficient decision-making processes.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

IBM Big Data Hub

JULY 6, 2023

What is data science? Data science is a broad, multidisciplinary field that extracts value from today’s massive data sets. It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. That’s where data science comes in.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

FineReport

MAY 29, 2020

Business Intelligence is commonly divided into four different types: reporting, analysis, monitoring, and prediction. In other words, you can view BI reporting as various styles+ dynamic data. . Interactive reports support drilling down or drilling through multiple data levels at the click of a mouse.

Reporting 94

Reporting OLAP Visualization Software 94

Smarten

JANUARY 31, 2019

Today’s Advanced Analytics Tools allow business users to leverage features like self-serve data preparation, smart data visualization and assisted predictive modeling.

Business Intelligence 40

Business Intelligence Analytics Predictive Modeling Forecasting 40

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 59

Data mining Machine Learning Deep Learning Marketing 59

IBM Big Data Hub

AUGUST 14, 2023

With QRadar EDR, security analysts can leverage attack visualization storyboards to make quick and informed decisions. It can determine root cause analysis and the orchestrate next steps based on the knowledge the models have trained on and built based on the threats your organization has faced.

Cost-Benefit 61

Cost-Benefit Machine Learning Consulting Data mining 61

Sisense

APRIL 10, 2020

It’s quite popular for its visualizations: charts, graphs, pictures, and various plots. These visualizations are useful for helping people visualize and understand trends , outliers, and patterns in data. These libraries are used for data collection, analysis, data mining, visualizations, and ML modeling.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Sisense

AUGUST 11, 2019

The sheer quantity and scope of data produced and stored by your company can make it incredibly hard to peer through the number-fog to pick out the details you need. This is where Business Analytics (BA) and Business Intelligence (BI) come in: both provide methods and tools for handling and making sense of the data at your disposal.

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

FineReport

MAY 13, 2020

Although compared to the paid version, not all free BI tool provides stunning data visualization; they offer easy-to-understand charts that can meet your basic needs. Another distinct trait of this software is its feature of data entry. Users can input the data back to the database via the web reports created by FineReport. .

OLAP 105

OLAP KPI Data mining Business Intelligence 105

datapine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. Well, what if you do care about the difference between business intelligence and data analytics?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. Working with massive structured and unstructured data sets can turn out to be complicated. So, let’s have a close look at some of the best strategies to work with large data sets.

Metadata 99

Metadata Visualization Unstructured Data Data mining 99

Domino Data Lab

AUGUST 1, 2021

the need for explainable AI is mainly motivated by the following three reasons: The need for trust – if a doctor is recommending a treatment protocol based on a prediction from a neural network, this doctor must have absolute trust in the network’s capability. According to Fox et al.,

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Smarten

MAY 24, 2018

ElegantJ BI, an innovative vendor in Business Intelligence, Augmented Analytics and Augmented Data Preparation, is pleased to announce its participation in the Gartner 2018 INDIA Data & Analytics Summit from 5 – 6th June 2018 in Mumbai, India. ElegantJ BI is proud to be a Silver Sponsor at this important event.

Analytics 40

Analytics Data Analytics Data mining Predictive Modeling 40

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 2) Data Discovery/Visualization. We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

DECEMBER 12, 2018

Advanced analytics is a comprehensive set of analytical techniques and methods designed to help businesses discover trends and patterns, solve problems, accurately predict the future and drive change using data-driven, fact-based information. What is Advanced Analytics? What Are the Benefits of Advanced Analytics?

Analytics 40

Analytics Business Intelligence Data mining Predictive Modeling 40

FineReport

MARCH 31, 2024

In 2024, business intelligence (BI) software has undergone significant advancements, revolutionizing data management and decision-making processes. Harnessing the power of advanced APIs, automation, and AI, these tools simplify data compilation, organization, and visualization, empowering users to extract actionable insights effortlessly.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. that gathers data from many sources. These tools prep that data for analysis and then provide reporting on it from a central viewpoint. These systems are designed for people whose primary job is data analysis. Consider Delta.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 9, 2024

Change Data : A method of tracking and capturing changes made to data in a database or data source, including monitoring inserts, updates, and deletes to data records in real-time or near-real-time for the purpose of keeping downstream systems, such as data warehouses, data lakes, or other applications, in sync with the source data systems.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52