CIO Business Intelligence

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics? Data analytics tools.

Data Analytics 132

Data Analytics Diagnostic Analytics Management Analytics 132

Rocket-Powered Data Science

JULY 6, 2021

In at least one way, it was not different, and that was in the continued development of innovations that are inspired by data. This steady march of data-driven innovation has been a consistent characteristic of each year for at least the past decade. 2) MLOps became the expected norm in machine learning and data science projects.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

FineReport

MARCH 31, 2024

Acting as a comprehensive solution, the best BI tools collect and analyze company data to generate easily interpretable graphs, reports, and charts , leveraging advanced data mining, analytics, and visualization techniques. Best BI Tools for Data Analysts 3.1

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Smart Data Collective

MARCH 28, 2022

All the processes and techniques used in data analytics can be automated into algorithms that work on raw data. The type of data analytics best suited for a company is decided by its development stage and what type of brand and identity marketing it wishes to implement. Data analytics in education.

Data Analytics 85

Data Analytics Software Analytics Statistics 85

Decision Management Solutions

DECEMBER 8, 2020

Machine learning can improve operations, but only when its predictive models are deployed, integrated, and—most importantly—acted upon. Enterprises today are eager to apply machine learning to improve their operations. But how do they ensure that it truly serves their business operations in the most optimal way?

Machine Learning 52

Machine Learning Data mining Predictive Modeling Data-driven 52

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

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 80

Data Science Data Analytics Prescriptive Analytics Analytics 80

datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 2) Data Discovery/Visualization.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

BizAcuity

MARCH 18, 2019

Predictive analytics continues to gain popularity, and research proves that there is a gradual move toward credit scoring strategies developed using data mining and predictive analytics. Predictive analytics has played a pivotal role in streamlining the lending process.

Predictive Analytics 83

Predictive Analytics Analytics Cost-Benefit Data mining 83

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 139

Data Science Statistics Machine Learning Visualization 139

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 56

Machine Learning Data Science Statistics Deep Learning 56

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

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 56

Data mining Machine Learning Deep Learning Marketing 56

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 markets and competition are moving much more quickly these days and predicting, planning and forecasting is more important than ever.

Business Intelligence 40

Business Intelligence Analytics Predictive Modeling Forecasting 40

FineReport

MAY 29, 2020

Business Intelligence is commonly divided into four different types: reporting, analysis, monitoring, and prediction. In contrast, a BI tool emphasizes data analysis since the BI tool is often a suite comprised of the feature of reporting, monitoring, analysis, and prediction. . Innovative Data Entry .

Reporting 94

Reporting OLAP Visualization Software 94

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

IBM Big Data Hub

AUGUST 14, 2023

QRadar’s ML models use root-cause analysis automation and integration to make connections for threat and risk insights, showing interrelationships that stretched teams might miss due to turnover, inexperience and the increased sophistication and volume of threats.

Cost-Benefit 58

Cost-Benefit Machine Learning Consulting Data mining 58

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

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

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

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

Sisense

APRIL 10, 2020

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. Loading data in both R and Python. y_pred=predict(xb, y_val) val-auc=auc(y_pred,y_val).

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

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

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 98

Metadata Visualization Unstructured Data Data mining 98

Jet Global

MAY 1, 2023

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. The data may come from multiple systems or aggregated views, but the output is a centralized overview of information.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52