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? Data analytics includes the tools and techniques used to perform data analysis.

Data Analytics 133

Data Analytics Diagnostic Analytics Management Analytics 133

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

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. Use decision modeling to understand real-world business problems in a way that allows machine learning to be applied effectively. After all, the end goal is to achieve better business outcomes.

Machine Learning 52

Machine Learning Data mining Predictive Modeling Data-driven 52

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

CIO Business Intelligence

APRIL 22, 2022

Data scientists are the core of most data science teams, but moving from data to analysis to production value requires a range of skills and roles. For example, data analysts should be on board to investigate the data before presenting it to the team and to maintain data models.

Data Science 139

Data Science Statistics Machine Learning Visualization 139

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? For instance, a parsing model could identify the subject, verb and object of a complete sentence. You may need to iterate this process until the results are satisfactory.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

Smart Data Collective

MARCH 28, 2022

There are four main types of data analytics: Predictive data analytics: It is used to identify various trends, causation, and correlations. It can be further classified as statistical and predictive modeling, but the two are closely associated with each other.

Data Analytics 85

Data Analytics Software Analytics Statistics 85

BizAcuity

MARCH 18, 2019

Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. Benefits of Predictive Analytics in Unsecured Consumer Loan Industry. The consumer lending business is centered on the notion of managing the risk of borrower default.

Predictive Analytics 83

Predictive Analytics Analytics Cost-Benefit Data mining 83

IBM Big Data Hub

AUGUST 14, 2023

An exponential boost to your threat detection and investigation efforts To augment your organization’s strained security expertise and resources and increase their impact, QRadar SIEM’s built-in features and add-ons use advanced machine learning models and AI to uncover those hard-to-detect threats and covert user and network behavior.

Cost-Benefit 59

Cost-Benefit Machine Learning Consulting Data mining 59

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

Sisense

AUGUST 11, 2019

BA is a catch-all expression for approaches and technologies you can use to access and explore your company’s data, with a view to drawing out new, useful insights to improve business planning and boost future performance. BA primarily predicts what will happen in the future. What About “Business Intelligence”?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

FineReport

APRIL 9, 2024

Through the utilization of predictive models, clinicians can forecast patient outcomes and resource needs, enabling early intervention and personalized care delivery. Furthermore, the implementation of healthcare data mining techniques allows organizations to uncover hidden patterns and correlations within their datasets.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

FineReport

MAY 29, 2020

The ‘data’ part is the statistics and data display. . Business understanding’ is realizing in-depth data analysis and smart data forecasting via analysis and prediction functions such as data mining, predictive modeling, and so on.

Reporting 94

Reporting OLAP Software Visualization 94

Sisense

APRIL 10, 2020

These support a wide array of uses, such as data analysis, manipulation, visualizations, and machine learning (ML) modeling. These libraries are used for data collection, analysis, data mining, visualizations, and ML modeling. Modeling in R and Python. Every library has its own purpose and benefits.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

FineReport

MAY 31, 2020

Kunci untuk software BI adalah “data+pemahaman bisnis” Bagian ‘”data” diatas adalah statistik dan tampilan data. Ini membantu Anda untuk memahami mengapa performa saat ini demikian dan cara meningkatkannya.

OLAP 52

OLAP Software Business Intelligence Data mining 52

Rocket-Powered Data Science

JULY 6, 2021

2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase.

Machine Learning 279

Machine Learning Data-driven IoT Deep Learning 279

FineReport

MAY 13, 2020

It provides data scientists and BI executives with data mining, machine learning, and data visualization capabilities to build effective data pipelines. . It also can be used to create a predictive model for various business domains and kinds of models, such as classification, regression, and clustering. .

OLAP 105

OLAP KPI Data mining Business Intelligence 105

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. It doesn’t matter if you use graphs or charts, you need to get better at data visualization. Data storage is a key component of any successful organization. Speaking of which.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

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. The end-user is another factor to consider. Most BI software in the market are self-service.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade. See Ribeiro et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Smarten

MAY 24, 2018

Smarten Augmented Analytics represents the evolution of the ElegantJ BI approach to business intelligence, and the significance of self-serve data preparation, smart visualization, and assisted predictive modeling.

Analytics 40

Analytics Data Analytics Data mining Predictive Modeling 40

Smarten

DECEMBER 12, 2018

As the analytical solutions market evolves, the advent of self-serve tools provides business users with the ability to leverage self-serve data preparation, smart data visualization and assisted predictive modeling and operate at a level that was not possible before. Ability to achieve mature modeling goals.

Analytics 40

Analytics Business Intelligence Data mining Predictive Modeling 40

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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

Jet Global

MAY 1, 2023

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.” These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52