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 vs. business analytics.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

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. But how do they ensure that it truly serves their business operations in the most optimal way? After all, the end goal is to achieve better business outcomes.

Machine Learning 52

Machine Learning Data mining Predictive Modeling Data-driven 52

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 82

Data Analytics Software Analytics Statistics 82

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 83

Predictive Analytics Analytics Cost-Benefit Data mining 83

IBM Big Data Hub

SEPTEMBER 19, 2023

This iterative process is known as the data science lifecycle, which usually follows seven phases: Identifying an opportunity or problem Data mining (extracting relevant data from large datasets) Data cleaning (removing duplicates, correcting errors, etc.)

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

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

CIO Business Intelligence

APRIL 22, 2022

These tools are used for a variety of data-related tasks, ranging from extracting and cleaning data, to subjecting data to algorithmic analysis via statistical methods or machine learning. Tableau: Now owned by Salesforce, Tableau is a data visualization tool.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

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 57

Machine Learning Data Science Statistics Deep Learning 57

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

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? Text analysis takes it a step farther by focusing on pattern identification across large datasets, producing more quantitative results.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

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

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

IBM Big Data Hub

AUGUST 14, 2023

Advanced analytics help detect known and unknown threats to drive consistent and faster investigations every time and empower your security analysts to make data-driven decisions. With ML analytics models, your organization can gain additional insight into user behavior with predictive modeling and baselines of what is normal for a user.

Cost-Benefit 58

Cost-Benefit Machine Learning Consulting Data mining 58

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

Sisense

APRIL 10, 2020

These libraries are used for data collection, analysis, data mining, visualizations, and ML modeling. There are also a wide array of libraries available for both languages for text processing, text analysis, and text modeling. Python has 200+ standard libraries and nearly infinite third-party libraries.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

FineReport

MAY 13, 2020

KNIME is an open-source BI tool specialized for data linkage, integration, and analysis. It provides data scientists and BI executives with data mining, machine learning, and data visualization capabilities to build effective data pipelines. .

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.

Metadata 97

Metadata Visualization Unstructured Data Data mining 97

Rocket-Powered Data Science

JULY 6, 2021

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

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.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

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

Domino Data Lab

AUGUST 1, 2021

The plot below is an example of PDPs that show the impact of changes in features like temperature, humidity, and wind speed on the predicted number of rented bikes. PDPs for the bicycle count prediction model (Molnar, 2009). Creating a PDP for our model is fairly straightforward. Guestrin, C., Why should I trust you?:

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

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.

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.” Predictive analytics use a combination of data sets from multiple sources to find relationships and correlations. Standalone is a thing of the past.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52