CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 128

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 128

CIO Business Intelligence

AUGUST 23, 2023

That need for complex mathematical modeling at scale makes the finance industry a perfect candidate for the promise of quantum computing, which makes (extremely) quick work of computations, including complex ones, delivering results in minutes or hours instead of weeks and months.

IT 79

IT Machine Learning Risk Optimization 79

FineReport

APRIL 9, 2024

From advanced analytics to predictive modeling, the evolving landscape of business intelligence is revolutionizing how data is processed and leveraged for actionable insights. In addition to these advancements, another prominent trend in data analysis is the growing impact of data visualization.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

Smarten

MARCH 18, 2019

That world exists today with the evolution of sophisticated, yet easy-to-use tools that include predictive analytics for business users, visual analytics software and tools, and self-serve data preparation.

Predictive Analytics 40

Predictive Analytics Visualization Software Analytics 40

CIO Business Intelligence

MAY 9, 2024

That includes IT, to align AI technologies with existing infrastructure; HR, on workforce development; finance, to understand funding and new business cost models; and legal and compliance, to ensure responsible use of AI. This includes skills in statistical analysis, data visualization, and predictive modeling.

Risk Management 121

Risk Management Risk Cost-Benefit Technology 121

DataKitchen

JUNE 19, 2023

Our customers start looking at the data in dashboards and models and then find many issues. Perhaps we could just chill out in those stressful situations and “let go,” as the Buddha suggests. The spiritual benefits of letting go may be profound, but finding and fixing the problem at its root is, as Samuel Florman writes, “ existential joy.”

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 122

Predictive Analytics Analytics Predictive Modeling Data mining 122

Smarten

JUNE 17, 2022

Smarten Augmented Analytics tools include Assisted Predictive Modeling , Smart Data Visualization , Self-Serve Data Preparation , Sentiment Analysis , and Clickless Analytics with natural language processing (NLP) for search analytics. CERT-IN also issues advisories, guidelines and white papers for security practices.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

IBM Big Data Hub

AUGUST 22, 2023

It uses real-world data (both real time and historical) combined with engineering, simulation or machine learning (ML) models to enhance operations and support human decision-making. Traditional AI models versus foundation models These capabilities can help to continuously determine the state of the physical object.

Unstructured Data 80

Unstructured Data Consulting Visualization IoT 80

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 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

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. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

Data Analytics 131

Data Analytics Diagnostic Analytics Management Analytics 131

Smarten

OCTOBER 25, 2023

Among the top considerations: Self-Service BI Collaborative Features Mobile BI Data Visualization Citizen Data Scientist Support Augmented Analytics If you are looking for the right BI tools or augmented analytics and data discovery solution, be sure to consider the mobility of the solution, and its ease-of-use and ease-of-access.

Visualization 67

Visualization Predictive Modeling Machine Learning Business Intelligence 67

Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ It is meant to identify crucial relationships and opportunities and risks and help the organization to accurately predict: Growth.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

FineReport

APRIL 21, 2024

Additionally, there is a growing demand for advanced analytics and data visualization tools to make data-driven decisions. Key Features of SaaS BI Tools When it comes to SaaS BI tools , one of the key features that sets them apart is their ability to provide real-time data access and visualization.

Business Intelligence 52

Business Intelligence Visualization Dashboards Data-driven 52

CIO Business Intelligence

APRIL 22, 2022

Data science could help an organization build tools to predict hardware failures, enabling the organization to perform maintenance and prevent unplanned downtime. It could help predict what to put on supermarket shelves, or how popular a product will be based on its attributes. Data must be collected and cleaned.

Data Science 139

Data Science Statistics Machine Learning Visualization 139

BizAcuity

APRIL 1, 2023

There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics. Exploratory Data Analysis (EDA) EDA is used to analyze data and summarize their main properties and characteristics using visual techniques.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. provides the user with visualizations, code editor, and debugging. Not to forget various areas of data scientists employed in, from academia to IT companies.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

BizAcuity

JANUARY 18, 2023

There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics. EDA is used to analyze data and summarize their main properties and characteristics using visual techniques. Predictive Analytics. Predictive modeling for flagging suspicious activity.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Smarten

APRIL 12, 2023

Smarten Augmented Analytics tools include Assisted Predictive Modeling , Smart Data Visualization , Self-Serve Data Preparation , Sentiment Analysis , and Clickless Analytics with natural language processing (NLP) for search analytics.

Snapshot 52

Snapshot Key Performance Indicator KPI Business Intelligence 52

DataRobot

NOVEMBER 1, 2021

Practitioners in the AI space are focused on the speed and accuracy of model predictions. But the end game for the applicability of models is not in the predictions, but the decisions they enable, and predictive models alone don’t ensure better decisions. What Is Decision Intelligence?

Machine Learning 98

Machine Learning Manufacturing Predictive Modeling Optimization 98

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Juice Analytics

JULY 6, 2018

Gathering a collection of visualizations and calling it a data story is easy (and inaccurate). Putting data on a screen is easy. Making it meaningful is so much harder. Making data-driven narrative that influences people.hard. Schedule a demo.

Slice and Dice 83

Slice and Dice Predictive Modeling Visualization Data-driven 83

Smarten

MARCH 12, 2020

A solution that provides a balance between data agility and access and data governance and security can provide solid, dependable information and the ability for users to leverage Self-Serve Data Preparation , Assisted Predictive Modeling and Smart Data Visualization while protecting the organization from risk and mitigating security issues.

Data Governance 67

Data Governance Predictive Modeling Data-driven Visualization 67

Smarten

JUNE 10, 2022

Recent studies have focused on the trends in business intelligence and augmented analytics, predicting that businesses will grow analytics within the enterprise with: Augmented Analytics to enable non-technical business users to create sophisticated data models.

Slice and Dice 52

Slice and Dice Analytics Key Performance Indicator Business Intelligence 52

CIO Business Intelligence

OCTOBER 12, 2023

We made that visually appealing to people. Generac Power Systems’ Tim Dickson is an award-winning CIO who drives transformative change through technology and talent. He’s known as a digital game changer who operates at the intersection of advanced technology and business strategy. What’s your take on the changing role of the CIO?

IoT 119

IoT Manufacturing Strategy Modeling 119

Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal. Most data starts as messy and must be molded to be usable.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

DataRobot

SEPTEMBER 17, 2021

So they create business or “decision rules” that act on the output of their predictive models to add business best practices and standardize decision-making across the organization. Some companies build models but never put them into production because they lack the necessary decision infrastructure.

Forecasting 52

Forecasting Predictive Modeling Machine Learning Cost-Benefit 52

IBM Big Data Hub

FEBRUARY 14, 2024

Other uses include Netflix offering viewing recommendations powered by models that process data sets collected from viewing history; LinkedIn uses ML to filter items in a newsfeed, making employment recommendations and suggestions on who to connect with; and Spotify uses ML models to generate its song recommendations.

Cost-Benefit 88

Cost-Benefit Insurance Unstructured Data Machine Learning 88

Sisense

MARCH 27, 2019

Unlike traditional models that look at historical data for patterns, real-time analytics focuses on understanding information as it arrives to help make faster, better decisions. To provide real-time data, these platforms use smart data storage solutions such as Redshift data warehouses , visualizations, and ad hoc analytics tools.

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

Smarten

AUGUST 21, 2019

Using the Smarten approach, users can quickly and easily prepare and analyze data and visualize and explore data, notate and highlight data and share data with others. Users can highlight trends and patterns, test hypotheses and theories to reduce business risk, and easily predict and forecast results.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

Smarten

SEPTEMBER 11, 2017

Read a report, attend a conference and your head is swirling with terms like ‘assisted predictive modeling’, plug n’ play predictive analysis, smart visualization, augmented data discovery and augmented data preparation. Assisted Predictive Modeling. What could be better than that?

Predictive Modeling 61

Predictive Modeling Analytics Predictive Analytics Forecasting 61

Juice Analytics

MARCH 11, 2021

3) That’s where our data visualization and user experience capabilities helped them turn this data into a web-based analytical tool that focused users on the metrics and peer groups they cared about. There are many paths to consider: Visual representations that reveal patterns in the data and make it more human readable.

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

Smarten

APRIL 18, 2023

The enterprise must provide self-serve tools including self-serve data preparation, assisted predictive modeling, smart data visualization and natural language processing (NLP) capability that will allow users to ask questions and get information in a Google-type environment, without coding or programming or the assistance of the IT team.

Digital Transformation 52

Digital Transformation Predictive Modeling Data Quality Enterprise 52

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. It culminates with a capstone project that requires creating a machine learning model. Data Science Dojo.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

CIO Business Intelligence

JUNE 20, 2022

IoT sensors send elevator data to the cloud platform, where analytics are applied to support business operations, including reporting, data visualization, and predictive modeling. Otis One is currently offered in 12 countries and aims to expand to an additional eight countries by year’s end. From the edge to the cloud.

Internet of Things 105

Internet of Things IoT Manufacturing Data Lake 105

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. What is machine learning?

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

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 support a wide array of uses, such as data analysis, manipulation, visualizations, and machine learning (ML) modeling.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98