O'Reilly on Data

JUNE 18, 2019

The good news is that researchers from academia recently managed to leverage that large body of work and combine it with the power of scalable statistical inference for data cleaning. HoloClean adopts the well-known “noisy channel” model to explain how data was generated and how it was “polluted.” Software 2.0 and Snorkel”.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

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. Improved decision-making will create more successful outcomes.

Data Analytics 105

Data Analytics Software Analytics Statistics 105

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. Inversion by surrogate models. they can train their own surrogate model.

Modeling 278

Modeling Machine Learning Predictive Modeling Consulting 278

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 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. Try our professional BI and analytics software for 14 days free!

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

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 139

Predictive Analytics Analytics Predictive Modeling Data mining 139

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. from 2022 to 2028.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

Domino Data Lab

OCTOBER 7, 2020

Statistical methods for analyzing this two-dimensional data exist. This statistical test is correct because the data are (presumably) bivariate normal. When there are many variables the Curse of Dimensionality changes the behavior of data and standard statistical methods give the wrong answers. Data Has Properties.

Statistics 145

Statistics Testing Predictive Modeling Big Data 145

CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. 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.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

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. Some common tools include: SAS” This proprietary statistical tool is used for data mining, statistical analysis, business intelligence, clinical trial analysis, and time-series analysis.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

O'Reilly on Data

DECEMBER 12, 2019

Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Random attacks can reveal all kinds of unexpected software and math bugs.

Machine Learning 285

Machine Learning Modeling Testing Risk Management 285

Smarten

JULY 9, 2018

Create Citizen Data Scientists with Assisted Predictive Modeling! You need Assisted Predictive Modeling (Plug n’ Play Predictive Analysis with auto-suggestions and recommendations). The Plug and Play Predictive Analytics and predictive modeling platform is suitable for business users.

Predictive Modeling 40

Predictive Modeling Modeling Predictive Analytics ROI 40

Smarten

MARCH 13, 2018

That may seem like a tall order but with the right business intelligence software, you can provide predictive analytics for business users, including assisted predictive modeling that walks users through the analytical process and allows them to achieve the best results without a sophisticated knowledge of data analytical techniques.

Predictive Modeling 40

Predictive Modeling Modeling Analytics Predictive Analytics 40

datapine

DECEMBER 4, 2019

Without a doubt, it’s a big technological advancement, and one of the big statistics buzzwords, but the extent to which it is believed to be already applied is vastly exaggerated. The commercial use of predictive analytics is a relatively new thing. The accuracy of the predictions depends on the data used to create the model.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Predictive Analytics Recreation/Entertainment 110

Smart Data Collective

MAY 23, 2021

Rodrigo Liang is CEO of SambaNova, which provides both hardware and software to businesses for the purpose of analyzing data. While this can be classed as data science, one difference is that data science tends to use a predictive model to make its analysis, while AI can be capable of analyzing based on learned knowledge and facts.

Data Science 118

Data Science Cost-Benefit Statistics Predictive Modeling 118

Domino Data Lab

JANUARY 21, 2021

Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task. Each dataset has properties that warrant producing specific statistics or charts.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

David Menninger's Analyst Perspectives

NOVEMBER 7, 2024

Even though the AI hype cycle appears to be fading, it’s still clear that the unglamorous field of artificial intelligence applied to enterprise software will be the most consequential technology change in business computing since the 1990s. The next important step is creating an enterprise planning and reporting database of record.

Forecasting 130

Forecasting Machine Learning Finance Predictive Analytics 130

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

Nor can we learn prediction intervals across a large set of parallel time series, since we are trying to generate intervals for a single global time series. With those stakes and the long forecast horizon, we do not rely on a single statistical model based on historical trends.

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

CIO Business Intelligence

OCTOBER 13, 2023

In the next six to 12 months, some of the most popular anticipated uses for gen AI include content creation (42%), data analytics (53%), software development (41%), business insight (51%), internal customer support (45%), product development (40%), security (42%), and process automation (51%).

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Data Science and Beyond

JULY 22, 2018

Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics. But it wasn’t clear to me how to market myself – my LinkedIn title at the time was “software engineer with a research background” , which is a bit of a mouthful.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

FineReport

MAY 29, 2020

Excel Vs. BI Reporting Tools, and BI Software in Reporting. Even now, Excel is still the most popular software that companies use it to make a spreadsheet and implement reporting. . BI Software VS BI Reporting Tools. Most BI software has reporting capabilities. The key to BI software is ‘data+business understanding.’ .

Reporting 94

Reporting OLAP Visualization Business Intelligence 94

Smarten

NOVEMBER 23, 2023

The Smarten Augmented Analytics suite includes Smart Data Visualization , AI and Assisted Predictive Modeling , Self-Serve Data Preparation , Natural Language Processing (NLP) and Search Analytics , SnapShot Monitoring and Alerts , and many other sophisticated features.

Publishing 62

Publishing Marketing Analytics Predictive Modeling 62

CIO Business Intelligence

JULY 28, 2022

Data scientists have extensive academic backgrounds — often in computer science, statistics, and mathematics. They specialize in building powerful algorithms, and analyzing, processing, and modeling data so they can then interpret the results to create actionable plans. Expanding data science teams. Oshkosh Corp.,

Data Science 143

Data Science IT Machine Learning Data-driven 143

AWS Big Data

DECEMBER 19, 2024

HEMA built its first ecommerce system on AWS in 2018 and 5 years later, its developers have the freedom to innovate and build software fast with their choice of tools in the AWS Cloud. These services are individual software functionalities that fulfill a specific purpose within the company.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

Smarten

JUNE 17, 2022

Smarten announces the recent certification of its Smarten Augmented Analytics Software product by CERT-IN. Smarten CEO, Kartik Patel says, “The CERT-IN certification for our Smarten suite of software products is an important credential.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Jedox

MAY 17, 2022

Financial planners , Chief Financial Officers, and analysts have all struggled to build accurate methods for predicting what’s likely to happen. Prior to the dawn of advanced statistical analysis and machine learning, predictive analytics efforts fell into 4 broad categories: Guessing , which is the default that most people revert to.

Predictive Analytics 83

Predictive Analytics Finance Analytics Forecasting 83

Sisense

AUGUST 11, 2019

Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and making an educated guess about how things will pan out in the future. BA primarily predicts what will happen in the future. What About “Business Intelligence”?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

AWS Big Data

AUGUST 21, 2024

The expected data scan is predicted by machine learning (ML) models based on prior historical run statistics. Davide Pagano is a Software Development Manager with Amazon Redshift based out of Palo Alto, specialized in building cloud-based data warehouses and analytics cloud services solutions.

Optimization 110

Optimization Data Lake Data Warehouse Cost-Benefit 110

The Data Visualisation Catalogue

APRIL 4, 2019

I believe DataView VR is the next step in the evolution of analysis and presentation software. I’ve implemented DataView in my own work and find it an excellent way to organize investment information, do data discovery and create predictive models. The user can actually see the output of the model in multiple-dimensions.

Dashboards 75

Dashboards Predictive Modeling Visualization Modeling 75

Smarten

MAY 29, 2023

World-renowned technology analysis firm Gartner defines the role this way, ‘A citizen data scientist is a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics. ‘If Automatic generation of models.

Prescriptive Analytics 52

Prescriptive Analytics Predictive Modeling Digital Transformation Data Science 52

Smarten

OCTOBER 25, 2017

My team uses augmented data preparation and self-serve data prep, and tools like smart data visualization, plug n’ play predictive analysis and assisted predictive modeling to connect all the dots, find those all-important exceptions, and identify patterns and trends so they can get ahead of the game and help us in the market.

Predictive Modeling 63

Predictive Modeling Statistics Visualization Business Analytics 63

Sisense

APRIL 10, 2020

R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. Here, we will implement the XG-Boost algorithm, an algorithm that learns on the basis of training data (which we loaded earlier in both R and Python programming languages) with the help of probability and statistics.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Smarten

APRIL 25, 2024

Artificial Intelligence (AI) and Machine Learning (ML) elements support Citizen Data Scientists and help users prepare data, achieve automated data insights and create, share and use predictive models. Users can harness the power of statistics and machine learning to uncover hidden insights and improve the overall quality of your data.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

Smarten

APRIL 19, 2024

Gartner recently estimated that the market for AI software will be nearly $134.8 The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. billion, with the market growing by 31.1% in next several years.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Smarten

DECEMBER 17, 2018

Tools like Assisted Predictive Modeling allow the average business user to become a Citizen Data Scientist with tools that offer guidance and auto-suggestions to help the user arrive at the outcome they need without being frustrated or having to call in an army of analysts and IT staff to help them complete their analysis.

Predictive Analytics 40

Predictive Analytics Predictive Modeling Analytics Statistics 40